DEPARTAMENT DE F�ISICA AT�OMICAMOLECULAR I NUCLEAR

Energy Flow and lustering algorithmsfor the re onstru tion of physi s obje tsin ATLASUNIVERSITAT DE VAL�ENCIATESIS DOCTORALM. CARMEN IGLESIAS ESCUDEROJULIO 2005

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D. ANTONIO FERRER SORIA, Catedr�ati o de la Universidad de Va-len ia y miembro del departamento de F��si a At�omi a, Mole ular y Nu learde la Fa ultad de F��si as de la Universidad de Valen ia y del Instituto deF��si a Corpus ular (IFIC) de Valen ia.CERTIFICA:Que la presente mem�oriaEnergy Flow and lustering algorithmsfor the re onstru tion of physi s obje ts in ATLAS ha sido real-izada bajo su dire i�on en el Departamento de F��si a At�omi a, Mole ular yNu lear de la Universidad de Val�en ia por D. Carmen Iglesias Es udero y onstituye su tesis para optar al grado de do tor en F��si a por la Universidadde Val�en ia.Y para que onste, en omplimiento de la legisla i�on vigente, �rma elpresente erti� ado en Valen ia a de Julio de 2005.Dr. Antonio Ferrer Soria.

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a Xosepor estar siemprea mi lado

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ContentsResumen 10.1 Introdu i�on . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10.2 Los Jets en ATLAS . . . . . . . . . . . . . . . . . . . . . . . . 10.3 El algoritmo Energy Flow . . . . . . . . . . . . . . . . . . . . 20.3.1 Energy Flow en ATLAS . . . . . . . . . . . . . . . . . 30.3.2 Apli a i�on del algoritmo Energy Flow en Atlfast . . . 50.3.3 Resultados obtenidos y on lusiones . . . . . . . . . . 60.4 Algoritmos de lusteriza ion . . . . . . . . . . . . . . . . . . . 70.4.1 Compara i�on de Algoritmos de lusteriza ion . . . . . 70.4.2 Parti ulas simuladas y re onstruidas . . . . . . . . . . 90.4.3 Idea Prin ipal del an�alisis . . . . . . . . . . . . . . . . 90.4.4 Resultados obtenidos y on lusiones . . . . . . . . . . 90.5 Test Combinado on Ha es de part�� ulas . . . . . . . . . . . . 100.5.1 Datos de part�� ulas de muy baja energ��a . . . . . . . . 110.5.2 Algoritmos de Clusteriza i�on en el Combined Test Beam 130.5.3 Idea prin ipal del anlisis . . . . . . . . . . . . . . . . . 130.5.4 Resultados obtenidos y on lusiones . . . . . . . . . . 13Introdu tion 171 Jet phenomenology in the Standard Model 211.1 The Standard Model . . . . . . . . . . . . . . . . . . . . . . . 211.1.1 Fundamental for es . . . . . . . . . . . . . . . . . . . . 221.1.2 Leptons and quarks . . . . . . . . . . . . . . . . . . . 221.1.3 Problems of the Standard Model . . . . . . . . . . . . 241.2 Hadron stru ture and on�nement . . . . . . . . . . . . . . . 251.2.1 Parton hard s attering . . . . . . . . . . . . . . . . . . 261.2.2 Fragmentation . . . . . . . . . . . . . . . . . . . . . . 261.2.3 Underlying Events . . . . . . . . . . . . . . . . . . . . 271.2.4 Parton Distribution Fun tion . . . . . . . . . . . . . . 281.3 Jet phenomenology . . . . . . . . . . . . . . . . . . . . . . . . 281.3.1 Jets in proton-proton ollisions . . . . . . . . . . . . . 291.4 A brief jet history . . . . . . . . . . . . . . . . . . . . . . . . 301.4.1 Jet and LHC physi s . . . . . . . . . . . . . . . . . . . 302 Physi s at the LHC 352.1 Introdu tion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352.2 The Higgs boson . . . . . . . . . . . . . . . . . . . . . . . . . 37i

ii CONTENTS2.3 Supersymmetry . . . . . . . . . . . . . . . . . . . . . . . . . . 392.4 Extra dimensions . . . . . . . . . . . . . . . . . . . . . . . . . 402.5 The quark-gluon plasma . . . . . . . . . . . . . . . . . . . . . 412.6 CP violation beyond the Standard Model . . . . . . . . . . . 423 Des ription of the ATLAS Experiment 473.1 The proton-proton ollider: LHC . . . . . . . . . . . . . . . . 473.2 The ATLAS dete tor . . . . . . . . . . . . . . . . . . . . . . . 523.3 Main sub-dete tors of ATLAS . . . . . . . . . . . . . . . . . . 533.3.1 Parti le identi� ation . . . . . . . . . . . . . . . . . . 543.3.2 Useful Coordinates . . . . . . . . . . . . . . . . . . . . 563.4 Inner Dete tor . . . . . . . . . . . . . . . . . . . . . . . . . . 573.5 Magnet System . . . . . . . . . . . . . . . . . . . . . . . . . . 593.6 Calorimeters . . . . . . . . . . . . . . . . . . . . . . . . . . . 603.6.1 Ele tromagneti Calorimeter . . . . . . . . . . . . . . 633.6.2 Hadroni Calorimeters . . . . . . . . . . . . . . . . . . 653.7 Muon Spe trometer . . . . . . . . . . . . . . . . . . . . . . . 683.8 Trigger Chambers . . . . . . . . . . . . . . . . . . . . . . . . 693.9 Trigger and Data-a quisition system . . . . . . . . . . . . . . 703.10 Computing . . . . . . . . . . . . . . . . . . . . . . . . . . . . 733.10.1 Computing Model . . . . . . . . . . . . . . . . . . . . 743.10.2 Relations with the LCG proje t and with Grid mid-dleware providers . . . . . . . . . . . . . . . . . . . . . 773.11 Appendix1: Event Store . . . . . . . . . . . . . . . . . . . . . 784 Calorimetry 814.1 Introdu tion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 814.2 Basi on epts of Calorimetry . . . . . . . . . . . . . . . . . . 814.2.1 Ele tromagneti Calorimetry . . . . . . . . . . . . . . 834.2.2 Experimental requirement and limitation of ele tro-magneti alorimeters . . . . . . . . . . . . . . . . . . 854.2.3 Hadroni Calorimetry . . . . . . . . . . . . . . . . . . 874.2.4 Energy resolution and limitation of hadroni alorime-ters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 905 Full Simulation and Re onstru tion in ATHENA 975.1 Introdu tion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 975.2 Full Simulation: GEANT . . . . . . . . . . . . . . . . . . . . 985.3 Athena Framework . . . . . . . . . . . . . . . . . . . . . . . . 1005.3.1 Athena Components . . . . . . . . . . . . . . . . . . . 101

CONTENTS iii5.4 ATLAS o�ine software organization . . . . . . . . . . . . . . 1025.5 Athena Algorithms . . . . . . . . . . . . . . . . . . . . . . . . 1035.5.1 Tra king . . . . . . . . . . . . . . . . . . . . . . . . . . 1045.5.2 Ele tron and photon identi� ation . . . . . . . . . . . 1055.5.3 Muon identi� ation and re onstru tion . . . . . . . . . 1065.5.4 Jet re onstru tion . . . . . . . . . . . . . . . . . . . . 1065.5.5 Missing transverse energy . . . . . . . . . . . . . . . . 1095.5.6 Other sofwtare algorithms . . . . . . . . . . . . . . . . 1105.6 Monte Carlo event generators . . . . . . . . . . . . . . . . . . 1115.6.1 Pythia . . . . . . . . . . . . . . . . . . . . . . . . . . . 1115.7 Athena releases used . . . . . . . . . . . . . . . . . . . . . . . 1126 ATLFAST: the Fast Simulation 1156.1 Introdu tion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1156.2 Atlfast: Fast Simulation and re onstru tion . . . . . . . . . . 1156.3 ATHENA-Atlfast organization . . . . . . . . . . . . . . . . . 1186.3.1 Cells and Clusters . . . . . . . . . . . . . . . . . . . . 1196.3.2 Isolated ele trons, photons and muons . . . . . . . . . 1206.3.3 Jet Re onstru tion in Atlfast . . . . . . . . . . . . . . 1216.3.4 Missing transverse energy . . . . . . . . . . . . . . . . 1226.3.5 AtlfastB Algorithm for jet energy alibration and mis-tagging . . . . . . . . . . . . . . . . . . . . . . . . . . 1226.3.6 Jet energy re alibration . . . . . . . . . . . . . . . . . 1226.3.7 Tra k re onstru tion . . . . . . . . . . . . . . . . . . . 1237 Jet Algorithms in ATLAS 1257.1 From partons to re onstru ted jets . . . . . . . . . . . . . . . 1257.2 Role of Jets in LHC Physi s . . . . . . . . . . . . . . . . . . . 1277.3 Jet Measurement . . . . . . . . . . . . . . . . . . . . . . . . . 1277.3.1 Experimental aspe ts of the jet energy re onstru tion 1287.4 Jet Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . 1297.4.1 Cone Algorithm . . . . . . . . . . . . . . . . . . . . . 1307.4.2 KT Algorithm . . . . . . . . . . . . . . . . . . . . . . 1337.4.3 MGS Algorithm . . . . . . . . . . . . . . . . . . . . . 1357.4.4 Performan e of the jet algorithms (TDR Results) . . . 1357.5 A tual Jet Re onstru tion in ATLAS . . . . . . . . . . . . . . 1367.6 Appendix 1: Jet Algorithms in CDF . . . . . . . . . . . . . . 138

iv CONTENTS8 Energy Flow in Atlfast 1438.1 Introdu tion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1438.2 Aim of this hapter . . . . . . . . . . . . . . . . . . . . . . . . 1438.3 Energy Flow Con ept . . . . . . . . . . . . . . . . . . . . . . 1448.4 Parameterization of the energy in Atlfast . . . . . . . . . . . 1478.5 Generation with PYTHIA 6.2 . . . . . . . . . . . . . . . . . . 1488.6 Re onstru tion and Simulation with Atlfast . . . . . . . . . . 1498.7 Parti le level omposition of the jets . . . . . . . . . . . . . . 1508.7.1 Number of parti les forming the jets . . . . . . . . . . 1518.7.2 Jet energy in the alorimeter . . . . . . . . . . . . . . 1528.7.3 Jet ET fra tion arried by harged hadrons . . . . . . 1548.8 Study of the overlapping of parti les . . . . . . . . . . . . . . 1548.8.1 Classi� ation of the \ ells" . . . . . . . . . . . . . . . 1558.8.2 Jet ET resolution with and without Energy Flow . . . 1588.9 PT spe trum of parti les, Underlying Events and MinimumBias . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1628.9.1 Transverse Energy of single parti les . . . . . . . . . . 1628.9.2 E�e t of Underlying Events . . . . . . . . . . . . . . . 1638.9.3 Appli ation of Energy Flow with Underlying Events . 1668.9.4 E�e t of Minimum Bias Events . . . . . . . . . . . . . 1678.9.5 Transverse Energy Deposited by Soft Pro esses . . . . 1698.9.6 Pile-Up Events at high luminosity . . . . . . . . . . . 1708.10 Con lusions and further studies . . . . . . . . . . . . . . . . . 1719 Clustering algorithms in ATLAS re onstru tion software 1779.1 Introdu tion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1779.2 O�-line re onstru tion . . . . . . . . . . . . . . . . . . . . . . 1779.2.1 Cell sele tion . . . . . . . . . . . . . . . . . . . . . . . 1789.2.2 Cluster formation . . . . . . . . . . . . . . . . . . . . . 1799.2.3 Cluster lassi� ation . . . . . . . . . . . . . . . . . . . 1799.2.4 Cluster alibration . . . . . . . . . . . . . . . . . . . . 1799.2.5 Identi�ed Parti le alibration . . . . . . . . . . . . . . 1809.3 Why Clustering is useful for Energy Flow? . . . . . . . . . . . 1809.4 Clustering Algorithms . . . . . . . . . . . . . . . . . . . . . . 1819.4.1 Sliding Window Clustering . . . . . . . . . . . . . . . 1829.4.2 EGamma Clusters . . . . . . . . . . . . . . . . . . . . 1829.4.3 3D Clustering Algorithm: CaloTopoCluster . . . . . . 1839.5 Des ription of CaloTopoClusterMaker in 7.8.0 . . . . . . . . . 1849.6 CaloTopoCluster in 8.2.0 Release . . . . . . . . . . . . . . . . 1859.6.1 First luster splitter in CaloRe . . . . . . . . . . . . . 187

CONTENTS v9.7 Appendix 1: Code of CaloTopoClusterMaker . . . . . . . . . 1909.8 Appendix 2: Code of Cluster Splitter . . . . . . . . . . . . . . 19110 Clustering for simulated parti les at Very Low Energy 19510.1 Basi Idea of the analysis . . . . . . . . . . . . . . . . . . . . 19510.2 Samples of single parti le . . . . . . . . . . . . . . . . . . . . 19810.2.1 Composition of the showers . . . . . . . . . . . . . . . 19910.3 Thresholds for EM Noise . . . . . . . . . . . . . . . . . . . . . 20210.3.1 Multipli ity of TopoClusters . . . . . . . . . . . . . . . 20210.3.2 Number of TopoClusters with di�erent EM Noise . . . 20410.3.3 ET resolution with di�erent EM Noise . . . . . . . . . 20610.3.4 Mean value of ET lusterETgenerated with di�erent EM Noise . . . 20910.4 Lower thresholds for Seed and Neighbor ells . . . . . . . . . 21110.4.1 Multipli ity of TopoClusters . . . . . . . . . . . . . . . 21110.4.2 Number of TopoClusters with lower thresholds . . . . 21210.4.3 Deposited Energy . . . . . . . . . . . . . . . . . . . . 21410.4.4 ET resolution results with lower thresholds . . . . . . 21510.4.5 Mean value of ET lusterETgenerated with lower thresholds . . . . 21710.4.6 Possible double ounting . . . . . . . . . . . . . . . . . 21910.5 Cone algorithms for VLE parti les . . . . . . . . . . . . . . . 22010.5.1 Rare behavior of Cone Algorithms for VLE parti les . 22010.5.2 Preliminary on lusions about Cone Algorithm . . . . 22210.5.3 �R de�nitions for one algorithms for VLE parti les . 22310.5.4 ET resolution from one algorithms for VLE parti les 22410.6 Comparison of Cone-algorithms with TopoCluster and EGammaanalysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22610.7 TopoClusters in 8.2.0 Release . . . . . . . . . . . . . . . . . . 22810.7.1 Size of the TopoCluster: Number of ells . . . . . . . . 22810.7.2 Study of the TopoCluster with more energy . . . . . . 23210.7.3 ET resolutions for TopoClusters in 8.2.0 Release . . . 23410.7.4 Topo lusters with the ele troni noise thresholds . . . 23510.8 Con lusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23910.9 Next Step in Clustering of VLE parti les . . . . . . . . . . . . 24010.10Appendix 1: Analysis of the de ay �0 ! . . . . . . . . . . 24110.10.1 Proximity �0- . . . . . . . . . . . . . . . . . . . . . . 24110.10.2 Proximity - . . . . . . . . . . . . . . . . . . . . . . . 24210.11Appendix 2: Study of the overlap . . . . . . . . . . . . . . . . 24510.11.1 Energy Resolution with and without Splitter . . . . . 24710.11.2 Energy deposited in LArEM ell of 2nd layer . . . . . 248

vi CONTENTS10.11.3 Final on lusion about Splitter in VLE parti les . . . 24811 Combined TestBeam 2004 25111.1 Introdu tion . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25111.2 The motivation . . . . . . . . . . . . . . . . . . . . . . . . . . 25111.3 S hedule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25311.4 The setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25511.5 First measurements: debugging . . . . . . . . . . . . . . . . . 25711.6 The Measurements . . . . . . . . . . . . . . . . . . . . . . . . 25711.6.1 Calorimetry . . . . . . . . . . . . . . . . . . . . . . . . 25711.6.2 Inner Dete tor . . . . . . . . . . . . . . . . . . . . . . 25811.6.3 Muon Spe trometer . . . . . . . . . . . . . . . . . . . 25811.6.4 The LVL1 Trigger . . . . . . . . . . . . . . . . . . . . 25811.6.5 The DAQ . . . . . . . . . . . . . . . . . . . . . . . . . 25811.7 Simulation in CombinedTB . . . . . . . . . . . . . . . . . . . 25911.8 O�ine Re onstru tion and Software tools . . . . . . . . . . . 26011.9 Where the real ombination is taking pla e . . . . . . . . . . 26111.10Other important subje ts . . . . . . . . . . . . . . . . . . . . 26211.11VLE parti les in Combined Test Beam . . . . . . . . . . . . . 26211.11.1 Produ tion of parti les with low pT . . . . . . . . . . . 26312 Clustering for VLE parti les from Combined Test Beam 26712.1 Basi Idea of the analysis . . . . . . . . . . . . . . . . . . . . 26712.2 Physi s Samples from Combined TB 2004 . . . . . . . . . . . 26712.3 Energy re onstru tion . . . . . . . . . . . . . . . . . . . . . . 26812.4 Sele tion Cuts for parti les at VLE . . . . . . . . . . . . . . . 26912.4.1 Sele tion of well-de�ned tra k in TRT . . . . . . . . . 26912.4.2 Separate ele trons from �=� . . . . . . . . . . . . . . . 26912.4.3 Separate pions from muons . . . . . . . . . . . . . . . 27112.5 Number of Parti les . . . . . . . . . . . . . . . . . . . . . . . 27312.6 Clustering information in CBT ntuples . . . . . . . . . . . . . 27512.7 Clustering results for ele trons . . . . . . . . . . . . . . . . . 27612.7.1 Number of Clusters for ele trons . . . . . . . . . . . . 27612.7.2 Energy resolution of Clusters for ele trons . . . . . . . 27712.8 Improvement in the resolution of ele trons . . . . . . . . . . . 27912.8.1 Number of Clusters for ele trons . . . . . . . . . . . . 27912.8.2 Energy resolution of Clusters for ele trons . . . . . . . 28012.9 Results for pions and muons . . . . . . . . . . . . . . . . . . . 28112.10Improvement in the sele tion of parti les: �/� separation . . 28212.10.1 Se ond method: Using the longitudinal pro�le . . . . 282

CONTENTS vii12.10.2 Third method: using MDT information . . . . . . . . 28312.10.3Number of Clusters for pions and muons . . . . . . . . 28512.10.4 Energy resolution of Clusters for pions and muons . . 28612.10.5 Con lusions about pion/muon separation . . . . . . . 28612.11Con lusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28712.12Farther Analysis: Threshold hanges for lustering algorithms 28812.12.1 Sliding Window algorithm . . . . . . . . . . . . . . . . 28812.12.2 Spe ial SW algorithm for Testbeam . . . . . . . . . . 28812.12.3 TopoCluster algorithm . . . . . . . . . . . . . . . . . . 28812.13Apendix 1: Pedestal analysis . . . . . . . . . . . . . . . . . . 29012.14Apendix 2: Re ExTB, the Combined TB re onstru tion pa k-age . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29112.14.1 To get the Combined Testbeam ntuple . . . . . . . . . 29112.14.2Di�erent trees in the Root-tuple . . . . . . . . . . . . 29112.14.3 TileRe /h1000 . . . . . . . . . . . . . . . . . . . . . . 29212.14.4 TB/tree . . . . . . . . . . . . . . . . . . . . . . . . . . 29212.14.5 Calorimeters information . . . . . . . . . . . . . . . . 29312.14.6 Clustering variables : pre�x and suÆx . . . . . . . . . 29312.14.7 CALO/169 : TileCal . . . . . . . . . . . . . . . . . . . 29412.14.8 CALO/168 : Liquid Argon Calorimeter . . . . . . . . 29512.14.9 Clustering algorithm ode for CombinedTB . . . . . . 295Con lusions 301A knowledgements 304

viii CONTENTS

List of Figures0.1 Resolu i�on del momento transverso (PT ) en el Dete tor Cen-tral y resolu i�on de la energ��a transversa (ET ) en el alor��metrohadr�oni o omo fun i�on de la energ��a de las part�� ulas en elbarril entral del dete tor (� = 0). . . . . . . . . . . . . . . . 30.2 Resolu i�on de la energ��a del jet en los dos es enarios: on laapli a i�on en las CELDAS CARGADAS de la resolu i�on del alor��metro hadr�oni o o on la apli a i�on de la parametriza �ondel momento del dete tor entral, para �R = 0.4 (arriba) y�R = 0.7 (abajo). . . . . . . . . . . . . . . . . . . . . . . . . 60.3 Esquema del fun ionamiento del algoritmo TopoCluster. . . . 80.4 Esquema de la distribu i�on de los distintos omponentes delTest Combinado 2004. . . . . . . . . . . . . . . . . . . . . . . 110.5 Esquema del volumen re onstruido en el alor��metro Tile uti-lizado en la re onstru i�on de la energ��a. . . . . . . . . . . . . 121.1 Creation of new pair of quark-antiquarks. . . . . . . . . . . . 251.2 S heme of the di�erent stages in the fragmentation pro ess:hard s attering, parton shower, hadronization and �nally thede ay of the unstable primary parti les. . . . . . . . . . . . . 271.3 QCD Monte-Carlo model simulation of proton-proton olli-sion in whi h a hard 2-to-2 parton s attering with PT(hard)has o urred. The resulting event ontains parti les that orig-inate from the 2 ingoing partons (plus ISR and FSR) andparti les that ome from the break-up of the p-p (beam-beamremnants). Underlying Events is everything ex ept the 2 out-going hard s attered jets. . . . . . . . . . . . . . . . . . . . . 281.4 The jet from the parton generation to the energy depositionin the alorimeter. . . . . . . . . . . . . . . . . . . . . . . . . 292.1 Typi al ross se tions and event rates at the LHC, at ps=14TeV, assuming a luminosity of 1034 m�2s�1 . . . . . . . . . . 362.2 Signal-to-ba kground ratios for Higgs dete tion in some han-nels in ATLAS. . . . . . . . . . . . . . . . . . . . . . . . . . . 382.3 Uni� ation of the strong and ele troweak intera tions is notpossible without supersymmetri parti les (left) but is possi-ble with supersymmetri parti les (right). . . . . . . . . . . . 392.4 Simulation of a \typi al" supersymetri event in the CMSdete tor. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402.5 An ATLAS simulation of a bla k hole produ tion event at LHC. 41ix

x LIST OF FIGURES2.6 Possible signatures of the quark-gluon plasma in relativisti heavy ion ollision. . . . . . . . . . . . . . . . . . . . . . . . . 423.1 The LEP/LHC inje tor system. . . . . . . . . . . . . . . . . . 483.2 The LHC s hemati layout. . . . . . . . . . . . . . . . . . . . 513.3 General overview of the ATLAS dete tor. . . . . . . . . . . . 523.4 Signature of some highly energeti parti les in the inner dete -tor (inner tra ker), alorimeter and muon spe trometer (outertra ker). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 553.5 De�nition of azimuthal angle ' (left) and the pseudorapidity� oordinate. . . . . . . . . . . . . . . . . . . . . . . . . . . . 563.6 3 Dimensional ut-away view of the ATLAS Inner Dete tor. . 573.7 Three-dimensional view of the bare windings of the ATLASmagnet system: the entral solenoid, the air- ore barrel toroidand the two air- ore end- ap toroids. . . . . . . . . . . . . . . 603.8 View of the ATLAS alorimetry. . . . . . . . . . . . . . . . . 613.9 Sket h of the a ordion stru ture of the ele tromagneti alorime-ter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633.10 Left: The ele tron energyresolution of the ele tromagneti alorimeter system at two di�erent in lination angles, as mea-sured in a testbeam. Right: The ele tron energyresolutionas fun tion of pseudorapidity for di�erent ele tron ET , fromsimulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 643.11 Left: A Tile Calorimeter extended barrel module onstru tedin Bar elona. Right: S hema of a module of TileCal with itsdi�erent omponents: s intillator (blue), WLS �bers (green)and photomultiplier (red). . . . . . . . . . . . . . . . . . . . . 663.12 S hemati representation of the TileCal geometriy. a) repre-sents the s heme as it is onstru ted: alternating masters ansspa ers, b) gives the same geometry but from a di�erent pointof view, ) shows the path traversed by a tra k in iron ands intillator and d) represents an assembled tile alorimeterperiod. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 673.13 Left: Transverse view of the ATLAS muon spe trometer.Right: 3D view of the muon spe trometer instrumentationindi ating the di�erent hambers. . . . . . . . . . . . . . . . . 683.14 Regions of interest (ROI). . . . . . . . . . . . . . . . . . . . . 713.15 Three levels of the ATLAS trigger. . . . . . . . . . . . . . . . 72

LIST OF FIGURES xi3.16 Tier-0 at CERN is responsible for the ar hiving and distribu-tion of the primary RAW data. The derived datasets: ESD,primary AOD and TAG sets are distributed to Tier-1. Tier-2will host 1/3 of the available urrent primary AOD and thefull TAG samples. . . . . . . . . . . . . . . . . . . . . . . . . 753.17 Tier1 Sites in the world. . . . . . . . . . . . . . . . . . . . . . 764.1 Left: Energy loss me hanisms for ele trons and positrons.Right: Photon intera tion ross se tions vs. energy for lead.The total ross se tion is the sum of the ross se tions for thephotoele tri e�e t, Compton s attering, and pair produ tion. 844.2 Simulation of longitudinal development of 10 GeV ele tronshowers in Al, Fe and Pb. . . . . . . . . . . . . . . . . . . . . 854.3 S hemati of the hadroni shower development. . . . . . . . . 884.4 longitudinal pro�le of energy deposition for pion showers ofdi�erent energies. . . . . . . . . . . . . . . . . . . . . . . . . . 895.1 ATHENA-GAUDI obje t diagram, taken from [12℄. . . . . . . 1025.2 Expe ted H ! signal at the LHC for an integrated lumi-nosity of 100fb�1. Left: the signal re onstru ted in ATLASfor mH=120 GeV is shown on top of the irredu ible ba k-ground. Right: the signal re onstru ted in CMS for mH=130GeV is shown after ba kground subtra tion. . . . . . . . . . . 1055.3 Di�erent steps of the jet measurement in Athena. . . . . . . . 1085.4 S heme of the generators situation inside Athena framework. 1116.1 Comparison betweeen Full Simulation and Fast simulationexe ution, taken from [2℄. . . . . . . . . . . . . . . . . . . . . 1166.2 S heme of the di�erent steps in Atlfast: from Generators toOutput �le (Ntuple), passing for the Atlfast obje ts ( ells, lusters, re onstru ted parti les, jets ...) and the Atlfast al-gorithms, taken from [6℄ . . . . . . . . . . . . . . . . . . . . . 1176.3 Exe ution order of Algorithms in AtlfastAlgs. . . . . . . . . . 1186.4 Exe ution order of the CellMaker algorithm and ClusterMakeralgorithm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1206.5 Exe ution order of the JetMaker algorithms. . . . . . . . . . . 1227.1 The orresponden e between the parton energy and its dire -tion with the measured jet is in uen ed by many physi s anddete tor e�et s. . . . . . . . . . . . . . . . . . . . . . . . . . . 126

xii LIST OF FIGURES7.2 The energy loss of parti les depends on the polar angle (pseu-dorapidity). . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1297.3 In the one algorithm the jet is re onstru ted inside a onearound the tower with the highest ET . . . . . . . . . . . . . . 1307.4 Iterations of the position of the entroid of the luster andthe orresponding one, until the one axis oin ides with thestable entroid. . . . . . . . . . . . . . . . . . . . . . . . . . . 1317.5 Cones will be split and the shared towers will be assigned tothe losest proto-jet in (�,�) spa e. . . . . . . . . . . . . . . . 1327.6 If two protojets share more than 50% of the transverse energyof the lower ET protojet, the two jets are merged. . . . . . . 1327.7 The open arrows represent pre lusters in the event, and thesolid arrows represent the �nal jets re onstru ted by the KTalgorithm. The six diagrams show su essive iterations of thealgorithm. In ea h diagram, either a jet is de�ned (when it iswell separated from all other pre lusters), or two pre lustersare merged (when they have small relative kT ). The asterisklabels the relevant pre luster(s) at ea h step. . . . . . . . . . 1337.8 Comparison between one algorithm and kT algorithm. . . . . 1347.9 Results from a parti le level study using ATLFAST at lowluminosity (without MinimumBias events) for one algorithmwith �R =0.7 and �R =0.4 ompared with theKT and MGSAlgorithm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1357.10 Results from a parti le level study using ATLFAST at high lu-minosity (where Minimum Bias has been simulated) for onealgorithm with �R =0.7 and �R =0.4 ompared with theKT and MGS Algorithm . . . . . . . . . . . . . . . . . . . . . 1367.11 Number of jets (left) and the average transverse energy (right)above 10 GeV/ Pt in fully simulated SUSY events for Seeded one, Kt and Sedless. . . . . . . . . . . . . . . . . . . . . . . . 1377.12 The MidPoint algorithm split or merge overlapping oneswhose enters pi and pj separad by less than 2R. . . . . . . . 1397.13 An ilustration of infrared sensitivity in one algorithm. In thisexample, jet lustering begins around seed parti les, shownhere as arrows with length proportional to energy. The pres-en e of soft radiation between two jets may ause a mergingof the jets that would not o ur in the absen e of the softradiation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139

LIST OF FIGURES xiii7.14 An ilustration of ollinear sensitivity in jet re onstru tion. Inthis example, the on�guration of the left fails to produ e aseed be ause its energy is split among several dete tor towers.The on�guration on the right produ es a seed be ause itsenergy is more narrowly distributed. . . . . . . . . . . . . . . 1398.1 Improvement in jet energy resolution obtained as a fun tionof jet transverse energy in well-balan ed photon-jet events forthe CDF dete tor at the Tevatron. Also shown is the jet en-ergy resolution expe ted in ATLAS from detailed simulationdoen for the ATLAS TDR [2℄. . . . . . . . . . . . . . . . . . . 1448.2 Transverse momentum (PT ) in the Inner Dete tor and en-ergy resolution in the Hadroni Calorimeter as fun tion ofthe parti les energy in the Barrel (at � = 0). . . . . . . . . . 1468.3 Multipli ity of jets for the two radius of the jet one: �R=0.4and 0.7, and for the ET jet ranges of 20-40 GeV, 40-80 GeVand 80-160 GeV. The best PminT ut for �R=0.4 is �15 GeVand for �R=0.7 is 20 GeV, values for whi h the number ofjets has de reased and stabilized. . . . . . . . . . . . . . . . . 1498.4 Re onstru tion of the jet from stable parti les inside a oneof radios 0.4 and 0.7 after passing a ertain sele tion. . . . . . 1508.5 View of the ATLAS Inner dete tor and Calorimeters system.The overage in of the Inner Dete tor is j�j < 2:5. . . . . . . . 1518.6 Total ET of re onstru ted jets from parti les and from Atlfastfor �R=0.4 and Pt jet 40-80 GeV. . . . . . . . . . . . . . . . 1528.7 A grid of \ ells" with a granularity �� x �� = 0.1 x 0.1 isde�ned around the entral oordinate �jet-�jet of the re on-stru ted jet. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1548.8 The lassi� ation of ells depends on whi h parti le fell in it.Only harged hadrons: Charged, only photons: Neutral anda mixing between neutral and harged parti les: Mixed Cells. 1558.9 Number of times that ea h \ ell" is lassi�ed as Charged,Neutral or Mixed Cell per jet in the �-� plane, for 40-80 GeVjets with �R=0.4. . . . . . . . . . . . . . . . . . . . . . . . . 1568.10 Number of times that ea h \ ell" is lassi�ed as Charged,Neutral or Mixed Cell per jet as a fun tion of the radius �R,for 40-80 GeV jets with �R=0.4. Most are in the entral\ring", (� <0.1). . . . . . . . . . . . . . . . . . . . . . . . . . 156

xiv LIST OF FIGURES8.11 ET deposited in the �-� plane by harged hadrons in ChargedCells, photons in Neutral Cell and mixing neutral- hargedparti les in Mixed Cells per jet at 40-80 GeV with �R=0.4. . 1578.12 ET deposited in Charged, Neutral and Mixed \ ells", as afun tion of the radius DR, in the ase of 40-80 GeV withDR=0.4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1578.13 Energy resolution of the harged hadrons from HAD Calorime-ter, � 13%, for the ase of 40-80 GeV and DR=0.4 . . . . . . 1588.14 Momentum resolution of the harged hadron tra ks from In-ner Dete tor,� 1%,for the ase of 40-80 GeV and DR=0.4 . . 1588.15 For the range of 40-80 GeV and �R=0.4, the resolution inthe ET of the jet applying HAD Calorimeter parameteriza-tion is �7.9% (top) while if the parameterization of the innerdete tor is applied the resolution improves �4.8% (bottom). . 1598.16 Left: re onstru ted jet by Atlfast at 20-40 GeV with a utPminT =15 GeV for �R=0.4. Right: re onstru ted jet fromparti les at 20-40 GeV with �R=0.4. . . . . . . . . . . . . . . 1608.17 Left: re onstru ted jet by Atlfast at 20-40 GeV with a utPminT =20 GeV for �R=0.7. Right: re onstru ted jet fromparti les at 20-40 GeV with �R=0.7. . . . . . . . . . . . . . . 1618.18 Variation of the jet energy resolution for the two s enarios(hadroni alorimeter energy resolution and tra k momentumresolution from inner dete tor) for jets with �R=0.4 (left)and �R=0.7 (right). . . . . . . . . . . . . . . . . . . . . . . 1618.19 The average ET distributions of pions (top) and photons (bot-tom)for low ET jets with one �R=0.4. . . . . . . . . . . . . 1628.20 The multipli ity of harged hadrons in rease from�7.0 hargedhadrons per jet to �7.7, i.e., around 10%, when the Underly-ing Events are in luded. . . . . . . . . . . . . . . . . . . . . . 1648.21 The multipli ity of photons in rease from �7.1 photons perjet to �8.1, i.e., around 14%, when the Underlying Eventsare in luded. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1648.22 ET resolution of the jet applying Had Calorimeter parame-terization (top) and applying inner dete tor parameterization(botom) for harged ells in 40-80 GeV jets re onstru ted with�R=0.4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1668.23 Density of harged (left) and neutral (right) parti les in thesimulated Minimum Bias events for unit of rapidity . . . . . . 167

LIST OF FIGURES xv8.24 Number of total parti les ( harged and neutral) in the 4 ases:QCDJet+Underlying Events (white), QCDjets (yellow), MB(grey) and Pile-Up at low luminosity (grid histo). The �rstplot without PT ut applied and the se ond with it. . . . . . 1698.25 ET deposited in ea h ell, in the 4 ases: QCDJet+UnderlyingEvents (white), QCDjets (yellow), Minimum Bias (grey) andPile-Up at low luminosity (grid histogram). The �rst plotwithout PT ut applied and the se ond with it. . . . . . . . . 1709.1 In the 3D Clustering algorithm, the lusters are formed arounda seed ell above a ertain threshold (Seed ut = E=�noise )and they are added to the luster if their energy is above thethreshold Neighbor ut = jE=�noisej. . . . . . . . . . . . . . . 1849.2 Ele troni s noise levels (in MeV on a log s ale) for all ells asa fun tion of alorimeter layers ( olor ode) and � (x-axis). . 1859.3 PileUp noise levels (in MeV on a log s ale) for all ells as afun tion of alorimeter layers ( olor ode) and � (x-axis). . . 1869.4 The ell volumes (mm3 on a log s ale) of all ells as a fun tionof alorimeter layers ( olor ode) and � (x-axis). . . . . . . . 18710.1 Composition of the shower for the neutral pions at 5 GeV. . . 19910.2 Composition of the shower for the harged pions at 5 GeV. . 20010.3 Number of TopoCluster for �+'s and neutrons, using EM Noise=10MeV (red), EM Noise=70 MeV (green) and CaloNoiseTool(blue). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20410.4 Number of TopoCluster for �0's, using EM Noise=10 MeV(red), EM Noise=70 MeV (green) and CaloNoiseTool (blue). 20510.5 ET resolution for 1-30 GeV �+'s for TopoCluster with dif-ferent EM Noise thresholds applied (10 MeV, 70 MeV andCaloNoiseTool), the pT resolution of tra ks and the resolu-tion of the ET deposited in all the alorimeter ells. . . . . . 20610.6 ET resolution for 1-30 GeV neutrons for TopoCluster withdi�erent EM Noise thresholds applied (10 MeV, 70 MeV andCaloNoiseTool) and the resolution of the ET deposited in allthe alorimeter ells. . . . . . . . . . . . . . . . . . . . . . . . 20710.7 ET resolution for �0's from 1 to 30 GeV, where di�erentEM Noise are applied for the TopoClusters (10 MeV, 70 MeVand CaloNoiseTool). Therefore we have al ulated the EGamma lusters resolution and the resolution of the energy depositedby all the ells in the alorimeter. . . . . . . . . . . . . . . . . 208

xvi LIST OF FIGURES10.8 Mean value of the ET lusterETgenerated ratio for �0's from 1 to 30 GeV,where di�erent EM Noise are applied for the TopoClusters(10 MeV, 70 MeV and CaloNoiseTool). Therefore we have al ulated the mean value of the EGamma luster energy andthe mean value of the energy deposited by all the ells in the alorimeter . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20910.9 Mean value of the ET lusterETgenerated ratio for �+'s and neutrons from1 to 30 GeV, where di�erent EM Noise are applied for theTopoClusters (10 MeV, 70 MeV and CaloNoiseTool). There-fore we have al ulated the mean value of the tra k energywith xKalman for �+'s and the mean value of the energydeposited by all the ells in the alorimeter . . . . . . . . . . 21010.10Number of TopoCluster for �+'s and �0's using EM Noise=10MeV (red), EM Noise=70 MeV (green), CaloNoiseTool withSeedCut=30 (blue), with SeedCut=6 (bla k), with SeedCut=5(pink) and with SeedCut=4 (light blue). . . . . . . . . . . . . 21210.11Number of TopoCluster for neutrons using EM Noise=10 MeV(red), EM Noise=70 MeV (green), CaloNoiseTool with Seed-Cut=30 (blue), with SeedCut=6 (bla k), with SeedCut=5(pink) and with SeedCut=4 (light blue). . . . . . . . . . . . . 21310.12ET resolution for 1-30 GeV �+'s, whit di�erent thresholds forTopoClusters, the pT resolution of the tra ks and the resolu-tion of the ET in all the ells. . . . . . . . . . . . . . . . . . . 21510.13ET resolution for 1-30 GeV neutrons, whit di�erent thresholdsfor TopoClusters and the resolution of the ET deposited inall the ells. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21610.14ET resolution for 1-30 GeV �0's, with di�erent thresholdsfor TopoClusters, the EGamma lusters resolution and theresolution of the ET deposited in all the ells. . . . . . . . . . 21610.15Mean value of the ET lusterETgenerated ratio for 1-30 GeV �+'s, whit dif-ferent thresholds for TopoClusters, pT resolution of the tra ksand ET resolution in all the ells. . . . . . . . . . . . . . . . . 21710.16Mean value of the ET lusterETgenerated ratio for 1-30 GeV neutrons,whit di�erent thresholds for TopoClusters and ET resolutionin all the ells. . . . . . . . . . . . . . . . . . . . . . . . . . . 21710.17Mean value of the ET lusterETgenerated ratio for 1-30 GeV �0's, withdi�erent thresholds for TopoClusters, the EGamma lustersresolution and the resolution of the ET deposited in all the ells. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218

LIST OF FIGURES xvii10.18Lineal and logarithmi distributions of ET lusterET ell for TopoClus-ters, EGamma or Sliding Window lusters. . . . . . . . . . . 21910.19 E lusterEgenerated distributions at 1 GeV for EGamma- one and Topo- one. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22010.20�� distributions in TRUTH- one and TRACK- one at 1 and3 GeV. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22110.21ET resolution for 1-30 GeV �0's, where di�erent one algo-rithm are applied (always with �R = 0:1). . . . . . . . . . . . 22210.22ET resolution for 1-30 GeV �+'s, where di�erent one algo-rithm are applied (always with �R = 0:1). . . . . . . . . . . . 22210.23ET resolution for 1-30 GeV �+'s, whith di�erent one algo-rithms: TRACK- one and TRUTH- one are al ulated with�R = 1.0, 0.4, 0.2 and 0.1. . . . . . . . . . . . . . . . . . . . 22410.24ET resolution for neutrons from 1 to 30 GeV, where the onealgorithm (TRUTH- one) is al ulated with �R = 1.0, 0.4,0.2 and 0.1. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22410.25ET resolution (top) and Mean value of the ET lusterETgenerated ratio(bottom) for �0's from 1 to 30 GeV, where the one algorithm(TRUTH- one) is al ulated with �R = 1.0 and 0.1, as wellas de�ning lusters sizes of 7x3, 5x3 and 3x3 ells. . . . . . . 22510.26Comparison of ET resolution of the best one algorithms withthe rest of lustering algorithms, for 1-30 GeV harged pions.The best algorithms are TRACK- one with �R = 0.2 (darkblue line in the �gure) and TRUTH- one with �R = 0.4(bla k line), very lose one to ea h other. . . . . . . . . . . . 22610.27Comparison of ET resolution of the one algorithm with therest of lustering algorithms for 1-30 GeV neutrons. The bestalgorithm is TRUTH- one (�R <0.2.) . . . . . . . . . . . . . 22710.28Comparison of ET resolution of the one algorithm with therest of lustering algorithms for 1-30 GeV �0's. The bestalgorithms is TRUTH- one (�R <0.1). . . . . . . . . . . . . 22710.29Energy deposit of the ells whi h form the TopoClusters inthe �-�map of the whole alorimeter system for harged pionsat 5 GeV. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23110.30Energy deposit of the ells whi h form the TopoClusters inthe �-� map in the EM alorimeter for neutral pions at 5 GeV.23110.31�� = ��0 � � and �� = ��0 � � distribution from � � � oordinates of the �0's and the two de ayed photons. . . . . . 241

xviii LIST OF FIGURES10.32�R distribution from � � � oordinates of the �0's and thetwo de ayed photons. . . . . . . . . . . . . . . . . . . . . . . . 24110.33�� = � 1 � � 2 and �� = � 1 � � 2 distributions from �� � oordinates of the two de ayed photons. . . . . . . . . . . . . 24210.34�R distribution from � � � oordinates of the two de ayedphotons. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24210.35RMS of the �� and �� distribution of the two de ayed photons.24310.36The MEAN value and the RMS of the �R from the � � � oordinates of the one photon to the other. . . . . . . . . . . 24310.37�� and �� distribution of the de ayed photons from 1 and3 GeV �0's. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24310.38�R distribution of the two de ayed photons from 1 and 3GeV �0's. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24410.39Event display for a multiparti le sample with �0 = 10 GeV,�� = 10 GeV and neu = 10 GeV generated far away betweenthem. It's possible to distinguish 3 lusters from ECAL Mid-dle layer up to Tile2. . . . . . . . . . . . . . . . . . . . . . . . 24610.40Event display for a multiparti le sample with �0=10 GeVand ��=10 GeV generated to be very lose (�R=0.05). It'sdiÆ ult to distinguish the lusters in Tile. . . . . . . . . . . . 24610.41The energy deposited in LArEM ell of 2nd layer by hargedand neutral pions of very low energy (3, 5 and 10 GeV). Themean value of the energy deposited is around 280 GeV, so the orre t value for the EtDensityCut and apply orre tly theClusterSplitter to TopoCluster oming from VLE parti les ould be 250 MeV/600000 mm3. . . . . . . . . . . . . . . . . 24811.1 Setup for Combined TestBeam of the EM alorimeter (LArEM)and Hadroni alorimeter . . . . . . . . . . . . . . . . . . . . 25211.2 S hedule of the studies arried out. . . . . . . . . . . . . . . . 25411.3 Left: the Pixel setup. Center: the SCT setup. Right: theTRT setup. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25511.4 The Combined test beam setup (top view) in H8. . . . . . . . 25611.5 Geant4 Layout if the Combined Test Beam setup. . . . . . . 25911.6 Conditions Database infrastru ture . . . . . . . . . . . . . . . 26011.7 A drawing of the beam line element layout. The dimensionsare not in s ale and the elements are represented by blo ks. . 26111.8 Setup for VLE beam. . . . . . . . . . . . . . . . . . . . . . . . 263

LIST OF FIGURES xix12.1 S hema of the volume of TileCal used for the energy re on-stru tion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26812.2 Left: number of ACD ount in the 2nd Cherenkov hamberfor 9 GeV parti les: it will be possible to separate ele tronsfrom pions/muons with a ut in �650. Right: number of highlevel hits per tra k for 9 GeV parti les: with a ondition inthis variable an improvement in the eÆ ien y of the sele tionwill be a hieved. . . . . . . . . . . . . . . . . . . . . . . . . . 27012.3 Energy in the sample D of TileCal for 9 GeV parti les. Withthe ondition ESampleD < 0.15 GeV it should be possible toremove the muons from the pion sample. . . . . . . . . . . . . 27112.4 Ratio of the energy in ea h sample of TileCal respe t to thetotal energy in TileCal for pions/muons samples at 7 GeVwith the limit used in red. . . . . . . . . . . . . . . . . . . . . 27212.5 Distribution of the ET deposited by ele trons (green), pions(blue) and muons (red) in the LAr alorimeter at 2-9 GeV. . 27412.6 Number of lusters using the sliding window algorithms (SW lus-ter and SW TB luster) and the Topo EM luster algorithm,for ele trons at 1-9 GeV. . . . . . . . . . . . . . . . . . . . . . 27612.7 Energy resolution of SW luster, SW TB luster and Topo EM luster algorithm, for ele trons at 9 GeV. . . . . . . . . . . . 27812.8 Transverse energy por pions (left) and muons (right) at 9GeV in both LAr and Tile alorimeter, after applying the utE<0.1GeV as veto for muons. . . . . . . . . . . . . . . . . . . 28112.9 Fits in ea h TileCal sample in two part (peak and tail), usingthe longitudinal pro�le to sele t muons. . . . . . . . . . . . . 28212.10Layout of the di�erent MDT stations: BIL, BML, BOL, EI,EM, EO. Ea h MDT station has several eta regions. . . . . . 28312.11Number of digits in ea h MDT stations. . . . . . . . . . . . . 28412.12Transverse energy por pions (left) and muons (right) at 7 and9 GeV in both LAr and Tile alorimeter, after applying the ut in MDT statotions. . . . . . . . . . . . . . . . . . . . . . . 285

xx LIST OF FIGURES

List of Tables0.1 Resolu i�on en energ��a utilizando los algoritmos SW luster,SW TB luster y Topo luster, para ele trones a 9, 7, 5 and 3GeV. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140.2 Resolu i�on en energ��a utilizando Topo luster (LAr+Tile) parapiones y muones a 9, 7, 5 and 3 GeV, despues de apli ar ortesen las esta iones MDT del espe tr�ometro de muones. . . . . . 141.1 Matter fermions . . . . . . . . . . . . . . . . . . . . . . . . . . 233.1 LHC performan e parameters. . . . . . . . . . . . . . . . . . . 503.2 Dimensions of the ATLAS sub-dete tors. . . . . . . . . . . . . 543.3 The main parameters of the Inner Dete tor. In the end- apSCT, the resolutions vary, only a typi al number is indi ated. 583.4 The ATLAS alorimeter system. . . . . . . . . . . . . . . . . 623.5 Some Simulated Trigger Rates at LVL1 at high luminosity. . 717.1 Advantages and disadvantages between one algorithm andkT algorithm. . . . . . . . . . . . . . . . . . . . . . . . . . . . 1348.1 Numbers of generated QCD jets for the di�erent ases afterapplying the sele tion riteria. . . . . . . . . . . . . . . . . . . 1508.2 Number of sele ted stable parti les into jets in various rangesof ET for �R=0.4 and 0.7. . . . . . . . . . . . . . . . . . . . 1518.3 ET (in GeV) of sele ted stable parti les into jets for variousranges of ET for �R=0.4 and 0.7. . . . . . . . . . . . . . . . 1538.4 Proportion of Number of lassi�ed ells for the total grid(�R<0.4) and for the entral region (�R<0.1). . . . . . . . . 1568.5 ET deposited in Charged, Neutral and Mixed \ ells" respe tto the total ET of the re onstru ted jet from the stable parti les.1578.6 Jet energy resolution for the two s enarios (hadroni alorime-ter energy resolution and tra k momentum resolution frominner dete tor) and the relative improvement. . . . . . . . . . 1608.7 O upan y of ell (part / ell) with a granularity of 0.1 x 0.1in the �-� plane for only QCDjets and for UE + QCDjets. . . 1658.8 Density parti les in eta (part /eta) for only QCDjets and forUE + QCDjets. . . . . . . . . . . . . . . . . . . . . . . . . . . 1658.9 LHC predi tion for Underlying Events and Minimum BiasEvents for pp ollision at energies of p14 TeV, taken from A.Moraes studies[24℄. . . . . . . . . . . . . . . . . . . . . . . . . 165xxi

xxii LIST OF TABLES8.10 O upan y of ell (part / ell) with a granularity of 0.1x0.1for QCDjets, MB events and Pile-Up events at low luminosity. 1688.11 Density parti les in eta (part /eta) for QCDjets, MB eventsand Pile-Up events at low luminosity. . . . . . . . . . . . . . . 16910.1 Proportion of transverse energy deposited by harged pionsand neutrons in EM and Tile Calorimeter inside TopoEM andTopoTile lusters using CaloNoiseTool and Seed ut=30 andNeighbor ut=3. . . . . . . . . . . . . . . . . . . . . . . . . . . 20110.2 Multipli ity of TopoClusters for �+'s and neutrons from 1 to30 GeV, using EMNoise= 70 MeV and the default value forSeed ut (E=�noise = 30) and Neighbor ut (jE=�noisej = 3).Proportion (in %) of the existen e of 0, 1, 2 and more than 2TopoClusters in ea h event. . . . . . . . . . . . . . . . . . . . 20310.3 Multipli ity of TopoCluster for �0's and EGamma lustersfrom 1 to 30 GeV, using EMNoise= 70 MeV and the defaultvalue for Seed ut (E=�noise = 30) and Neighbor ut (jE=�noisej= 3). Proportion (in %) of the existen e of 0, 1, 2 and morethan 2 TopoClusters in ea h event. . . . . . . . . . . . . . . . 20310.4 Multipli ity of TopoCluster for �+'s and neutrons from 1 to30 GeV, using CaloNoiseTool and Seed ut=4 and Neighbor- ut=2. Per entage of the existen e of 0, 1, 2 and more than2 TopoClusters in ea h event. . . . . . . . . . . . . . . . . . . 21110.5 Multipli ity of TopoCluster for neutral pions and EGamma lusters from 1 to 30 GeV, using CaloNoiseTool and Seed- ut=4 and Neighbor ut=2. Per entage of the existen e of 0,1, 2 and more than 2 TopoClusters in ea h event. . . . . . . . 21210.6 Fra tion of energy deposited in alorimeter for Charged pionsand Neutrons from 1 to 30 GeV, for TopoClusters with dif-ferent thresholds (E=�noise) for Seed Cell and Neighbor ellsand for all the alorimeter ells. . . . . . . . . . . . . . . . . . 21410.7 Fra tion of energy deposited in alorimeter for Neutral pionsfrom 1 to 30 GeV, for TopoClusters with di�erent thresh-olds (E=�noise) for Seed Cell and Neighbor ells, for Egamma lusters and for all the alorimeter ells. . . . . . . . . . . . . 214

LIST OF TABLES xxiii10.8 Mean value of ells in TopoCluster for 1-30 GeV hargedpions, using CaloNoiseTool, Seed ut=4 and Neighbor ut=2.The 2nd olumn shows the total number of ells in all alorime-ter. The 1st table shows the total number of ells in the EM alorimeter, next to the values for the di�erent layers of this alorimeter (Presampler, Front, Middle and Ba k). The 2ndtable shows the total number of ells in TILE, next to thevalues in its samples (A, BC, D). . . . . . . . . . . . . . . . . 22810.9 Mean value of ells in TopoCluster for 1-30 GeV neutrons,using CaloNoiseTool and Seed ut=4. The 2nd olumn showsthe total number of ells in all alorimeter. The 1st tableshows the total number of ells in the EM alorimeter, nextto the values for the di�erent layers of this alorimeter (Pre-sampler, Front, Middle and Ba k). The 2nd table shows thetotal ells in TILE, next to the values in its samples (A, BC,D). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22910.10Mean value of ells in TopoCluster for 1-30 GeV �0's, usingCaloNoiseTool and Seed ut=4. The 2nd olumn shows thetotal number of ells in all alorimeter. The 3th olumn showsthe total number of ells in the EM alorimeter, next to thevalues for the di�erent layers (Presampler, Front, Middle andBa k). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23010.11Mean value of the ET deposited in TopoClusters and theproportion (in %) respe t to the total ET deposited for theTopoCluster with the maximum energy (1st TopoClusters)and the next in energy (2nd TopoCluster) for �+'s using Seed- ut=4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23210.12Mean value of the energy deposited in TopoClusters in EMand Tile alorimeter and the proportion (in %) respe t to thetotal energy deposited in all alorimeter for the TopoClusterwith the maximum energy (1st TopoClusters) and the next inenergy (2nd TopoCluster) for �+'s, using CaloNoiseTool andSeed ut=4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23210.13Mean value of the energy deposited in TopoClusters and theper entage with respe t to the total energy deposited for the1st and the 2nd TopoCluster for neutrons. . . . . . . . . . . . 23310.14Mean value of the ET deposited in TopoClusters in EM andTile and the per entage with respe t to the total ET for the1st and the 2nd TopoCluster for neutrons. . . . . . . . . . . . 233

xxiv LIST OF TABLES10.15Mean value of the ET deposited in TopoClusters and the per- entage with respe t to the total ET deposited in EM for 1stand the 2nd TopoCluster for �0's. . . . . . . . . . . . . . . . . 23310.16Energy resolution and Mean value of ET lusterETgenerated in TopoClus-ters for 1-30 GeV harged pions, using CaloNoiseTool andSeed ut=4 and Neighbor ut=2. . . . . . . . . . . . . . . . . . 23410.17Energy resolution and Mean value of ET lusterETgenerated in TopoClus-ters for 1-30 GeV neutrons, using CaloNoiseTool and Seed- ut=4 and Neighbor ut=2. . . . . . . . . . . . . . . . . . . . 23410.18Energy resolution and Mean value of ET lusterETgenerated in TopoClus-ters for 1-30 GeV neutral pions, using CaloNoiseTool andSeed ut=4. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23510.19Mean value of the ells in TopoCluster for �+ with noisethesholds using Seed ut=4. The 2nd olumn is the ells inall alorimeter. The 1st table shows the total ells in EM alo, next to the values in ea h layer (Pres, Front, Middleand Ba k). The 2nd table shows the total ells in TILE, nextto the values in its samples (A, BC, D). . . . . . . . . . . . . 23610.20Mean value of the ells in TopoCluster for �0's with noisethesholds using Seed ut=4. The 2nd olumn shows the total ells in the EM alo, next to the values in ea h layer (Pre-sampler, Front, Middle and Ba k). . . . . . . . . . . . . . . . 23710.21Comparison of the Mean value of the number of ells in ea hTopoCluster for �+'s without (no ut) and with ( ut) noisethesholds, using Seed ut=4. . . . . . . . . . . . . . . . . . . . 23710.22Comparison of the Mean value of the number of ells in ea hTopoCluster for �0's without (no ut) and with ( ut) noisethesholds, using Seed ut=4. . . . . . . . . . . . . . . . . . . . 23710.23Energy resolution and Mean value of ET lusterETgenerated in TopoClus-ters for harged pions, using CaloNoiseTool and Seed ut=4and Neighbor ut=2. . . . . . . . . . . . . . . . . . . . . . . . 23810.24Energy resolution and Mean value of ET lusterETgenerated in TopoClus-ters for neutrons, using CaloNoiseTool and Seed ut=4 andNeighbor ut=2. . . . . . . . . . . . . . . . . . . . . . . . . . . 23810.25Energy resolution and Mean value of ET lusterETgenerated in TopoClus-ters for neutral pions, using CaloNoiseTool and Seed ut=4and Neighbor ut=2. . . . . . . . . . . . . . . . . . . . . . . . 238

LIST OF TABLES xxv12.1 Number of the runs of very low energy parti les taken duringthe CombinedTB 2004 that will be used in this analysis. . . . 26712.2 Level of noise per ell for ea h part of the LAr alorimeter(Presemapler, Front, Middle and Ba k) and ea h sample ofTileCal (A, BC and D). . . . . . . . . . . . . . . . . . . . . . 26812.3 Values of the path lenght of ea h sample of the Tile alorimeter.27212.4 Conditions under the energy in ea h sample of TileCal respe tto the total energy in TileCal. The limits have been extra tedfrom the distribution of ESampleA=ET ile, ESampleBC=ET ile andESampleD=ET ile for parti les at 7, 8 and 9 GeV. . . . . . . . . 27212.5 Number of ele trons, pions and muons at 1-9 GeV depositedin LAr and their per entages with respe t to the total numberof parti les. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27312.6 Number of lusters using the sliding window algorithms (SW lus-ter and SW TB luster) and the Topo EM luster algorithm,respe t to the total number of ele trons re onstru ted at 1-9GeV. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27612.7 Energy resolution of SW luster, SW TB luster and Topo EM luster algorithm, for ele trons at 1-9 GeV. . . . . . . . . . . 27712.8 Number of lusters using the sliding window algorithms (SW lus-ter and SW TB luster) and the Topo luster algorithm, re-spe t to the total number of ele trons re onstru ted at 9, 7,5 and 3 GeV. . . . . . . . . . . . . . . . . . . . . . . . . . . . 27912.9 Energy resolution of SW luster, SW TB luster and Topo lus-ter algorithm, for ele trons at 9, 7, 5 and 3 GeV. . . . . . . . 28012.10Number of Topo lusters (LAr+Tile) respe t to the total num-ber of pions and muons re onstru ted at 9, 7, 5 and 3 GeV. . 28112.11Energy resolution of Topo luster (LAr+Tile) for pions andmuons at 9, 7, 5 and 3 GeV, applying the ut E<0.1GeV asveto for muons. . . . . . . . . . . . . . . . . . . . . . . . . . . 28112.12Set of parameters for the �t of the muon response in Tile-Cal in 2 parts: peak (p0�exp(-p2(x-p1-exp(-p2(x-p1))) and tail(exp(p3�x2 + p4�x + p5)). . . . . . . . . . . . . . . . . . . . . 28212.13Set of uts in ea h eta region of ea h MDT station to removemuons. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28512.14Number of TopoClusters respe t to the number of parti lesfor pions and muons at 9, 7, 5 and 3 GeV after appling theMDT uts. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28612.15Energy resolution of Topo luster (LAr+Tile) at 9, 7, 5 and 3GeV, after applying the MDT uts. . . . . . . . . . . . . . . . 286

xxvi LIST OF TABLES12.16Ele troni noise per ell (from pedestal) orresponding to thedi�erent runs of VLE parti les used in this analysis. Com-parison of the new proposed �noise value and the old (default)one. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 290

Resumen0.1 Introdu i�onEl LHC es un a elerador y olisionador de protones onstruido en el CERN.Di ha m�aquina fun ionar�a on una alta luminosidad (10�34 m2s�1) y abar- ar�a intervalos de energ��as desde los GeV, para ubrir la f��si a del quark b,hasta el orden de los TeV, para tratar de estudiar nueva f��si a, m�as all�a delModelo Est�andar (SM).LHC onsta de uatro dete tores, de entre ellos, ATLAS y CMS sonde prop�osito general de estudio de la f��si a que ofre e LHC. ATLAS hasido dise~nado para tener una buena alorimetr��a ele tromagn�eti a en lamedida de la energ��a e identi� a i�on de fotones y ele trones, ompletadapor una alorimetr��a hadr�oni a para realizar medidas pre isas de la energ��atransversa faltante (ETmiss) y jets gra ias a su ompleta obertura. Adem�asATLAS ser�a apaz de medir on alta pre isi�on el momento de los muones,as�� omo las traye torias de las part�� ulas argadas urvadas por efe to del ampo magn�eti o solenoidal de 2 T en la regi�on entral y el ampo toroidalen el dete tor de muones alrededor de la alorimetr��a.0.2 Los Jets en ATLASLos jets resultan de la fragmenta i�on de los partones y onsisten en horrosde part�� ulas, en su mayor��a hadrones: piones argados y neutros, algunoskaones y una peque~na propor i�on de protones y neutrones. Apare en enel dete tor omo una omposi i�on de materia hadr�oni a argada (prin ipal-mente �+'s y ��'s), de materia hadr�oni a neutra (kL y neutrones) y ele -tromagn�eti a neutra (fotones pro edentes de la desintegra i�on �0 ! ).El alor��metro hadr�oni o est�a segmentado longitudinal y transversalmenteen � (�angulo azimutal) y � (pseudorapidity), de�niendo una granularidad��x�� � 0.1x0.1 del orden del tama~no de la as ada hadr�oni a. De formaque los jets son observados omo agrupa iones (denominadas lusters) deenerg��a lo alizada en eldas de 0.1 x 0.1 en el plano �-� y suelen re onstru-irse mediante un ono entrado en la elda de mayor energ��a transversa (ET )y on un radio �R=p��2x��2 de valores 0.4 o 0.7.La orresponden ia entre los partones produ idos omo onse uen ia dela intera i�on fuerte ( ono ida omo hard-s attering) y la energ��a re onstru-ida en el alor��metro est�a in uen iada por diversos fa tores:� efe tos f��si os tales omo la fragmenta i�on, estados de radia i�on ini- ial y �nal (ISR y FSR) e intera iones de otros onstituyentes delprot�on (Underlying Events, Minimum Bias, Pile Up...),1

2 Resumen� efe tos del dete tor, omo el ampo magn�eti o, no linealidades,zonas muertas, la granularidad, el ruido ele tr�oni o y las fugas longi-tudinales de energ��a.Por tanto, la re onstru i�on de los jets no es trivial, y en mu has o asionesadem�as depende del algoritmo utilizado en la re onstru i�on del jet (tama~nodel ono, algoritmo de lusteriza i�on utilizado en la re onstru i�on de los lusters, separa i�on entre jets, solapamiento... ).La informa i�on obtenida sobre los jets ser�a ampliamente utilizada enmu hos de los anales de la f��si a de LHC. A parte de estudios de QCD,los jets se usan en an�alisis de on�rma i�on del Modelo Est�andar (re on-stru i�on de resonan ias de los bosones W y Z, o del quark top, b�usquedadel SM Higgs...), y estudios de f��si a mas all�a del SM omo dimensionesextra, supersimetr��as (SUSY)...0.3 El algoritmo Energy FlowLos argumentos dados en los apartados anteriores exigen disponer de unabuena resolu in en la medida de la energ��a de los jets. Alrededor de 2/3de la energ��a del jet provienen de part�� ulas argadas (piones y kaones),sin embargo los algoritmos de re onstru i�on de jets no utilizan la infor-ma i�on de las trazas, sino que usan s�olamente la energ��a proveniente delos alor��metros. Por esta raz�on, es interesante utilizar el algoritmo EnergyFlow. Este algoritmo onsiste en trabajar onjuntamente on la informa i�ona nivel re onstru i�on de las trazas obtenida a partir del dete tor entral yla informa i�on de la energ��a depositada en los alor��metros, omplet�andola on la identi� a i�on de part�� ulas.A bajo momento transverso (pT ), el error en el momento de las trazas esmenor que el error en la energ��a de los alor��metros. La resolu i�on relativadel sistema de trazas de ATLAS, �(pT )pT , para el aso de la zona entral delos alorimetros (que ser�a la analizada en este estudio), se puede expresar:�(PT )PT = 0:036%pT � 1:3% (0.1)Por otro lado, la resolu i�on en energ��a en el alor��metro hadr�oni o en la zona entral, para el aso de los jets, viene dada por:�(E)E = 50%pE � 3% (0.2)En la �gura 8.2 se observa que la resolu i�on del alor��metro para un pi�onde 10 GeV es del 16% mientras que se mide su pT on una pre isi�on del

0.3. El algoritmo Energy Flow 3

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0 50 100 150 200 250 300 350 400Figure 0.1: Resolu i�on del momento transverso (PT ) en el Dete tor Central y resolu i�onde la energ��a transversa (ET ) en el alor��metro hadr�oni o omo fun i�on de la energ��a delas part�� ulas en el barril entral del dete tor (� = 0).1.3%. Este omportamiento apare e �uni amente para valores muy peque~nosdel pT , e impli a que ser��a interesante apli ar el algoritmo Energy Flow paravalores de pT menores de 140 GeV, situa i�on en la ual las resolu iones deambos sistemas son iguales.De esta forma, apli ando el algoritmo Energy Flow para sustituir las u tua iones de energ��a en los alor��metros por medidas m�as pre isas delmomento se puede llegar a mejorar la resolu i�on en la energ��a de los jets.La apli a i�on de este algoritmo requiere de un buen ono imiento de laforma de la as ada dentro del alor��metro y un estudio del solapamientode part�� ulas argadas y neutras en las eldas del alor��metro, ya que esteefe to limita la e� ien ia del algoritmo.0.3.1 Energy Flow en ATLASLos ini ios de este algoritmo se remontan a la era del LEP, dentro delproye to ALEPH. Hoy en d��a, para el dete tor ATLAS, se est�a empezando adesarrollar dentro de ATHENA, el entorno de software o�ine de ATLAS, elpaquete de re onstru i�on EFlowRe que utiliza omo entradas las se~nalesdel dete tor simuladas en todo detalle. Las espe i� a iones de la alorimetr��ade ATLAS van a desempe~nar un papel importante en la de�ni in de un�optimo algoritmo Energy Flow (division en tiras en el EM, �na granulari-

4 Resumendad disponible para la medida del omienzo de la as ada hadr�oni a, gran antidad de material en dete tor interno).El dete tor ATLAS tiene una alorimetr��a hadr�oni a ex elente (mu homejor que los dete tores del LEP), pero tambin mejor que CDF y CMS,donde el algoritmo Energy Flow est�a tambi�en bajo estudio. Por ejemplo, laresolu i�on de la energa del jet1 es er ana a 8% a 50 GeV para un tama~no del ono �R = 0.7. Ni CMS on su a tual algoritmo Energy Flow ni CDF2 onsus viejos estudios se a er an a este rendimiento. La apli a i�on del EnergyFlow en ATLAS tratar�a de mejorar a�un m�as esta resolu i�on en energ��a.El pro eso patr�on para el algoritmo Energy Flow es el anal H ! b�b(�este es tambi�en el que est�a onsiderado omo el m�as interesante por CDF).A tualmente, todav��a se est�a intentando entender el fun ionamiento paralos jets aislados (sin ruido ele tr�oni o ni Pile Up).M�as re ientemente3, se ha estado estudiando por Daniel Froidevaux yElzbieta Ri hter-Was el aso de la desintegra i�on del � omo paso intermediopara entender m�as sobre la omplejidad de los jets en QCD. Este �ultimoofre e resultados prometedores, por lo menos para la desintegra i�on tau enel intervalo de energ��as de inter�es para el Higgs de baja masa (H ! ��) osimplemente para el anal Z ! �� , (que es la ontamina i�on dominante eirredu ible para el mH <150 GeV)4Por otro lado, el algoritmo desarrollado en el Reino Unido por DanTovey5 es algo diferente en �losof��a al a er amiento de Daniel/Elzbieta. Enun primer momento su fun ionamiento era bueno para las part�� ulas individ-uales pero no para los jets6, en parte debido a la aren ia de un algoritmodel lusteriza i�on que podr��a lasi� ar los lusters orrespondientes a las as adas individuales dentro de los jet a trav�es de todos los alor��metros(para este �n el algoritmo Sliding Windows no es id�oneo). Tal algoritmo esesen ial en el m�etodo Energy Flow porque el aislamiento del luster permiteresolver las ambig�uedades debido la superposi i�on de los mismos.A tualmente ya existe un algoritmo de lusteriza i�on por ve indad en 3D1V�ease el ap��tulo del ATLAS TDR en la re onstru i�on del jet, tabla 9-4, p. 2702D. Costanzo, en su Ph. D tesis obtubo una mejora del 30% utilizando el m�etodo EnergyFlow optimizado para CDF: usando informa i�on de la trazas y alorimetr��a: Sear h for aStandard Model Higgs Boson using the W pair de ay hannel at the LHC, Julio, 20003V�ease la presenta i�on de Elzbieta en la reuni�on de Jet/ETmiss, 4/3/04, en el CERN4Ri hter-Was, Elzbieta et al. Exploring hadroni tau identi� ation with DC1 datasamples: a tra k based approa h, ATL-COM-PHYS-2004-057.5Des rito en presenta iones realizadas por Dan Tovey durante la reuni�on del grupoJet/Etmiss en el CERN en 6/12/01, 7/03/02 y 11/026V�ease la presenta i�on en Athens Workshops of ATLAS Physi s Energy ow re on-stru tion: status and prospe ts, D. Tovey, Mayo del 2003

0.3. El algoritmo Energy Flow 5(CaloTopoClustermaker desarrollado por S. Menke) para generar m�ultiples lusters aislados dentro de los jets7. Con este algoritmo se anti ipa que elfun ionamiento de Energy Flow ser�a mejorado per eptiblemente. Tambi�en seutiliza el �odigo del parametriza i�on de la as ada FastShower para prede irdep�ositos de la energ��a en el alor��metro lleno de trazas argadas, y junto onel algoritmo de lusteriza i�on en 3D debe permitir redu ir las u tua ionesde energ��a de las as adas had�oni as.0.3.2 Apli a i�on del algoritmo Energy Flow en AtlfastATLFAST propor iona una r�apida simula i�on de la respuesta del dete tora las part�� ulas y su posterior re onstru i�on.En ATLFAST no hay una simula i�on detallada de las as adas en los alor��metros ni de las se~nales dejadas por las trazas en el dete tor interno,s�olamente se parametriza la resolu i�on de la energ��a en alorimetr��a, y sesimulan la e� ien ia y la resolu i�on en pT en el dete tor entral.a) Genera i�on on Pythia 6.2 de 1000 eventos de Jets QCD:- para distintos intervalos de pT del jet:20-40, 40-80 , 80-160, 160-320, 320-640 and 640-1280 GeV- En un primer momento no se in luyen Underlying Events ni PileUp (despues se in luir�an en ondi iones de baja luninosidad)- ISR y FSR son in luidos- �parton < 5.0 ( obertura del alor��metro)b) Re onstru i�on on ATLFAST 6.2.0 de jets de quarks y gluones:- Algoritmo de re onstru i�on: Cono de �R=0.4 y �R=0.7- �jet < 2.0 (dentro de la obertura del det. entral: �inner < 2.5)- diversos valores de pTmin se eligen dependiendo del �R del onode manera que la multipli idad del jet siga siendo signi� ativa:pTmin = 20 GeV si �R = 0.7 y pTmin = 15 GeV si �R = 0.4 ) Re onstru i�on del jet a partir de las part�� ulas dentro del onode �R = 0.4 o 0.7 alrededor del �jet-�jet.- Sele ionando s�olo part�� ulas estables- ET > 0.5 GeV para part�� ulas argadas- j�part j < 2.5, s�olo part�� ulas dentro de �inner (debido al posterioruso ombinado de medidas del alorimetr��a y trazas).7Presenta i�on de F. Paige en la reuni�on de Jet/ETmiss Jets from TopoClusters,23/11/04

6 Resumend) Clasi� a i�on de eldas. Se de�ne una rejilla de 81 eldas on unagranularidad ��x��=0.1x0.1 alrededor del punto de deposi i�on deljet re onstruido (�jet-�jet). A ontinua i�on, se lasi� an di has eldasseg�un la part�� ula que ae en ellas:- CELDAS CARGADAS: Celdas en las que s�olo aen part�� ulas argadas (�'s y kaones),- CELDAS NEUTRAS: Celdas en las que s�olo aen fotones,- CELDAS MIXTAS: Celdas on mez la de argadas y neutras.El algoritmo Energy Flow se apli a s�olo a las CELDAS CARGADAS pues ada part�� ula del luster llevar�a una traza aso iada y no habr�a p�erdidade energ��a. Para los hadrones argados que se en uentran en las CELDASCARGADAS, se sustituye de la resolu i�on del Calor��metro hadr�oni o (e .0.2) por la resolu i�o del Dete tor de trazas (e . 0.1).0.3.3 Resultados obtenidos y on lusionesEl uso del algoritmo Energy Flow a nivel de part�� ulas en ATLAS puedepoten ialmente mejorar la resolu i�on de la energ��a del jet (ver �g. 0.2).Esta mejora aumenta en los valores m�as bajos de pT hasta �40%. Sinembargo, alrededor de 100 GeV la superposi i�on de las part�� ulas es mayory la gana ia en resolu i�on para los jets es marginal.

Figure 0.2: Resolu i�on de la energ��a del jet en los dos es enarios: on la apli a i�on enlas CELDAS CARGADAS de la resolu i�on del alor��metro hadr�oni o o on la apli a i�onde la parametriza �on del momento del dete tor entral, para �R = 0.4 (arriba) y �R =0.7 (abajo).

0.4. Algoritmos de lusteriza ion 7Por otro lado, la in uen ia de losUnderlying Events y el Pile Up en ondi- iones de baja luminosidad puede ser insigni� ante para las resolu iones deenerg��a apli ando el algoritmo Energy Flow.Sin embargo, uno debe tener presente que se ha he ho este an�alisis us-ando un paquete de simula ion (Atlfast) r�apido pero tambi�en muy simplista,donde el efe to del dete tor y de los diversos efe tos f��si os impli ados en lagenera i�on de los jets no se han onsiderado.0.4 Algoritmos de lusteriza ionDentro del mar o a tual del software o�ine de ATLAS (Athena), dos tiposdiferentes de algoritmos de lusteriza i�on son utilizados.La re onstru i�on de la deposi i�on ele tromagn�eti a que propor iona unamedida �optima de ele trones y fotones se realiza mediante un algoritmo quebus a el entro de di ha deposi i�on. Este algoritmo es un ono alrededor del entro de gravedad de una elda y forma en una ventana de 3x5 eldas (parafotones no onvertidos) o 3x7 eldas (para ele trones y fotones onvertidos).En el aso de la re onstru i�on de las as adas hadr�oni as, las eldas er anas al entro on deposi iones de energ��a por en ima de un ierto um-bral son a~nadidas al luster. Este algoritmo es ono ido omo algoritmotopol�ogi o.0.4.1 Compara i�on de Algoritmos de lusteriza ionPara el an�alisis mostrado en los ap��tulos 9 y 10, se han utilizado los sigu-ientes algoritmos de lusteriza i�on presentes en Athena:A) Sliding Window y EGamma.El algoritmo Sliding Window (SW) es simplemente una b�usqueda dem�aximos lo ales de deposi i�on de ET en una rejilla usando una "ven-tana" de tamao �jo ompuesta de un grupo de eldas (torres del trig-ger) ontiguas en el espa io �-�. Los m�aximos lo ales son en ontradosmoviendo la ventana en � o en �. La ventana se puede ajustar a diver-sos tamaos, para poderla optimizar para diversas part��ulas/energ��as.SW realiza una re onstru i�on de la energ��a del luster muy preliminarporque no hay orre iones apli adas.Por su parte, EGamma ombina la informa i�on sobre las trazas deldete tor entral on la informa i�on de los lusters de los alor��metros,tomando el valor por defe to de SW. EGamma son las variables �utilespara la identi� a i�on de fotones y ele trones.

8 ResumenEn ambos algoritmos, el valor pre�jado es 5x5 eldas dentro de ada luster, entrado en la elda on el valor m�as grande de ET .B) TopoCluster.Es un algoritmo topol�ogi o, en este aso el luster no tiene un tama~no�jo y se onstruye alrededor de una elda origen on energ��a por en imade un ierto umbral. Se agregan las eldas ve inas si sus energ��as est�anpor en ima de otro umbral dado (ver �gura 9.1). Los ortes, que seha en para la elda origen y sus ve inas, dependen del ruido ele tr�oni oen ada elda.Figure 0.3: Esquema del fun ionamiento del algoritmo TopoCluster.En este an�alisis han sido estudiados distintos niveles de ruido y diversos ortes en la energ��a de la elda origen y las eldas ve inas:{ Ruido ele tr�oni o:- ruido en EM = 10 MeV. Demasiado bajo, no es realista. Solose usa para testar.- ruido en EM = 70 MeV. Valor por defe to para el ruido EM.- CaloNoiseTool = True. A tiva i�on del paquete que modelizael ruido ele tr�oni o{ Umbrales de energ��a:- Celda origen: E/�noise= 30, 6, 5, 4- Celdas ve inas: jE=�noisej= 3, 2.5, 2C) Algoritmo del Cone.El lusters es re onstruido a partir de las eldas en un ono de radio�R=p��2 x ��2. En este an�alisis se estudiaron diversos modosde entrar el ono y distintos valores del radio, dependiendo de lanaturaleza de la as ada: ele tromagn�eti a o hadr�oni a.

0.4. Algoritmos de lusteriza ion 90.4.2 Parti ulas simuladas y re onstruidasSe han utilizado muestras DC1 simuladas on Geant3 para generar pionesy neutrones (los omponentes prin ipales del jet) a muy baja energ��a. Sebus a entender la forma de la as ada, la energ��a depositada en las eldas yla resolu i�on en energ��a.Primero, se han generado 1000 eventos a � =0.3 (barril del alor��metro)y � =1.6 on solo un tipo de part�� ulas:- piones neutros: para entender el omportamiento de fotones en el alor��metro EM- piones argados y neutrones: para ono er mejor la as ada hadr�oni aTodas las part�� ulas han sido generadas on momento transverso (pT ) de 1a 30 GeV y sin in luir ruido ele tr�oni o.Despu�es se generaron 1000 eventos de �0's, ��'s y neutrones on ruidoele tr�oni o, para estudiar su efe to en el tama~no de la as ada y la resolu i�onen energ��a. La introdu i�on del ruido ele tr�oni o llevar�a a apli ar nuevosumbrales de energ��a en las eldas del TopoCluster.Finalmente se han generado muestras mixtas on mez la de part�� ulas,para analizar el efe to de la superposi i�on de los Topo lustes de part�� ulasneutras y argadas a muy baja energ��a (Anexo II).0.4.3 Idea Prin ipal del an�alisisComparar los diversos algoritmos de lusteriza i�on de Athena y la resolu i�onde la energ��a obtenida, on el �n de ono er el aumento en resolu i�on quese tendr��a al apli ar el algoritmo Energy Flow. Para ello al ulo la ET entodas las eldas del alor��metro y la onsidero omo la \Energy Flow dereferen ia", es de ir, la mejor resolu i�on que podr��a ser al anzada por elalgoritmo m�as so�sti ado que onsiderara la ET en todo el alor��metro. Laresolu i�on obtenida por los distintos algoritmos ser�a omparada on ella.0.4.4 Resultados obtenidos y on lusionesTopoClusters es una herramienta muy �util en el estudio de los lustersy propor iona una re onstru in muy buena de los mismos, in luso en el aso de part�� ulas de muy baja energ��a. De la primera parte del ap��tulo 10se puede on luir que usando TopoClusters on el paquete CaloNoiseTool yapli ando Seed ut = 4 y NeighborCut = 2:- se obtienen los mejores valores de la resolu i�on de la energa para �0's,��'s y neutrones

10 Resumen- el bajo rendimiento de TopoClusters para las part ulas individuales a1, 3, y 5 GeV se elimina.- Se obtiene la mayor ET depositado dentro del TopoClustersLos resultados de TopoCluster son in luso mejores que obtenido de los lus-ter EGamma para el aso de �0's.Comparando on los otros algoritmos de lusteriza i�on , TopoCluster esmuy ompetitivo para los neutrones, �+'s y �0's a muy baja energ��a respe toal mejor algoritmo de �estos asos:- el TRUTH-Cone, para neutrones y �0's, es de ir el algoritmo del ono entrado en el � � � de las part ulas generadas- el TRACK- one, para los piones argados, es de ir el algoritmo del ono entrado en el � � � de la traza en la segunda apa del dete tor entral.Cuando el ruido ele trni o es in luido, la resolu in deET para los TopoClus-ters es peor, pero apli ando los ortes:- CellThresholdOnAbsEt = 10.0*MeV- NeighborThresholdOnAbsEt = 80.0*MeV- SeedThresholdOnEt = 200.0*MeVse onsiguen valores de ET lusterETgenerated similares al aso sin ruido ele tr�oni o.Esto signi� a que es un modo m�as realista de re oger la ET depositada enlas eldas.As�� pues, el algoritmo de TopoClusters ( on los ambios anteriores) sepodra utilizar omo \herramienta est�andar" en el estudio de lusters depart�� ulas a muy baja energ��a.0.5 Test Combinado on Ha es de part�� ulasEn el a~no 2004, la olabora i�on ATLAS ha estado impli ada en un TestCombinado on ha es de part�� ulas, llamado Combined Test Beam (CTB).Una se i�on ompleta del barril del dete tor on los alor��metros ele tro-magn�eti o (EM) y hadr�oni o (HAD) y las End Cap del dete tor de muoneshan sido probadas on unas metas laras: pre-en argar los elementos �nalesy estudiar el fun ionamiento del dete tor en una toma realista de datos ombinados. Gra ias a esta experien ia, se ha adquirido maestr��a en las op-era iones y gran antidad de datos (�4.6 TeraBytes de datos, �90 millonesde eventos) que est�an ya bajo an�alisis.

0.5. Test Combinado on Ha es de part�� ulas 11

Figure 0.4: Esquema de la distribu i�on de los distintos omponentes del Test Combinado2004.Una se i�on del experimento del ATLAS (ver �g. 11.1) se ha probado on ha es de diversas part�� ulas (ele trones, muones, piones, protones yfotones) en diversas energ��as y polaridades, de 1 hasta 350 GeV, propor- ionando una oportunidad �uni a de evaluar el fun ionamiento individual delos sub-dete tores, pero tambi�en de explotar el poder de ATLAS para laidenti� a i�on y medida de las part�� ulas y entender mejor el dete tor antesde la fase de " ommissioning".Con los datos re ogidos ser�a posible realizar una re onstru i�on ombi-nada de muones y ele trones usando la informa i�on del dete tor interno, dela alorimetr��a y del sistema de muones para estudiar las p�erdidas de energ��adel muon, su identi� a i�on y la separa i�on muon/pion, as�� omo mirar lasp�erdidas de energ��a en grietas y en los bordes entre sub-dete tores. Tambi�enhabr�a estudios de identi� a i�on de ele trones y piones, separa i�on entre am-bos y formas de la as ada en diversas ondi iones (por ejemplo, variandoel material en frente o el ampo magnti o). Con los periodos de fotonesse estudiar�a su onversi�on. Los datos ser�an utilizados para los estudios devalida i�on del paquete de simula i�on Geant4/FLUKA.0.5.1 Datos de part�� ulas de muy baja energ��aPara este an�alisis se han usado los datos del Combined TestBeam 2004 a muybaja energ��a (1-9 GeV) a �=0.35, on informa i�on de ambos alor��metros(EM+HAD) e informa i�on de las trazas en el dete tor interno uni amentepro edente del TRT (el sistema de P��xel no fun ionaba). Las muestrasde 100.000 eventos ontienen una mez la de ele trones, piones y muones y

12 Resumenfueron re onstruidas apli ando la versi�on 9.1.2 y 10.0.2 de Athena.a) Re onstru i�on de la Energ��a:La energ��a total ser�a la suma de la energ��a depositada en las eldasdel alor��metro siempre que jE eldaj > �pedestal y que solo las eldas deuna peque~na regi�on alrededor del eje del haz son tomadas en uenta:- Para el alor��metro EM: 0.25 < � < 0.45, 0.15 < � < 0.15- Para el alor��metro HAD: 0.20 < � < 0.50, 0.1 < � < 0.1, que ontiene las eldas A3, A4, A5, BC3, BC4, BC5, D1 y D2, omose muestra en la �gura. 12.1.

Figure 0.5: Esquema del volumen re onstruido en el alor��metro Tile utilizado en lare onstru i�on de la energ��a.b) Separa i�on de part�� ulas:Puesto que las muestras ontienen una mez la de ele trones, muonesy piones, es ne esarios apli ar diversos ortes para sele ionar laspart�� ulas.- Sele i�on de trazas bien de�nidas en el TRT.- Cortes en el ontador de Cherenkov y en los hits de alto nivel deltrigger para separar ele trones de piones/muones.- Cortes para separar piones de muones:a) Uso de la �ultima apa del alor��metro HAD omo veto, uandoE < 6 GeV.b) uando E > 6 GeV, puesto que una fra i�on de los pionespuede al anzar la �ultima apa del alor��metro HAD, �esta yano puede ser usada omo veto. Se apli a el he ho de que elmuon deposita su energ��a uniformemente a lo largo de todoel dete tor o tambi�en diversos ortes en ada esta i�on MDTdel espe t�ometro de muones.

0.5. Test Combinado on Ha es de part�� ulas 130.5.2 Algoritmos de Clusteriza i�on en el Combined Test BeamComo resultado de la re onstru i�on se obtienen ROOT-ntuples on la sigu-iente informa i�on respe to a los algoritmos de lusteriza i�on:- Em luster: lusters pro edentes del algoritmo Sliding Window. Estealgoritmo es un ono alrededor del entro de gravedad de una elda yforma en una ventana de 3x5.- Tbem lusters: lusters pro edentes de un algoritmo usado en previostest. Este algoritmo se ha a~nadido para permitir ompara i�on. Suventana es de 3x3 eldas.Em lusters y Tbem lusters usan ambos solo eldas pro edentes del alor��metro EM.- Cmb lusters: lusters del tipo Sliding Window pero he ho a partirde torres ( ombinando EM y HAD) en vez de a partir de eldas- Topo EM luster y Topo Tile luster: En este aso el lusterno tiene un tama~no �jo y se onstruye alrededor de una elda origen on energ��a por en ima de un ierto umbral. Se agregan las eldasve inas si sus energ��as est�an por en ima de otro umbral dado. Los ortes dependen del ruido ele tr�oni o en ada elda.0.5.3 Idea prin ipal del anlisisEl objetivo general de este an�alisis es omparar los diversos algoritmos de lusteriza i�on en CBT y la resolu i�on de la energ��a obtenida, on el �nde ono er el aumento en resolu i�on que se tendr��a al apli ar el algoritmoEnergy Flow.En on reto, se pretende a�nar los ortes apli ados en TopoCluster enpresen ia de ruido ele tr�oni o, tomando omo referen ia an�alisis previos re-alizados on part�� ulas de muy baja energ��a simuladas y re onstruidas onel software de ATLAS.0.5.4 Resultados obtenidos y on lusionesLa re onstru i�on de las part�� ulas a muy baja energ��a es posible onlas herramientas disponibles en el paquete de re onstru i�on para el TestCombinado dentro del software de ATLAS.En la re onstru i�on de ele trones de 1-9 GeV, los dos algoritmos Slid-ing Window son �utiles. Los valores de la resolu i�on de energ��a obtenidosson del orden de lo esperado. Por otro lado, los resultados on el algoritmoTopoCluster son muy ompetitivos on los anteriores.

14 ResumenET Resolu i�on en energ��apart�� ulas SW luster SW TB luster Topo luster9 GeV 4.81 4.41 5.047 GeV 5.32 4.62 5.465 GeV 6.61 5.97 6.903 GeV | 8.67 10.15Table 0.1: Resolu i�on en energ��a utilizando los algoritmos SW luster, SW TB luster yTopo luster, para ele trones a 9, 7, 5 and 3 GeV.Sin embargo, ser�a ne esario apli ar algunos ambios en los valores m��nimosde energ��a impuestos a los SW lusters durante su re onstru i�on, on el �nde poder utilizar este algoritmo sobre part�� ulas ele trom�agneti as de 1-3GeV.Por su parte, la re onstru i�on de piones y muones, primero ha ne esi-tado de un exhautivo pro eso de sele i�on on el �n de separar ambos tiposde part�� ulas, apli ando distintos m�etodos dependiendo de la energ��a de laspart�� ulas. Podemos on luir que para part�� ulas on energ��as menores de 6GeV, es mejor utilizar la �ultima apa del alor��metro HAD omo veto. Sinembargo, para energ��as superiores a 6 GeV, puesto que una fra i�on de lospiones puede al anzar la �ultima apa del alor��metro HAD, �esta ya no puedeser usada omo veto. Se apli ar�a enton es el he ho de que el muon depositasu energ��a uniformemente a lo largo de todo el dete tor o tambi�en diversos ortes en ada esta i�on MDT del espe t�ometro de muones. Los mejores val-ores de resolu i�on energ�eti a para los TopoClusters se han obtenido on el�ultimo metodo, estando adem�as dentro del rango de lo esperado.ET Resolu i�on en energ��a (Topo)part�� ulas Piones Muones9 GeV 21.15 6.547 GeV 22.42 7.135 GeV 23.08 9.453 GeV 30.30 15.05Table 0.2: Resolu i�on en energ��a utilizando Topo luster (LAr+Tile) para piones ymuones a 9, 7, 5 and 3 GeV, despues de apli ar ortes en las esta iones MDT del es-pe tr�ometro de muones.No obstante, ser��a interesante realizar un estudio m�as profundo de losdiversos l��mites y ondi iones que se apli an a la energ��a en el pro eso de

0.5. Test Combinado on Ha es de part�� ulas 15re onstru i�on de un TopoCluster (Seed ut y NeighborCut), adapt�andolos apart�� ulas de muy baja energ��ia, m�as all�a del an�alisis realizado en esta tesis.De manera que entendi�esemos mejor �omo afe tan los ambios en di hosl��mites a las resolu iones o el modo en el que podemos eliminar la mayor antidad de ruido ele tr�oni o.

16 Resumen

Introdu tionThe aim of alorimetry is to perform the energy measurement of an in- ident parti le by total absorption of its kineti energy. Calorimeters playan important role at high-energy ma hines be ause, in ontrast to other de-te tors su h as magneti spe trometers, their fra tional resolution improveswith energy. In parti ular, at the LHC, alorimeters will be leading dete -tors in many measurements, su h as the re onstru tion of physi s hannelsof prime interest.From the LHC physi s point of view there are many reasons for beinginterested in jets. Apart from QCD studies, jets are used in the re onstru -tion of resonan es of the bosons W and Z, su h as W ! jj, Z ! b�b or thetop quark su h as t ! bW, in measuring jet multipli ity and total energySupersymetri (SUSY) sear hes, for jet vetoes in the entral region down tolow-pT of �15 GeV, for ba kground reje tion, for jet tagging in the forwardregion et However, the de�nition of a jet is not unique and the orresponden ebetween the parton energy and its dire tion with the measured jet har-a teristi s is in uen ed by many e�et s (related to physi s or to dete torperforman e) that have to be onsidered from the very beginning of theparton produ ed in the hard-s attering pro ess. The representation of jetsin the dete tors (espe ially alorimeters) shows a more or less severe dis-torsion of the original orrelations due to dete tor e�e ts (shower spread,signal u tuations, ineÆ ien es...). It implies that jets at the dete tor levelare mu h less well de�ned that at the orresponding generation at parti lelevel. That means that the role of the re onstru tion is very important.The jet energy resolution an be improved with the apli ation of theEnergy Flow algorithm. The aim of the Energy Flow is to make optimaluse of the dete tor information ombining the measurement of the energydeposition in alorimeter ells with the re onstru ted tra ks in the entraldete tor. In this thesis there will be a �rst step in the exploration of thepotential of the Energy Flow algorithm at LHC with the ATLAS dete tor.Nevertheless, the use of tra k momentum instead of the alorimeter en-ergy improves the energy resolution only for isolated lusters. In omplexevents and within jets, more than one parti le will deposit their energy in thesame alorimeter ell, and showers will overlap. So, Energy Flow requiresbuilding the parti le ID asso iated with the tra k. This starts running intodiÆ ulties in high tra k multipli ity environment and oarse alorimetergranularity: it requires use of advan ed lustering algorithms apable ofeÆ ient isolation of the individual showers, together with an energy depositmodel. 17

18 Introdu tionFinally, luster formation must be validated with real data. In thissense, we have used the very low energy data (1-9 GeV) of ele trons andpions taken during the Combined Testbeam 2004.In Chapter 1, a theoreti al and phenomenologi al des ription of the jetprodu tion pro esses in pp ollisions has been done, in luding a summaryof the main important omponent of the matter inside the Standard Model,as well as explanation of the parton hard s attering.The Chapter 2 des ribes the physi s at LHC. The LHC will be the �rsta elerator to explore dire tly the TeV s ale and there are good reasons toexpe t interesting dis overies (Higgs boson, Supersymmetry...), sin e thereare several indi ations that it might reveal new physi s.In Chapter 3, the LHC proje t and more spe i� ally, the ATLAS exper-iment are brie y summarized, with parti ular emphasis on the subdete torsand their performan es that are more relevant for the studies presented inthis thesis.In Chapter 4, the basi on epts of ele tromagneti and hadroni alorime-try are reviewed. In on rete, the main features of ele tron and hadronshowers are des ribed.In Chapter 5, the tools used for generating the Monte Carlo event sam-ples for the analysis presented in this thesis are reviewed. The di�erentsteps on the ATLAS simulation are summarized and the framework and themain algorithms of Athena are des ribed, in spe ial, the steps of the jetre onstru tion in Athena, as well as the available software pa kages relatedwith this task.In Chapter 6, the ATLAS fast simulation and re onstru tion program,ATLFAST, is des ribed: its main hara teristi s, its organization and thedi�erent Athena Algorithms in Atlfast, so- alled Makers, for the di�erentobje ts de�ned in Atlfast , in parti ular, the makers for jet are explained.The Chapter 7 des ribes the jet physi s in ATLAS. The di�erent fa torwhi h in uen e in the de�nition of the jets are explained, as well as thedi�erent jet algorithms availables in ATLAS: one and kT .In Chapter 8, the maximum potential gain inET resolution of the EnergyFlow algorithm at LHC with the ATLAS dete tor is estimated taking intoa ount only shower shape e�e ts in a simpli�ed way with the fast simulationand re onstru tion pa kage of ATLAS: Atlfast. The omposition of jets(parti le densities, PT spe tra and nature, et ) at parti le level as well asthe e�e ts of Underlying event and Minimum bias events at low luminosityhave been also studied.In Chapter 9, the di�erent lustering algorithms inside the o�ine soft-ware of ATLAS are des ribed: Sliding Window lustering, Egamma luster-

Introdu tion 19ing and the 3D Topologi al algorithm: CaloTopoClusters, with its di�erentapli ations and tools in 7.8.0 and 8.2.0 releases of Athena. They will be usedin the next hapter in the analysis of the single parti les at very low energy(VLE).The Chapter 10 shows a omparison among di�erent ways of re on-stru ting the lusters inside ATHENA: TopoCluster, Sliding Window lus-ter, EGamma luster and di�erent one algorithms. We show how these lustering algorithms an be tuned to obtain the best energy resolutionwhen re onstru ting very low energy parti les. These results are based onsingle parti le samples of �0�s, ���s and neutrons, simulated with Geant3during DC1 with energy between 1 and 30 GeV and simulated with andwithout ele troni noise in the alorimeter.In Chapter 11, a general des ription of the 2004 Combined Test Beamis done: a omplete sli e of the barrel dete tor and of the Muon End- apwas tested in a running period from 17 May to 15 November. The motiva-tions, the omponents and the main goals are explained as well as the CBTs hedule, hara terized by di�erent phases with an in remental presen e ofsubdete tors. Finally, the last se tion is dedi ated to the runs of very lowenergy (VLE) parti les taken in the CBT and the des ription of the spe ialsetup needed to re ord them. These will be the data used in our analysiswith lustering algorithms shown in the next hapter.The Chapter 12 shows a omparison among the di�erent lustering algo-rithms presented in the Combined Testbeam ontext: the sliding window al-gorithms (EM lusters, TBEM lusters and CMB lusters) and the TopoClus-ter (Topo EM and Topo Tile). Be ause the samples with Very Low Energy(VLE) parti les are a mixing of pions, muons and ele trons, it will be ne -essary to apply several uts in order to sele t the desired parti les, and asummary the di�erent uts developped will be done.

20 Introdu tion

Chapter 1Jet phenomenology in theStandard ModelThis hapter provides a brief theoreti al and phenomenologi al des riptionof the jet produ tion pro esses in pp ollisions.1.1 The Standard ModelIn the last de ades a new theory was developed that des ribes all of theknown for es among elementary parti les1: the Standard Model of Parti lesIntera tions. The Standard Model [1℄ is an uni�ed quantum gauge theorywhi h des ribes ele tromagneti and weak intera tions, with a QuantumChromodynami s (QCD)[2℄ se tor for the des ription of strong intera tions.A ording to this theory, all of the fundamental intera tions derive from asingle general prin iple, the requirement of lo al gauge invarian e (undersuitable transformations) of the Lagrangian fun tions des ribing them.Many years of high energy physi s s ienti� resear h have on�rmed thevalidity of the Standard Model in a wide range of experimental test. Themain goal of present and future high energy experiments, is to further he kits predi tions (like the higgs boson existen e) also looking at some notexpe ted signature indi ating new physi s beyond this theory.1Ex eption is made for Gravity whi h, as far as we know, is too weak to play anysigni� ant role in ordinary nu lear and sub-nu lear pro esses.21

22 1. Jet phenomenology in the Standard Model1.1.1 Fundamental for esThe Standard Model a tually is a olle tion of related lo al gauge theories in- orporating the three known fundamental elementary parti les intera tions:� Quantum Ele trodinami s (QED), des ribing the ele tromagneti in-tera tions, like the for e binding ele trons to nu lei.� Ele troweak Theory, whi h des ribes the weak for es responsible ofsu h pro esses like the beta-de ay of nu lei and whi h uni�es then tothe ele tromagneti ones as being di�erent aspe ts of a single (\Ele -troweak") intera tion.� Quantum Cromodinami s (QCD), the theory of strong intera tionswhi h, a ting at very short distan es, bind quarks together to makenu leons (protons and neutrons) and nu leons to make nu lei.These for es are transmitted by spe i� arriers, spin-1 parti les usu-ally referred as gauge bosons2. The ele tromagneti intera tion is des ribedin terms of photon ex hanges between harged parti les, weak for es aretransmitted by the W� ( harged urrent weak intera tions) and Z0 (neutral urrent weak intera tions) bosons while the strong intera tion are mediatedby 8 di�erent gluons oupling only to the quark \ olor harge". The andthe gluons are massless while the W� and Z0 bosons (observed for the �rsttime at CERN Sp�pS hadron ollider in 1983)[3℄ are very massive (� 80 and91 GeV respe tively).1.1.2 Leptons and quarksThe subnu lear physi al world is hara terized by the existen e of manyparti les. Most of them are unstable and de ay into the more familiar par-ti les whi h onstitute ordinary matter (photons, ele trons, protons andneutrons).In a quantum �eld theory, the elementary parti le intera tions are ex-pressed in terms of parti le ex hanges. There are two types of parti les: thebasi building blo ks of matter, known as matter parti les (`point-like" el-ementary parti les) and the intermediate intera tion parti les. The matterparti les are fermions (parti les with spin S = 12 ). They are lassi�ed intoleptons, whi h do not respond to strong intera tions, and quarks, whi h do.Both quarks and leptons are divided in three families (see Table 1.1).2A ording to the relativisti quantum theory, these arriers an equivalently be de-s ribed in terms of �elds or parti les.

1.1. The Standard Model 23Family Leptons QuarksParti le Q Parti le Q/jej1 �e 0 u 2/3e -1 d -1/32 �� 0 2/3� -1 s -1/33 �� 0 t 2/3� -1 b -1/3Table 1.1: Matter fermions.Ele trons (e), muons (�) and taus (�) (whi h an be seen as heavier repli- as of the ele trons) and their asso iated neutrinos (respe tively �e, �� and�� ), onstitute the lepton family. Leptons are spin-12 fermions not hav-ing strong intera tions and are oupled into three weak isospin generations.Ea h generation onsists of a harged lepton and the asso iated neutrinoand annot be oupled to another lepton by weak intera tions3. �ee� ! ���� ! ���� !Apart from the leptons and the , W� and Z0 gauge bosons, all otherobserved parti les have strong intera tions and are alled hadrons. Theyin lude a variety of parti les among whi h protons and neutrons. There aremany strong (even if indire t) experimental eviden es that hadrons are madeout of elementary subnu lear onstituents alled quarks held together bystrong for es, but also experien ing ele tromagneti and weak intera tions.Six di�erent kinds of quarks (also referred as \ avors") a ount for all theseveral tens of known hadrons. The u, and t (\up", \ harm" and \top"4)quark avors have ele tri harge 23 jej while d, s and b (\down", \strange"and \bottom") quarks are harge -13 jej. ud ! s ! tb !Like the leptons, all of them are spin-12 fermions and are grouped intothree generations of weak isospin. However, ontrary to the leptons, weak3This orresponds to the leptoni quantum number invarian e in weak intera tions.4The top quark was the last to be dis overed. Its experimental eviden e was found in1995 at the Tevatron by the CDF and D0 ollaborations.

24 1. Jet phenomenology in the Standard Modelintera tions an also ouple quarks belonging to di�erent generations, even ifwith a suppressed probability (parameterized by the 3x3 Cabibbo-Kobayashi-Maskawa matrix elements).Leptons, quarks and the gauge bosons are the basis of our present un-derstanding of the physi al world. In this list is a tually missing the notyet dete ted Higgs parti le[4℄, the spin-0 boson foreseen by the StandardModel to explain the me hanism for spontaneously breaking of the SU(2)Lx U(1)Y ele troweak symmetry giving mass to the W� and Z0 bosons and toquarks and leptons. Its dis overy an rightly be onsidered a fundamentalmilestone in further on�rming the Standard Model validity.Ea h elementary parti le has an asso iated antiparti le, with the samemass and spin but opposite harge. The photon and Z0 are identi al to theirantiparti les.1.1.3 Problems of the Standard ModelThe Standard Model provides a remarkably su essful des ription ofpresently known phenomena. Still, it seems quite lear that the SM is awork in progress and it will have to be extended to des ribe physi s at arbi-trarily high energies. Furthermore, even if one a epts the rather odd set ofgroup representations and hyper harges that it requires, the SM ontains atleast 19 parameters. Moreover, many more parameters are required if onewishes to a ommodate non-a elerator observations.The questions raised and not answered by the SM are organized intoseveral broad ategories:) Mass problem: Do parti le masses really originate from a Higgsboson?) Hierar hy problem: if so, why are these masses so far away fromthe Plan k mass mP ' 1019GeV ? Or, an the validity of the SM beextended to large masses and energy s ales?) Uni� ation problem: Can all parti le intera tions be uni�ed in asimple gauge group, and, if so, does it predi t observable new phe-nomena su h as baryon de ay and/or neutrino masses? Does it alsopredi t relations between parameters of SM su h as gauge ouplingsor fermion masses?) Flavour problem: Whi h is the origin of the three avours ea hof quarks and leptons, and what explains their weak harged urrentmixing and CP violation?

1.2. Hadron stru ture and on�nement 251.2 Hadron stru ture and on�nementTwo lasses of hadrons are found: baryons andmesons. Baryons are fermions(half-integral spin) onsisting of three quarks, while mesons are bosons (in-tegral spin) made of one quark and one antiquark. The quark on�gurationsof hadrons establish their harge and other quantum numbers. These on-stituent quarks are usually referred as \valen e" quark. From the laws ofquantum me hani s, a u tuating loud (or \sea") of virtual gluons andneutral q�q pairs is also expe ted to be present in ea h hadron. Quarks andgluons inside a hadron are also generally referred as partons.Quarks and gluons alone experien e and transmit strong for es. A ord-ing to the orresponding theory (QCD)[2℄ , these intera tions are des ribedin terms of \ olor harge". Ea h quark is supposed to have one of three pos-sible olors: \red", \blue" and \green". Antiquarks arry the orresponding\anti olor", while gluons arry two labels: one olor and one anti olor. Only olored parti les an emit or absorb gluons to onserve olor. Leptons andthe other gauge boson, being olorless, do not feel the strong intera tions.Be ause of olor, the strong for es di�er signi� antly from the ele tro-magneti ones even if both are transmitted by massless gauge bosons. For in-stan e, di�erently from photons, gluons an ouple dire tly to other gluons.The most remarkable onsequen e is the \ olor on�nement": only olorless( olor-neutral) states are allowed as physi al hadrons. Neither quarks norgluons an appear as isolated parti les, they an only exist within ( olorless) omposite hadrons.

Figure 1.1: Creation of new pair of quark-antiquarks.The e�e t of inje ting energy into a hadron is not to separate the quarks,but to stret h the olor lines of for e among them, pro ess whi h representsthe reation of a new quark-antiquark pair (see �gure 1.1) and hen e newhadrons. So, when a quark or gluon re oils energeti ally from a hard olli-sion, the broken lines of for e behind it lead to a \jet" of hadrons a ordingto a pro ess usually referred as fragmentation or hadronization.

26 1. Jet phenomenology in the Standard Model1.2.1 Parton hard s atteringAt hadron Colliders, the most prominent signature for a hard s attering pro- ess taking pla e is the produ tion of a shower of parti les with a large totaltransverse momentum, i.e., the jets. The measurement of jets allows draw-ing on lusions about the hard s attering pro ess. To do so one has to takeinto a ount the evolution of the partoni system from the hard s atteringto the observed set of hadrons. This evolution in ludes parton showering(the reation of additional partons, typi ally with de reasing transverse mo-menta), the fragmentation of oloured partons into the olourless hadrons,short lived parti le de ays and the e�e t of the underlying event as wellas the ones of multiple intera tions in a single bun h rossing (pile-up ef-fe t).1.2.2 FragmentationOne an say that there are four basi stages in the fragmentation pro- ess[5℄[6℄ (see also �gure 1.2):� Elementary hard pro ess. The proton-proton intera tion produ es a setof outgoing fundamental obje ts: quarks and gluons. Colored quarkand gluons inside hadrons an be regarded as free parti les during ahard ollision.� Parton shower. Primary partons with large \virtual life" generate ashower of partons with lower \virtual life", be ause olor for es willorganize them into olorless hadrons though the fragmentation pro- ess whi h typi ally involves the reation of many additional quark-antiquark pairs.� Hadronization. The parton shower is transformed into the observedset of hadrons. These soft non-perturbative pro esses annot be al u-lated from s rat h. A semi-empiri al des ription of this omplex pro- ess has to be adopted. That means the introdu tion of some ad-ho phenomenologi al models of hadronization: (independent fragmenta-tion model, string model, luster model ..., due to the large numberof parti les involved and its implementation in expli it Monte Carlo onstru tions to be tuned on data.� De ay of the unstable primary parti les, into stable hadrons and lep-tons a ording to lifetimes and bran hing ratios for ea h unstable par-ti le.

1.2. Hadron stru ture and on�nement 27So, after the fragmentation pro ess, the �nal alorimeter jet that hasintera ted with the dete tor, ontains mainly hadrons: tens of neutral and harged pions, a lesser extent of kaons and very few light baryons (su h asprotons and neutrons).

Figure 1.2: S heme of the di�erent stages in the fragmentation pro ess: hard s attering,parton shower, hadronization and �nally the de ay of the unstable primary parti les.1.2.3 Underlying EventsThe \Hard S attering" omponents onsist of the out oming two \jets",whi h ome from a hard 2-to-2 original parton s attering, whi h intera t atshort distan e with large momentum transfer.On the other hand, the Underlying Events[7℄[8℄[9℄[10℄ orre tions takeinto a ount all the ontributions to the jet energy not oming from theoriginal partons, i.e., everything is a ounted ex ept the hard s attering(see �gure 1.3) and onsist of:� the beam-beam remnants in ea h in oming beam parti le behindthe hard s attering, due to the fa t that the proton is not an elemen-tary parti le and it is formed by 3 quarks.� ISR and FSR intera tions between quarks and gluons, before andafter the hard s attering, a ording to the QCD laws.� Multiple intera tions : a se ond, a third... softer 2-to-2 partons attering in addition to the hard s attering.Due to the Underlying Event, the jets measured may be signi� antlymore energeti than the primary partons. In order for jet study to be mean-ingful, the additional energy deposits due to the underlying event must be

28 1. Jet phenomenology in the Standard Model

Figure 1.3: QCD Monte-Carlo model simulation of proton-proton ollision in whi h ahard 2-to-2 parton s attering with PT(hard) has o urred. The resulting event ontainsparti les that originate from the 2 ingoing partons (plus ISR and FSR) and parti les that ome from the break-up of the p-p (beam-beam remnants). Underlying Events meaneverything ex ept the 2 outgoing hard s attered jets.determined and removed from jets before omparing to QCD predi tions.So, pre ise jet measurements will require good modeling of the UnderlyingEvents.1.2.4 Parton Distribution Fun tionIn general, any inelasti s attering between protons an be des ribed as anelasti ollision between a single proton onstituent with another one. Thenon- olliding onstituents of the in oming proton-proton ontribute to theunderlying event.In this parton model pi ture, the proton-proton an be featured as a\broad band" beam of partons arrying a fra tion x of the momentum oftheir parent hadrons. Transverse momenta of parton are negle ted. PartonDistribution Fun tions (PDF), Fi(x; �2) are so introdu ed giving the prob-ability for the i-th kind of parton to have fra tional momentum between xand x + dx, � is a fa torization s ale.1.3 Jet phenomenologySin e they annot be isolated, quarks and gluons an be studied only indi-re tly. In parti ular, the study of a jet gives information about the initiatingparton as it onsists of a group of energeti parti les whi h are emitted spa-tially ollimated along the original parton dire tion.

1.3. Jet phenomenology 29From the experimental point of view, in a typi al ollider experiment,jets appear as showers of ele tromagneti and hadroni matter. They areobserved in the alorimeters as lusters of energy deposited into multipleadja ent ells. Ea h jet is so hara terized by:- a harged fra tion (mainly ��)- a neutral ele tromagneti fra tion (mainly photons from �0 ! )- a neutral hadroni fra tion (mainly KL�s and neutrons)1.3.1 Jets in proton-proton ollisionsProtons are a elerated to extremely high energies and made to ollide head-on. Ea h hard ollision onverts beam parti le energy into dozens of out-going parti les. By pla ing a dete tor around the intera tion point, one anmeasure the properties of all the parti les emerging from the ollision. Adetailed study of their properties gives a better understanding of the protonstru ture.Just after the ollision, due to the way quarks and gluons are boundinside the protons, the proton-proton intera tion produ es a set of outgoingfundamental obje ts: quarks and gluons (\parton jets"). Their s atteringat large angles results in the appearan e of two (or more) highly energeti , ollimated sprays of parti le alled \parti le jets". When they intera twith the alorimeters, they are shown as energy deposits shared amongseveral alorimeter ells of the dete tor, usually known as \ alorimeterjets", (see �gure 1.4).

Figure 1.4: The jet from the parton generation to the energy deposition in the alorime-ter.

30 1. Jet phenomenology in the Standard ModelThe jet re onstru tion algorithms are used to identify, re onstru t and hara terize the \ alorimeter jets" in order to understand more aboutthe behaviour of the \parton jets", whi h we an not \see". Then, we an employ the KT lustering or the lassi al one to know more about the alorimeter jets in a meaningful way using the energy and geometry informa-tion of ea h ell. The re onstru ted alorimeter jets generally ontain extraenergy due to additional hadroni produ ts arising from the \spe tator par-tons" (Underlying Events) and multiple intera tions, in high luminosity, it ispossible to have several ollisions between beam parti les in the same beam rosssing, i.e., pile-up events. This e�e t has to be also taken into a ountduring the re onstru tion level.So, a pre isely de�ned jet algorithm to sear h for jets, valid for bothparton- and hadron-level �nal states, is thus essential for a proper ompari-son between measurements and theoreti al predi tions. They are des ribedbre y in the hapter 7.1.4 A brief jet historyThe on ept of ollimated hadrons with high multipli ity as the result of afragmentation pro ess appeared already at the end of 60's in deep inelasti s attering pro esses. Jets were �rst observed at e+e� olliders in 1975 whenthe enter of mass energy rea hed 6-8 GeV at SPEAR[11℄ . When PEP andPETRA rea hed energies of 30-40 GeV, jets were found to be the dominantfeature of hadron produ tion.Jets in hadron ollisions were observed for the �rst time in early 80s atCERN ISR olliding proton beam with enter of mass energy of 63 GeV[12℄. The higher energy needed to see jets in hadron ollisions, an be explained onsidering that in su h intera tions the hard s attering o urs between on-stituents partons arrying only a fra tion of the hadron momentum. Onlywith the 540-630 GeV enter of mass energies of the CERN Sp�pS, jet pro-du tion be ame the most striking feature of events with large transverseenergy[13℄.1.4.1 Jet and LHC physi sFrom the LHC physi s point of view there are many reasons for being inter-ested in jets. Apart from QCD studies, jets are used in the re onstru tionof resonan es of the bosons W and Z, su h as W ! jj, Z ! b�b or the topquark su h as t ! bW, in measuring jet multipli ity and total energy Su-persymetri (SUSY) sear hes, for jet vetoes in the entral region down to

1.4. A brief jet history 31low-pT of �15 GeV, for ba kground reje tion, for jet tagging in the forwardregion et .If for example Higgs should be a SUSY Higgs, it is very likely that its�rst eviden e would appear as an ex ess in the b�b invariant mass spe trum.Measurements of the top quark whi h also are very important both for theStandard Model (SM) and for �nding new physi s onstitute the state of theart in jet spe tros opy. For SUSY sear hes, jets are extremely importantsin e the dominating produ tion is through squarks and gluinos.

32 Referen es:Referen es:[1℄ S.L. Glashow, Nu l. Phys. 22 (1961) 579;S. Weinberg, Phys. Rev. Lett. 19 (1967) 1264;A. Salam, en Elementary Parti le Theory, ed. N. Svartholm (Almquistans Wiksells, Sto kholm, 1969), p. 367;S.L. Glashow, J. Iliopoulos y L. Maiani, Phys. Rev. D2 (1970) 1285.[2℄ A. Pi h, Quantum hromodinami s, Pro . 1994 European S hool ofHigh-Energy Physi s (Sorrento, 1994), eds. N. Ellis y M.B. Gavela,CERN Report CERN 95-04 (Ginebra, 1995).[3℄ G. Arnison et al. UA1 Collaboration, Phys. Lett B122 (1983) 103;M. Banner et al. UA2 Collaboration, Phys. Lett B122 (1983) 476.[4℄ P. Anderson, Phys. Rev. 130 (1963) 439;P.W. Higgs, Phys. Lett. 12 (1964) 132;F. Englert y R. Brout, Phys. Rev. Lett. (1964) 321;P.W. Higgs, Phys. Rev. 145 (1966) 1156;T.W.B. Kibble, Phys. Rev. 155 (1967) 1554.[5℄ H. Ruiz. Ph.D Thesis.Measurement of the W mass from the ww QQQQ hannel with the ALEPH dete tor. Univ. Bar elona-IFAE. De 200[6℄ G. Latino. Ph.D Thesis, Calorimetri Measurements in CDF: A NewAlgorithm to improve the energy resolution of hadroni Jets. Univ. ofCassino, Italy. CDF/THESIS/JET/PUBLIC/5555. February 2001[7℄ R. Field and D. Stuart. Min-Bias Data: Jet Evolution and EventShapes. CDF/ANAL/MIN-BIAS/CDFR/5067 July 1, 1999.F.K. Balagadde. CDF Jet Re onstru tion Algorithms and the Underly-ing Event. Ph. D Thesis. August, 2001, Fermilab.R. Field. (Florida-CDF) The Underlying Event in Hard S attering Pro- esses. Cambridge Workshop, July 20, 2002.[8℄ D. Green (Fermilab). Minimum Bias Pileup and Missing ET at CMS.Sept 1999[9℄ Minimum bias physi s at ATLAS:http://www.shef.a .uk/physi s/resear h/hep/atlas/physi s/ lements-nuÆeld/mbias.html

Referen es: 33[10℄ A.Moraes, I.Dawson, C. Buttar. Comparison of predi tions for mini-mum bias event generator and onsequen es for ATLAS radiation ba k-ground. ATL-PHYS-2003-020 (2003)A. Moraes Minimum bias and the underlying event: ATLAS tuning,presented at the Workshop on Monte Carlo tools for the LHC - CERN;31st Jul 2003.[11℄ V. Barger, R. Phillips Collider Physi s, Adam Hilger LTD (1984).[12℄ Thom, W et al. Charged parti le multipli ity distributions in p p ol-lisions at ISR energies.MPI-PAE-EXP-EL-63.- Mn hen : Max-Plan kInst. Astrophys. Dept., 1977 - Published in: Nu l. Phys., B 129 (1977)365-389[13℄ P. Bagnaia et al., Z. Phys C 20, 117 (1983).Bibliography- F. Halzen y A. D. Martin Quark and Leptons: An Introdu tory Coursein Modern Parti le Phisi s John Wiley and Sons (1984)- B.R. Martin y G. Shaw Parti le Physi s John Wiley and Sons (1995).

34 Referen es:

Chapter 2Physi s at the LHC2.1 Introdu tionThe LHC will be the �rst a elerator to explore dire tly the TeV s ale.Any new energy range takes us deeper into the stru ture of matter, but thereare good reasons to expe t the TeV range to be parti ularly interesting, sin ethere are several indi ations that it might reveal new physi s.a) One is that we expe t it to reveal the origin of parti le masses, whi hare presumably due to the Higgs me hanism[1℄ but possibly with theaid of additional parti les beyond the single Higgs boson of the minimalStandard Model, su h as supersymmetri parti les[2℄. These seem tobe required, for example, to stabilize the energy s ale of the weakintera tions below 1 TeV[3℄.b) Another indi ation of new physi s at the TeV s ale may be providedby attempts to unify the fundamental gauge intera tions, whi h failif only Standard Model parti les are in luded in the al ulations, butwork well if supersymmetri parti les appear at the TeV s ale[4℄. ) Another hint of new physi s at the TeV s ale is provided by the as-trophysi al eviden e for dark matter, whi h is naturally explained bynew weakly-intera ting parti les weighing less than a TeV[5℄.d) Finally, the muon anomalous magneti moment[6℄ provides evanes entsuggestions of new physi s at the TeV s ale.35

36 2. Physi s at the LHC

Figure 2.1: Typi al ross se tions and event rates at the LHC, at ps=14 TeV, assuminga luminosity of 1034 m�2s�1As seen in �gure 2.1, the LHC is designed to provide high ollision ratesthat should be ample to produ e the Higgs boson and supersymmetri par-ti les if they exist in the TeV energy range.Therefore, the LHC will yield plenty of bread-and-butter StandardModelphysi s. For example, its large sample of W bosons will enable the W massto be measured with an a ura y of about 15 MeV, and its large sampleof top quarks will enable the top mass to be measured with an a ura y ofabout 1 GeV[7℄[8℄.In addition to these topi s, the LHC will be able to explore densehadroni matter in relativisti heavy-ion ollisions, where the quark-gluonplasma may be reated. The LHC will also provide a good opportunity tostudy matter-antimatter asymmetry via CP violation in the B system. Ea hof these LHC opportunities is reviewed in the following.

2.2. The Higgs boson 37Many of the most interesting aspe ts of LHC physi s tou h on the in-terfa e between parti le physi s and osmology: the Higgs boson may be aprototype for the in ation, supersymmetry may provide the dark matter inthe Universe, heavy-ion ollisions may reprodu e onditions in the �rst mi- rose onds in the life of the Universe, and CP studies may help understandthe origin of the matter in the Universe.2.2 The Higgs bosonGenerating the masses of the ele troweak ve tor bosons requires breakinggauge symmetry spontaneously, i.e., there must be a �eld X with non-zeroisospin I that has a nonzero va uum expe tation value:mW;Z 6= 0, h0jXI j0i 6= 0 (2.1)In addition, the relation:m2W = m2Z os2�W (2.2)implies that I = 1/2 is preferred. Moreover, the value I= 1/2 is also neededto give masses to the fermions of the Standard Model.The next question on erns the nature of the �eld X: is it elementary oris it omposite? The option used in the original formulation of the StandardModel was an elementary �eld h0jHj0i 6= 0[1℄. However, this option issubje t to large quantum (loop) orre tions:Æm2H;W = O�����2 (2.3)where � is a ut-o� representing the energy s ale at whi h new physi sbeyond the Standard Model appears. One of the favoured origins for this ut-o� is supersymmetry[2℄. If the loop orre tions to the Higgs and Wmasses are to be naturally small, the ut-o� � should be less than about 1TeV. In parti ular, sparti les should appear below this s ale, if they are tostabilize the ele troweak s ale[3℄.Pre ision ele troweak measurements at LEP, SLC, et ., predi ted su - essfully that the top quark would be found with mass in the range 160 to180 GeV, and it was indeed found with a mass � 175 GeV[10℄. The pre isionele troweak experiments are also sensitive to the mass of the Higgs bosonand, when ombined with the measurement of the top mass, suggest thatmH < 200 GeV[11℄. Dire t sear hes for the Higgs boson at LEP using therea tion e+e� ! Z +H saw a hint in late 2000, whose signi� an e is nowestimated to be < 2�.

38 2. Physi s at the LHCFinally, they only provide the lower limit mH > 114.4 GeV[12℄. Com-bining the dire t and indire t information the Higgs boson is peaked sharplyaround 120 GeV, suggesting that the Higgs boson may not be far away.

Figure 2.2: Signal-to-ba kground ratios for Higgs dete tion in some hannels in ATLAS.The most important Higgs de ays vary rapidly as the Higgs mass in- reases from 120 to 200 GeV, so the LHC experiments must be prepared fora range of di�erent signatures[9℄. These in lude H ! b�b pairs in asso iationwith top or bottom quarks, H ! , H ! ZZ ! 4 leptons, H !WW andH ! �� [7℄[8℄. Combining these hannels, it seems ertain that a StandardModel Higgs boson an be found at the LHC, whatever its mass, and po-tentially quite qui kly if the Higgs mass is about 150 GeV or more, as seenin �gure 2.2. Most diÆ ult to �nd would be a Higgs boson weigthing about115 GeV. The Higgs mass ould be measured with a pre ision of the orderof per mil if it weigths less than about 400 GeV, and a number of ratios ofits ouplings ould be measured at the � 10 to 20% level[7℄[8℄.

2.3. Supersymmetry 392.3 SupersymmetryAs already mentioned, the primary motivation for supersymmetry in theTeV range is the hierar hy problem[3℄:- why is mW � mP ? where mP is the Plan k mass of about 1019 GeV,the energy where gravitational for es be ome as strong as the otherintera tions, and the only known andidate for a fundamental energys ale in physi s.- Alternatively, why is GN = 1=m2P � GF = 1=m2W ?- Or why is the Newton potential inside an atom so mu h smaller thanthe Coulomb potential: GNm2=r � e2=r?.

Figure 2.3: Uni� ation of the strong and ele troweak intera tions is not possible withoutsupersymmetri parti les (left) but is possible with supersymmetri parti les (right).Supersymmetry does not by itself explain the origin of this hierar hy, butit an stabilize the hierar hy if supersymmetri parti les appear with massesbelow of about 1 TeV. Other reasons for liking a essible supersymmetryin lude the help it provides to enable the gauge ouplings to be uni�ed, asshown in �gure 2.3[4℄, its predi tion of a relatively light Higgs boson[13℄,and the fa t that it stabilizes the e�e tive Higgs potential for small Higgsmasses[14℄.There are important onstraints on supersymmetry from the non-observa-tion of supersymmetri parti les at LEP and the Tevatron, the absen e ofthe Higgs boson at LEP, the agreement of b ! s measurements with theStandard Model and measurements of the anomalous magneti moment ofthe muon[6℄.In typi al supersymmetri s enarios, the LHC dis overs many sparti lesand one or more Higgs bosons, via as ade de ays of heavy sparti les[18℄su h as that simulated in �gure 2.4. In suitable ases, the de ay hain an

40 2. Physi s at the LHC

Figure 2.4: Simulation of a \typi al" supersymetri event in the CMS dete tor.be re onstru ted and several of the sparti le masses measured. The LHCis almost \guaranteed" to dis over supersymmetry if it is relevant to thehierar hy and dark matter problems.2.4 Extra dimensionsThese were suggested originally by Kaluza and Klein in attempts tounify gravity and ele tromagnetism. More re ently, it has been realizedthat extra dimensions are required for the onsisten y of string theory, and ould help unify the strong, weak and ele tromagneti for es with gravity ifthey are mu h larger than the Plan k length[20℄. In other s enarios, extradimensions ould originate the breaking of supersymmetry[21℄, or enable areformulation of the hierar hy problem[22℄.Possible signatures of extra dimensions ould in lude a diphoton gravitonresonan e, if gravity \feels" the extra dimensions, or a dilepton Z bosonresonan e, if the ele troweak gauge intera tions feel them. In some s enarioswith extra dimensions, gravity be omes strong at the TeV s ale and bla khole formation may form and then de ay via Hawking radiation, emittingmany jets and leptons, as seen in �gure 2.5.The LHC also has great apabilities for �nding the new strongly-intera tingparti les predi ted by some omposite \te hni olour" models of ele troweaksymmetry breaking, or of dete ting omposite stru ture inside quarks. All

2.5. The quark-gluon plasma 41

Figure 2.5: An ATLAS simulation of a bla k hole produ tion event at LHC.in all, the LHC has unparalleled rea h for �nding new physi s at the TeVs ale.2.5 The quark-gluon plasmaRelativisti heavy-ion ollisions at the LHC are expe ted to reate e�e -tive temperatures of the order of 600 MeV, whi h are far above the riti altemperature of about 170 MeV for the quark-hadron phase transition thathas been found in latti e al ulations.Previous experiments at the CERN SPS and RHIC have already foundeviden e that hadroni matter hanges its nature around 170 MeV, and theLHC should be able to tell us what lies beyond the quark-hadron phasetransition, re reating onditions in the �rst mi rose ond of the Universewith \Little Bangs".As seen in �gure 2.6 , among the signatures that the dedi ated experi-ment ALICE[23℄ plans to explore are:- �� interferometry: that an determine the size and expansion rateof the little �reball,- the abundan es of strange parti les: that are expe ted to in reasenear the transition temperature[24℄,- J= produ tion: that is sensitive to Debye s reening in a plasma[25℄,- jet quen hing: that ould be due to parton energy dissipation duringpropagation through a plasma.

42 2. Physi s at the LHC

Figure 2.6: Possible signatures of the quark-gluon plasma in relativisti heavy ion ol-lision.All these signatures are to be explored in a hostile environment where thou-sands of parti les are produ ed in ea h ollision.ALICE plans to measure J= and � produ tion in both the entralregion (using e+e� de ays) and towards the forward dire tion (using �+��de ays), and to ompare the J= produ tion with open harm produ tion,to see whether there is any signi� ant suppression. ATLAS and CMS mayalso ontribute to the studies of heavy-ion ollisions: for example, CMS anstudy Z bosons produ ed with large transverse momenta, and look whetherthere is a jet on the opposite side, or whether it has been quen hed[8℄.2.6 CP violation beyond the Standard ModelSo far, measurements of quark mixing angles and CP violation in thede ays of K and B mesons agree well with the Standard Model and itsKobayashi-Maskawa me hanism, though there are some puzzles, notably inB ! �K and �� de ays. In 2007, when the LHC omes into operation, notall the angles of the CP-violating unitarity triangle will have been measureda urately. It will fall to the LHC to arry on further these tests of theStandard Model, and perhaps provide a glimpse beyond it. There have beenmany suggestions how new physi s, su h as supersymmetry, might show upin studies of CP violation in mesons ontaining b quarks[?℄.

2.6. CP violation beyond the Standard Model 43These possibilities will be explored at the LHC by a dedi ated experi-ment, LHCb[26℄, as well as by ATLAS and CMS. There are some hannelswhere the LHC will provide a signi� ant in rease in the available statisti s,su h as B ! J= K and �+�� de ays. There are other hannels whereLHCb may be able to make the �rst measurements, su h as Bs ! DsK de- ays, enabling the unitarity triangle to be over onstrained. The stakes arehigh: the CP violation present in the Standard Model is apparently unableto explain the origin of the matter in the Universe. This would require someextension of the Standard Model, whi h might be found at the LHC.

44 Referen es:Referen es:[1℄ P.W. Higgs, Phys. Rev. Lett. 13, 508 (1964)[2℄ J. Wess, B. Zumino, Phys. Lett. B 49, 52 (1974)[3℄ L. Maiani, Pro eedings of the 1979 Gif-sur-Yvette Summer S hool onParti le Physi s, 1; G. t Hooft, Re ent Developments in Gauge Theories,Pro eedings of the NATO Advan ed Study Institute, Cargese, 1979,eds. G. t Hooft et al., (Plenum Press, NY, 1980); E. Witten, Phys.Lett. B 105, 267 (1981)[4℄ J. Ellis, S. Kelley, D.V. Nanopoulos, Phys. Lett. B 260, 131 (1991); U.Amaldi, W. de Boer, H. Furstenau, Phys. Lett. B 260, 447 (1991); P.Langa ker, M.-X. Luo, Phys. Rev. D 44, 817 (1991); C. Giunti, C.W.Kim, U.W. Lee, Mod. Phys. Lett. A 6, 1745 (1991)[5℄ J. Ellis, J.S. Hagelin, D.V. Nanopoulos, K.A. Olive, M. Sredni ki, Nu l.Phys. B 238, 453 (1984)[6℄ G.W. Bennett et al., Muon g 2 Collaboration, Phys. Rev. Lett. 89,101804 (2002)[7℄ ATLAS Collaboration, http://atlas.web. ern. h/Atlas/internal/ Wel- ome.html[8℄ CMS Collaboration, http:// msinfo. ern. h/Wel ome.html/[9℄ D. Costanzo. Higgs Physi s at the Large Hadron Collider ;ATL-CONF-2001-002 (hep-ex/0105033) - Geneva CERN 24 May 2001[10℄ F. Abe et al., CDF Collaboration, Phys. Rev. D 50, 2966 (1994); S.Aba hi et al., Phys. Rev. Lett. 74, 2632 (1995)[11℄ LEP Ele troweak Working Group:http://lepewwg.web. ern. h/LEPEWWG/[12℄ LEP Higgs Working Group:http://lephiggs.web. ern. h /LEPHIGGS /www /Wel ome.html/[13℄ Y. Okada, M. Yamagu hi, T. Yanagida, Prog. Theor. Phys. 85, 1 (1991);J. Ellis, G. Ridol , F. Zwirner, Phys. Lett. B 257, 83 (1991); H.E. Haber,R. Hemp ing, Phys. Rev. Lett. 66, 1815 (1991)[14℄ J. Ellis, D.A. Ross, Phys. Lett. B 506, 331 (2001)

Referen es: 45[15℄ C.L. Bennett et al., WMAP Collaboration, Astrophys. J. Suppl. 148, 1(2003)[16℄ J. Ellis, K.A. Olive, Y. Santoso, V.C. Spanos, Phys. Lett. B 565, 176(2003)[17℄ M. Battaglia, A. De Roe k, J. Ellis, F. Gianotti, K.A. Olive, L. Pape,hep-ph/0306219[18℄ I. Hin hli, F.E. Paige, M.D. Shapiro, J. Soderqvist, W. Yao, Phys. Rev.D 55, 5520 (1997)[19℄ M. Battaglia, A. De Roe k, J. Ellis, F. Gianotti, K.A. Mat hev, K.A.Olive, L. Pape, G. Wilson, Eur. Phys. J. C 22, 535 (2001)[20℄ P. Horava, E. Witten, Nu l. Phys. B 460, 506 (1996)[21℄ I. Antoniadis, Phys. Lett. B 246, 377 (1990)[22℄ I. Antoniadis, N. Arkani-Hamed, S. Dimopoulos, Phys. Lett. B 436, 257(1998)[23℄ ALICE Collaboration, http://ali e.web. ern. h/Ali e/[24℄ J. Rafelski, B. Muller, Phys. Rev. Lett. 48, 1066 (1982)[25℄ T. Matsui, H. Satz, Phys. Lett. B 178, 416 (1986)[26℄ LHCb Collaboration, http://lh b.web. ern. h/lh b/

46 Referen es:

Chapter 3Des ription of the ATLASExperiment3.1 The proton-proton ollider: LHCTo really hallenge the SM and rea h physi s at energies 10 times higherthan the urrent limits, a new 14 TeV enter-of-mass energy proton-proton ollider is being built at CERN (European Organization for Nu lear Re-sear h) in Geneva. Large Hadron Collider (LHC) will repla e LEP and usethe same 27 km long tunnel (see �gure 3.1). LHC will be able to produ eparti les with masses from energy s ales of MeV to a few TeV.

Protons are ollided instead of signi� antly lighter leptons be ause theenergy losses due to the syn hrotron radiation are proportional to M�4,47

48 3. Des ription of the ATLAS Experimentwhere M is the mass of the a elerated parti le1. The alternative, i.e. usingprotons and antiprotons, is not feasible due to those antiprotons sour eshave not enough intensity to satisfy the high luminosity imposed. Anyway,the disadvantage of using protons is their ompositing nature whi h leadsto more ompli ated events than seen in LEP dete tors. The fa t of usingproton-proton olliders for ed to design a spe ial dipole magneti �eld ableto a elerate the same parti le in opposite dire tions.

Figure 3.1: The LEP/LHC inje tor system.To extend the rea h of new physi s to as high mass s ales as possible andto in rease the produ tion ross se tion of the pro esses of interest, it wouldbe preferable to in rease the entre of mass energy above the 14 TeV of theLHC. The magneti �eld strength required to for e the parti le beams toturn around in the ollider with �eld in reases linearly with the beam en-ergy. The highest operational magneti �eld for a�ordable super ondu tingmagnets is 8.65 T whi h together with the requirement that the LHC hasto �t inside the existing LEP tunnel gives the maximum energy of 7 TeVenergy for ea h beam.With the beam energy limited, another way to in rease the rate of eventswith interesting physi s is to in rease the luminosity. The event rate of aspe i� pro ess is given as nx = �xL (3.1)where L is the luminosity and �x the ross se tion of the pro ess. The rossse tion is, at a given entre of mass energy, a �xed number only dependenton the spe i� physi s pro ess, while the luminosity, whi h represents a geo-metri parameter, is ontrolled by the set-up of the ollider. The luminosity1The reason why one de ided to ollide protons instead of ele trons is be ause ele tronsspread too many energy by Bremsstrahlung at high energy.

3.1. The proton-proton ollider: LHC 49is for a ollider L = 14� N2ftAT (3.2)where N is the number of protons in ea h bun h, t the time between individ-ual bun hes, AT the transverse dimension of the bun hes at the intera tionpoint and f the fra tion of bun h positions a tually ontaining protons.The time between the bun hes is limited by the requirement that thereshould be no additional intera tions on ea h side of the intera tion region.For the LHC the bun h rossing time will be 25 ns orresponding to a bun hseparation of 7.5 m and f = 0.80. The transverse dimensions of the beam an, at the intera tion point, be squeezed down to 15 �m.The only remaining way to in rease the luminosity is to in rease thenumber of protons in ea h bun h. This is limited by ele tromagneti for esbetween the olliding bun hes. The maximal luminosity a hievable will be lose to 2 � 1034 m�2s�1 but to be in a stable region the nominal luminosityis �xed at 1034 m�2s�1. For the �rst years of running it is foreseen to runat low luminosity (Llow = 1033 m�2s�1) and only gradually in reasing it tothe high luminosity (Lhigh = 1034 m�2s�1).The number of observed events is given as:nobs = L�BRT" (3.3)with T the e�e tive time the ma hine is running, BR the bran hing ratio ofthe sele ted de ay and " the dete tion eÆ ien y. Taking as an example the reation of a 500 GeV Higgs parti le, for the favourable H! ZZ de ay withthe Z bosons de aying to leptons, a luminosity of 1034 m�2s�1 or higher isrequired to identify a Higgs parti le2. The �rst years with the LHC an,however, be used for physi s pro esses with higher ross se tions su h as B-physi s, studies of the top quark and sear hes for supersymmetri parti les.The high requirement on luminosity is the reason for the hoi e of aproton-proton ollider. For while a proton-antiproton ollider has the ad-vantage that both ounter-rotating beams an be kept in the same beampipe, produ ing the enormous amounts of antiprotons required for the highluminosity is not realisti and would be more expensive than the proton-proton solution with separate beam pipes. The harge asymmetry intro-du ed with a proton-proton ollider is not a serious problem for the physi sanalysis.2A standard year at the LHC is supposed to give a total running time of T = 107 s.The ross se tion is 3 pb and the bran hing ratio for the H! ZZ de ay with the Z bosonsde aying to leptons is around 0.1%. At low luminosity this gives just below 50 events ayear before taking any dete tion eÆ ien ies into a ount.

50 3. Des ription of the ATLAS ExperimentMa hine performan esEnergy per beam 7 TeVDipole �eld 8.6 TeslaCoil aperture 56 mmDistan e between apertures 194 mmDesign Luminosity 1034 m�2s�1Beam-beam parameter 0.0034Inje tion energy 450 GeVCir ulating urrent/beam 0.54 ABun h spa ing 25 nsParti les per bun h 1011Stored beam energy 334 MJNormalized transverse emittan e 3.75 �m radr.m.s. bun h length 0.075 m�-values at I. P. in ollision 0.5 mFull rossing angle 200 �radBeam lifetime 22 hLuminosity lifetime 10 hEnergy loss per turn 6.7 KeVCriti al photon energy 44.1 eVTotal radiated power per beam 3.6 kWTable 3.1: LHC performan e parameters.The events with produ tion of high mass obje ts su h as ve tor bosonsor Higgs parti les are often alled physi s events3.The di�eren e between the total ross se tion and the ross se tion of theinteresting physi s is in many ases greater than ten orders of magnitude.The absolute majority of intera tions, alled Minimum Bias events, arefusion pro esses of gluons or quarks with a small energy transfer resulting inevents with many hadrons of low momentum and nothing else. To identifythe interesting events over this huge ba kground requires to reveal some lear signatures4.3The term is misleading sin e all intera tions of ourse ontain physi s but the domi-nating QCD-jet pro esses with low energy transfer are believed to ontain little unknownphysi s and are thus regarded as ba kground without any (new) physi s information.4One of these is the identi� ation of leptons with high transverse momentum. Leptonshave a very low rate in minimum bias events but an be found in sele ted de ay modes ofmost physi s pro esses. The strong need for lepton identi� ation has driven the design ofthe LHC dete tors.

3.1. The proton-proton ollider: LHC 51An spe ially important e�e t to be taken into a ount is the so- alledPile Up: in ea h bun h rossing, i.e. every 25 ns, 23 intera tions (inaverage) will take pla e5. Ea h of the intera tions give rise to many tra ksfrom the intera tion region thus giving events with many hundred tra ks.As a onsequen e, strong design and performan e requirements are imposedin order to avoid the possible interferen e between ollision produ ts withlarge life-time in onse utive ollision intera tions. LHC dete tors must haverather fast response and high granularity to minimize the ontribution of thepile-up in a given dete tor ell.

Figure 3.2: The LHC s hemati layout.Four experiments will be installed in the LHC ollider. On one side, AT-LAS (A Thoroidal LHC ApparatuS) and CMS (Compa t Muon Solenoids)are general-purpose dete tors whi h will be fo used in the sutdy of the p-pintera tions. They are designed to study a wide range of signatures and willbe used in further tests of the SM and in new physi s sear h. On the otherside, ALICE (A Large Ion Collider Experiment) is a heavy ion experimentand �nally LHCb is a b-physi s oriented experiment, with the purpose tostudy CP-violation in B-mesons.5The number of simultaneous proton-proton inelasti intera tions taking pla e in ea hbun h rossing is given by a Poisson distribution with an average of< n >= L�ietf (3.4)At high luminosity this gives an average of 23 simultaneous inelasti intera tions in ea h rossing with an expe ted value of the inelasti ross se tion �ie = 70 mb.

52 3. Des ription of the ATLAS Experiment3.2 The ATLAS dete torThe ATLAS dete tor[1℄[2℄ is a omplex of sub-dete tor systems (see �g.3.3) designed to be able to provide information about several domains of theparti le physi s in proton-proton ollisions at the LHC. The main di�eren ewith other ollider experiments is its enormous size: the ATLAS experimentis approximately eight times as big as the L3 (LEP) experiment, whi h isuntil now the largest ollider experiment ever built. The ATLAS dete torwill be 22 m high, 44 m long, and will weigh 7000 tons. This enormous sizeis a dire t onsequen e of both the high luminosity and the large entre-of-mass energy of the LHC beams (almost ten times higher than in earlier ollider experiments).

Figure 3.3: General overview of the ATLAS dete tor.The basi design riteria of the ATLAS dete tor are[1℄:- Very good ele tromagneti alorimetry for ele tron and photon iden-ti� ation and measurement, omplemented by full- overage hadroni alorimetry for a urate jet and missing transverse-energy measure-ments;- High-pre ision muon momentum measurements, with the apability toguarantee a urate measurements at the highest luminosity using theexternal muon spe trometer alone;

3.3. Main sub-dete tors of ATLAS 53- EÆ ient tra king at high-luminosity for momentum measurement ofhigh pT leptons, ele tron and photon identi� ation, � -lepton and heavy- avour identi� ation, and full eventre onstru tion apability at lowerluminosity;- Large a eptan e in pseudorapidity with almost full azimuthal angle overage everywhere;- Triggering and measurements of parti les at low-pT thresholds, pro-viding high eÆ ien ies for most physi s pro esses at the LHC6.In addition, the LHC dete tors have to be resistant enough to work in ahigh-radiation environment, driven by the high uxes of parti les expe ted,resulting from the pp intera tions, over a period of operation of at least tenyears.3.3 Main sub-dete tors of ATLASThe ATLAS dete tor has a layout that is typi al for a ollider dete torand onsists of two types of dete tor omponents: tra king dete tors,whi h measure the position of a rossing harged parti le with minimal dis-turban e, and alorimeters, whi h measure the energy of a parti le by totalabsorption. From the ollision point outwards �rst tra king dete tors (in-ner dete tor) are pla ed, then alorimeters, divided in ele tromagneti (EM)and hadroni alorimeters, and then tra king dete tors (muon spe trometer)again.The omplete ATLAS dete tor is split into a barrel part, where dete torlayers are positioned on ylindri al surfa es around the beam axis, and twoend- ap parts, where dete tor layers are positioned in planes of onstant zperpendi ular to the beam pipe. The alorimeter onsists also of a forwardand a ba kward part, extending up to a pseudorapidity of j�j = 4.9.The most important dimensions of the ATLAS dete tor are summarisedin table 3.2. Ea h dete tor omponent is optimised to satisfy various re-quirements, e.g. resolution with respe t to position and/or energy, parti leidenti� ation, overed range, osts and material. The inner dete tor andmuon spe trometer are pla ed in a magneti �eld for the measurement of6The design of ATLAS and the other LHC dete tors is driven by the need of sele tingthe \interesting" events from the �109 intera tions per se ond that will take pla e atdesign luminosity. Besides being able to trigger on su h events, the dete tor must measurethe relevant kinemati quantities with suÆ ient pre ision to a hieve the required reje tionpower against the expe ted ba kgrounds.

54 3. Des ription of the ATLAS Experiment

Table 3.2: Dimensions of the ATLAS sub-dete tors.the momentum of harged parti les. This magneti �eld auses a bendingof the tra k, with a radius of urvature dependent on the momentum value.This general-purpose dete tor, whi h was designed optimizing the physi sgoals[15℄ and trying to redu e the ost, uses a large air- ore toroid systemas a muon spe trometer, the liquid-argon te hnique for the ele tromagneti and end- ap hadroni alorimeters, iron-s intillator hadroni alorimetry inthe barrel, a super ondu ting solenoid as the tra ker magnet, semi ondu -tors in the inner-tra king system and straw-tubes in the outer tra ker part.A few aspe ts of the sub-dete tors systems are listed below.3.3.1 Parti le identi� ationTo identify and study the parti les an arrangement of dete tors will be builtaround the points where protons are brought into ollision. New parti lesare either identi�ed by their de ay produ ts or on the ontrary by the la kof de ay produ ts7.The purpose of an experimental setup at the Large Hadron Collider istherefore to identify all parti les oming out of a ollisionand measure theirenergy. From this information we try to re onstru t the underlying ollisionpro es. Two types of dete tors are used in LHC experiments for the parti leidenti� ation: tra king dete tors and alorimeters. Ea h parti le gives adi�erent signature in the ATLAS dete tor, making parti le identi� ationpossible. The signatures for the most important parti les are summarisedin �gure 3.4.7For instan e, an intermediate mass Higgs boson an de ay into two photons with adistin t invariant mass equal to the mass of the Higgs boso A supersymmetri parti le willde ay in dete table and undete table parti lesso a ollision an be identi�ed, but part ofthe ollision energy seems to have disappeared.

3.3. Main sub-dete tors of ATLAS 55

Figure 3.4: Signature of some highly energeti parti les in the inner dete tor (innertra ker), alorimeter and muon spe trometer (outer tra ker).An ele tron gives a signal in the inner dete tor, losing a small partof its energy, and in the alorimeter (mainly in the ele tromagneti (EM) alorimeter), depositing its remaining energy part. Photons give also a signalin the alorimeter, but not in the inner dete tor (unless a photon onvertsinto an ele tron-positron pair). Muons traverse the alorimeter and give asignal in the inner dete tor and muon spe trometer and eventually a smallsignal in the alorimeter. Charged hadrons give a signal in the inner dete torand the alorimeters. Hadrons shower8 deeper into the alorimeter thanele trons and photons and give a signal in both alorimeters.Jets (not shown in �gure 3.4) are a ombination of hadroni and leptoni parti les. The signature of a jet is a number of tra ks and alorimeter lusters lose to ea h other, and ause a signal in the inner dete tor and alorimeters and eventually also in the muon spe trometer9. Neutrinos annot be dete ted and leave only a signal of missing transverse energy.8A shower is de�ned as the as ade produ tion of ele trons, photons and hadrons(for hadron showers) initiated by a highly energeti parti le that was in ident on a thi kabsorber.9Jets are however mostly onsidered as a sour e of problemati ba kground levels.When the most od the jet energy is arried by one parti le, the jet may be misidenti-�ed as a sinble parti le. Most problemati in this sense are single pions that reate anele tromagneti shower be ause they leave photon or ele tron signatures.

56 3. Des ription of the ATLAS Experiment3.3.2 Useful CoordinatesThe standard oordinate system used involves the pseudorapidity � andazimuthal angle '. The azimuthal angle is that in the plane perpendi ular(see �g. 3.5) to the beam pipe (whi h de�nes the Cartesian z-axis), thus:tan' = yx (3.5)The pseudorapidity is de�ned by the relation (see �g. 3.5)� = �ln�tan��2�� (3.6)where � represents the angle measured from the beam pipe.The pseudorapidity is an interesting oordinate in proton-proton ollid-ers be ause it expands the small angle � and makes easy the al ulations inthe analysis. Besides, this oordinate omes from the rapidity:y = ln� (E+pz)(E�pz)�2 (3.7)The rapidity is invariant under longitudinal boost. So, if we onsider themass of the jet as equal to zero, we an assume that the pseudorapidity isalso invariant under longitudinal boost10.Figure 3.5: De�nition of azimuthal angle ' (left) and the pseudorapidity � oordinate.

10The pseudo-rapidity be omes equal to the rapidity in the limit E� m 2 (i.e. masslessapproximation).

3.4. Inner Dete tor 573.4 Inner Dete torThe Inner Dete tor (ID) [8℄[9℄ is ontained within a ylinder of length 7 mand a radius of 1.5 m (see �g. 3.6) sorrounds the beam pipe, in a solenoidalmagneti �eld of 2 T. The dete tor provides the tra king overage in theregion j�j <2.5 and it is ontained in the entral solenoid in order to enablethe momentum measurement of harged parti les.The Inner Dete tor onsists of two high-resolution position dete tors atinner radii and of ontinuous tra king elements in the outer part. The threesub-systems are:- the Pixel dete tor on the inside;- a sili on-strip dete tor alled the Semi-Condu tor Tra ker (SCT);- a straw tube tra ker on the outside alled Transition-Radiation Tra ker(TRT).

Figure 3.6: Three dimensional ut-away view of the ATLAS Inner Dete tor.The tasks of the inner dete tor are the pre ise momentum, impa t pa-rameter and vertex position measurement as well as the good pattern re og-nition. Using additional information from the alorimeter and muon sys-tems, the Inner Dete tor also ontributes to ele tron, photon, and muonidenti� ation, and supplies extra signatures for short-lived parti le de ayverti es.Important physi s onsiderations for the Inner Dete tor design are:- Ex ellent momentum and impa t parameter resolution for tra ks withpT > 0:5 GeV up to very high momentum.- Tra king overage over the range j�j < 2:5.- High eÆ ien y keeping high noise reje tion.- Charge identi� ation of high pT tra ks.

58 3. Des ription of the ATLAS Experiment- Tagging of b-jets originated from b-quarks.- Re onstru tion of soft ele trons and se ondary verti es from b and �de ays.- Prymary vertex identi� ation.- Ele tron identi� ation apability.- Identi� ation of a high pT tra k to redu e the level 1 ele tromagneti luster trigger rate from jet events.The momentum and vertex resolution requirements from physi s allfor high-pre ision measurements to be made with �ne granularity dete tors,given the very large tra k density expe ted at the LHC. The highest gran-ularity around the vertex region is provided by semi- ondu tor pixel andstrip dete tors, the later employed in the Semi ondu tor Tra ker (SCT).The basi prin iple of the semi ondu tor dete tors is that the passage ofionizing radiation reates ele tron-hole pairs in the semi ondu tor whi hare olle ted by an ele tri al �eld. The di�eren e between strips and pixelsis mainly geometry, pixels being losely spa ed pads apable of good twodimensional re onstru tion while strips give a better spatial resolution inone oordinate than the other.The pixel layers are segmented in R� and z, while SCT dete tor usessmall angle (40 mrad) stereo strips to measure both oordinates, with oneset of strips in ea h layer measuring � (see table 3.3) . The pixel dete tor ismu h more radiation tolerant than the sili on strip tra ker.

Table 3.3: The main parameters of the Inner Dete tor. In the end- ap SCT, the reso-lutions vary, only a typi al number is indi ated.To improve momentum re onstru tion, pattern re ognition and ele tronidenti� ation a straw-tube Transition Radiation Tra ker (TRT) is pla ed 11,11Transition Radiation Tra ker (TRT) provides 36 points per tra k (> 7 points/tra kfor e- identi� ation).

3.5. Magnet System 59whi h whi h an be operated at the high LHC-rates due to the small radiusof 4 mm with a 30 mmmmm wire. The non- ammable gas used onsistsof 70% Xe, 27% CO2 a 3% O2 and is operated as a proportional ounter.The layers are interleaved with a radiator material. This radiator materialprodu es transition-radiation photons, with a probability proportional tothe Lorentz boost ( � E=m) of the traversing parti le. The xenon in thetubes is sensitive to these photons. This allows ele tron identi� ation, sin eele trons have high boost.The Inner-Dete tor resolution an be parameterised for the barrel regionas: �(pT )pT = 0:036%pT � 1:30%psin � (pT in GeV) (3.8)and for the forward region as:�(pT )pT = 0:045%pT 1:30%psin � (pT in GeV) (3.9)The layout provides full tra king overage over j�j � 2:5, in ludingimpa t parameter measurements and vertexing for heavy- avour and � -tagging. The se ondary vertex measurement performan e is enhan ed bythe innermost layer of pixels, at a radius of about 4 m, as lose as is pra -ti al to the beam pipe. The lifetime of su h a dete tor will be limited byradiation damage, and may need repla ement after a few years, the exa ttime depending on the luminosity pro�le.3.5 Magnet SystemAn appropriate magneti �eld distribution is required for measuring thetransverse momenta of the produ ed harged parti les. The ATLAS mag-net system of the ATLAS dete tor onsist of the super ondu ting entralsolenoid and of the system of super ondu ting air- ore toroids (8 oils of thebarrel toroid and the 2 x 8 oils of the end- ap toroids). A 3D view of thebare windings of the ATLAS magnet system is given in �gure 3.7.The entral solenoid spanning over 5.3 m along the beam axis generatesa magneti �eld of 2 T in the inner dete tor avity. The solenoid oil is keptas thin as possible (�10 m) in order to minimize the dead material amountin front of the ele tromagneti alorimeter.The super ondu ting air- ore toroids represent a omplex system, whi hgenerates the magneti �eld in the outermost dete tor: the muon spe trom-eter. The toroid system onsist of 8 barrel and 2 x 8 end- ap oils (eight

60 3. Des ription of the ATLAS Experiment

Figure 3.7: Three-dimensional view of the bare windings of the ATLAS magnet system:the entral solenoid, the air- ore barrel toroid and two air- ore end- ap toroids.in ea h end- ap). Ea h barrel toroid oil is housed in its own ryostat andthe designed peak �eld amount to 3.9 T. The end- ap oils are ontained inone large ryostat (in ea h end- ap) and are designed for the peak �eld of4.1 T. The bending power is slightly lower in the transition region betweenthe two magnet overlap (1.3< j�j <1.6). The air- ore option minimizes thedead material amount, whi h restri ts the muon multiple s attering and thusenhan es the spe trometer resolution.3.6 CalorimetersThe ATLAS alorimeter system are pla ed between the inner dete torand the muon spe trometer. A general view of the ATLAS alorimetry ould be seen in the �gure 3.8 with its di�erent omponents: EM A or-dion alorimeters, Hadroni Tile alorimeters, Hadroni LAr End Cap andForward LAr alorimeters. The main task of the alorimeters[15℄ at hadron olliders onsist of:� The a urate measurement of the energy of either individual parti les(ele trons, photons and hadrons).� The measurement of the energy and dire tion of jets.� The information on the missing transversal energy ET (i.e. the en-ergy of parti les es aping the dete tion -e.g. neutrinos - in the planeperpendi ular to the beam axis).� parti le identi� ation (for instan e, separation of ele trons and pho-tons from hadrons and jets, and of � hadroni de ays from jets).

3.6. Calorimeters 61� the event sele tion at the trigger level (ATLAS alorimeters ontributeto it due to their fast response).

Figure 3.8: View of the ATLAS alorimetry.At the LHC, these general tasks will be more diÆ ult to be a hievedbe ause of the high luminosity and large enter-of-mass energy, whi h requiregood performan e over an unpre edent energy range, extending from a fewGeV up to the TeV s ale. Fast dete tor response and �ne granularity are alsorequired to minimize the impa t of the pile-up on the physi s performan e.Their radiation resistan e must allow operation for more than ten years ofdata-taken at high luminosity.The prin iple of alorimetry is the energy measurement of an in identparti le by total absorption, where a fra tion of the total energy is trans-formed into a measurable quantity ( harge or light). An in ident ele tronor photon gives rise to an ele tromagneti shower that an be des ribed bya as ade of e and g produ tion (mainly bremsstrahlung and the reation ofe+e� pairs). An in ident hadron gives rise to a hadroni shower onsistingof an ele tromagneti omponent (e, ), a hadroni omponent of stronglyintera ting parti les and a omponent of low energeti parti les that are not

62 3. Des ription of the ATLAS Experimentdete ted. Parti le identi� ation is performed using both the ele tromag-neti and hadroni alorimeters on the basis of transversal and longitudinalshower pro�les. An ele tromagneti shower gives mainly a signal in the�rst part of the alorimeter (ele tromagneti alorimeter). A hadron givesa signal in both parts of the alorimeter.Be ause of the spe ial interest in photons and ele trons the resolutionof the ele tromagneti alorimeter is of prime importan e. The hadron alorimeters are less a urate, whi h is also partly due to the nature ofhadroni showers in the alorimeter. The design goal energy resolution forphotons and ele trons is:�EE = 0:1pE � 0:001 � 0:3pE (E in GeV) (3.10)The design goal energy resolution for hadrons is:�EE = 0:5pE � 0:003 (E in GeV) (3.11)To make position measurements possible, the alorimeters are segmented in ells. The ele tromagneti alorimeter uses a segmentation varying between��x�� = 0.003 x 0.1 and ��x�� = 0.025 x 0.025. The hadroni alorimeteruses a oarser segmentation of ��x�� = 0.1 x 0.1 (see table 3.4).The ele tromagneti alorimeter uses Liquid Argon (LAr) as a tive medium,whereas in the hadroni alorimeter di�erent te hnologies are employed de-pending mainly on the environmental onstraints, like radiation dose. Thethi kness of the ele tromagneti alorimeter is about 25-30 radiation lengths.The thi kness of the hadroni alorimeter is about 10 absorption lengths.System j�j overage Granularity(�� ���)0.03 x 0.1 (s1)EM barrel j�j � 1:475 0.025 x 0.025 (s2)0.05 x 0.025 (s3)Presampler j�j � 1:8 0.025 x 0.1Hadroni barrel j�j � 1:8 0.1 x 0.1Hadroni end ap 1:5 � j�j � 2:5 0.1 x 0.12:5 � j�j � 3:2 0.2 x 0.2Forward Calo 3:2 � j�j � 4:9 -0.1 x 0.2Table 3.4: The ATLAS alorimeter system.

3.6. Calorimeters 633.6.1 Ele tromagneti CalorimeterThe Ele tromagneti (EM) alorimeter[5℄ involves one barrel and two end- ap liquid argon (LAr) alorimeters with a ordion geometry (see �g. 3.9).It is expe ted to a hieve an ex ellent energy-resolution, as it is shown in the�gure 3.10 for ele trons dara in testbeam and simulation results.Ele tromagneti Calorimeter performan eOne of the goals of the EM alorimeters[1℄[2℄ is the very pre ise energyre onstru tion of ele trons and photons, whi h is important e.g. for theHiggs mass determination. To that goal is required a energy resolution :�EE = 10%pE � 1% (E in GeV) (3.12)EM alorimeters also provide a powerful tool for parti le identi� ationdue to their high granularity:� ele tron/photon identi� ation and reje tion of the jet ba kground (forinstan e, the jet reje tion at ET > 20GeV is expe ted to be roughly5000, whi h enables to eliminate the QCD ba kground in H ! ).� identi� ation of � hadroni de ays (important e.g. in the sear h forMSSM Higgs boson de aying to �� pair)

Figure 3.9: Sket h of the a ordion stru ture of the ele tromagneti alorimeter.

64 3. Des ription of the ATLAS ExperimentBarrel CalorimeterThis sampling alorimeter uses lead as the absorber and liquid argon asthe a tive medium, it is ontained together with the entral solenoid in thebarrel ryostat. The absorber thi kness is optimized in terms of the energyresolution The signal is read-out by kapton ele trodes and the total numberof hannel is about 200.000. The alorimeter stru ture is of the a ordionshape, whi h ensures the full azimuthal symmetry without any ra ks in '.The alorimeter is subdivided into 3 longitudinal samplings with a to-tal thi kness of 24 radiation lengths (X0) at � = 0. The �rst longitudi-nal sampling (6X0) alled preshower is used for the parti le identi� ation( =�0; e=� separation, et ). The middle se tion is segmented into towers ofsize ��x�' =0.025x0.025 (�4x4 m2 at �= 0), provinding a pre ise positionmeasurement in �.The barrel alorimeter is pre eded by a presampler, whi h is representedby one thin (1 m) LAr a tive layer. It is used to orre t for the energy lostin the inner dete tor, ryostat and oil.End-Cap CalorimeterThe basi stru ture of the EM end- ap alorimeter is the same as in thebarrel part. It overs the region 1.375 < j�j < 3.2 and is longitudinally seg-mented in 2 o 3 samplings (depending on the pseudorapidity). A presampleris installed in front of this alorimeter as well.Ea h EM end- ap alorimeter is ontained together with the hadroni end- ap and forward alorimeters in the respe tive end- ap ryostat.

Figure 3.10: Left: The ele tron energyresolution of the ele tromagneti alorimetersystem at two di�erent in lination angles, as measured in a testbeam. Right: The ele tronenergyresolution as fun tion of pseudorapidity for di�erent ele tron ET , from simulation.

3.6. Calorimeters 653.6.2 Hadroni CalorimetersThree di�erent hadroni alorimeters overing di�erent pseudorapidityzones are involved in the ATLAS alorimeter system: Tile Calorimeter,Hadroni End-Cap Calorimeter and Forward Calorimeter.Hadroni Calorimeter performan eThe performan e of the di�erent sub-dete tors whi h form the Hadroni alorimeter[2℄[6℄ of ATLAS meet the main physi s requirements:� The target jet energy resolution:�EE = 50%pE � 3% for j�j < 3 (3.13)�ETE = 100%pET � 10% for 3 < j�j < 5 (3.14)Su h resolution will enable the jet-jet mass re onstru tion as well asthe missing ET measurement with the suÆ ient a ura y required forphysi al pro esses of interest.� The linearity of the jet energy measurement within 2% up to ET � 4TeV. This is espe ially important for the quark ompositeness study.� The total EM+hadroni alorimeter thi kness of approximately 10 �int(intera tion length) at � = 0 is required for the shower ontainment.This a�e ts both the energy resolution and the ba kground in themuon hambers.Tile CalorimeterThe Tile alorimeter[6℄, usually alled \TileCal", is a hadroni sampling alorimeter made of iron and s intillating tiles, whi h are read out by wave-length shifting (WLS) �bres. The Tile al ylindri al stru ture, with an innerand outer radii of 2280 and 4230 mm respe tively, onsists of:- a entral barrel (length 5640 mm along the beam axis) surroundingthe barrel EM alorimeter- two extended barrels (ea h being 2650 mm long) surrounding the end- ap regions, (a module during onstru tion is shown in �g. 3.11).All parts together over the region j�j < 1.7.

66 3. Des ription of the ATLAS Experiment

Figure 3.11: Left: A Tile Calorimeter extended barrel module onstru ted in Bar elona.Right: S hema of a module of TileCal with its di�erent omponents: s intillator (blue),WLS �bers (green) and photomultiplier (red).In the radial dire tion, the alorimeter is segmented into 3 samplings,being approximately 1.5�int, 4.1�int and 1.8�int thi k at � = 0. The totalthi kness, summing the 1.2 �int in the ele tromagneti alorimeter and theextra material in the support stru ture, rea hes 11�int. The tiles and ab-sorber plates are oriented perpendi ular to the beam axis and staggered indepth.Ea h of the barrels is subdivided in 64 modules in the azimuthal plane(whi h orresponds to �' = 0.1 � 2�/64). In the �-' plane, the granularity�� x �' = 0.1 x 0.1 (0.2 x 0.1 in the last third sampling) has been foundadequate for the studied pro esses.Ea h module is sta ked with a large number of basi blo ks alled pe-riods. A period onsists of four layers: the large trapezoidal iron plates(so- alled master plates) represent the �rst and third layer, while in theeven layers sampler steel spa er plates alternate with the s intillating tiles(see �g. 3.12). The thi knes of one period is 17 mm (3 mm s intillator tile+ 14 mm absorber).Ea h tile is read out on both sides by wavelength shifting (WLS) �bresand two separate photon-multiplier (PM) tubes, as it is shown in �g. 3.11.Readout ells are formed by joining groups of tiles. The groups are hosen sothat ells are pseudo-proje tive to the intera tion point. The total numberod hannel is about 10 000. PMs and ele troni s are housed jointly insidethe rigid U-shaped girder (lo ated in the outermost part of the TileCalmodules).

3.6. Calorimeters 67

Figure 3.12: S hemati representation of the TileCal geometriy. a) represents thes heme as it is onstru ted: alternating masters ans spa ers, b) gives the same geometrybut from a di�erent point of view, ) shows the path traversed by a tra k in iron ands intillator and d) represents an assembled tile alorimeter period.The read-out ele troni s is required to pro ess more than 104 PM re-sponses ea h 25 ns. The Tile alorimeter ontributes to the LVL1 inputwith the trigger tower energy sums, i.e., the sum of the energy depositedin all radial alorimeter samplings within the one 0.1 x 0.1 in �� x �'(so- alled trigger tower)12, and with the signal from ells in the last radialsampling.Hadroni End-Cap CalorimeterThe hadroni end- ap alorimeters over the region 1.5 < j�j < 3.2 andshare ommon ryostat vessel with the respe tive EM end- ap and forward alorimeters. The alorimeter is made of opper-plate absorbers (radiationresistant) interla ed with LAr a tive medium gaps; the signal is read-outwith the ele trostati transformers. Ea h of the two end- ap parts onsistsof two on entri wheels, whi h di�er in the absorber thi kness.Forward CalorimeterThe forward alorimeter (FCAL) onsists of two identi al parts, ea h ofthem integrated into the respe tive ATLAS end- ap. As it will work inhigh radiation and energy ux environment (it spans over the region 3.1< j�j < 4.9), it must be enough radiation resistant. Therefore it is madeas a sandwi h of opper (�rst sampling) and tungsten (se ond and thirdsamplings) absorbers with the LAr a ting as the a tive medium.12In the �rst and se ond samplings, the low-gain signals from both photomultipliersreading the same ell are summed up. As for the last sampling, the ells span over �' =2, their signals are divided into two neighbouring towers (ea h of the two PMs ontributesto di�erent tower). Thus, the trigger tower sum onsists of �ve PM signals.

68 3. Des ription of the ATLAS Experiment3.7 Muon Spe trometerThe pre ise muon pT determination is important for a large number of pro- esses studied within the ATLAS experiment, e.g., some possible Higgs de- ays. These data are provided by the outermost part of the ATLAS dete tor:muon spe trometer[7℄, where the muon tra k de e tion in the toroidal mag-neti �eld (mostly perpendi ular to the muon momentum) is measured.

Figure 3.13: Left: Transverse view of the ATLAS muon spe trometer. Right: 3D viewof the muon spe trometer instrumentation indi ating the di�erent hambers.The spe trometer onsist of three on entri ylindri al layers equippedwith two types of high-pre ision tra king hambers:- Monitored Drift Tubes (MDT) at lower pseudorapidities- Cathode Strip Chambers (CSCs) at higher j�j and lose to theintera tion point.The barrel hambers form three ylinders on entri with the beam axis, atradii of about 5, 7.5, and 10 m (Figure 3.13). They over the pseudorapidityrange j�j < 1. The end- ap hambers over the range 1 < j�j < 2.7 andare arranged in four disks at distan es of 7, 10, 14, and 21-23 m from theintera tion point, on entri with the beam axis.The muon spe trometer is designed for a momentum resolution:�(pT )pT < 1x10�4p=GeV (for pT > 300 GeV) (3.15)at smaller momenta, the resolution is limited to a few per ent by multi-ple s attering in the magnet and dete tor stru tures, and by energy loss

3.8. Trigger Chambers 69 u tuations in the alorimeters. To a hieve this resolution by a three-pointmeasurement, with the size and bending power of the ATLAS toroids, ea hpoint must be measured with an a ura y better than 50 mm. This setsthe s ale for the requirements on the intrinsi resolution, the me hani alpre ision, and the survey a ura y of the muon hambers.The pre ision measurement of the muon tra ks is made in the r-z pro-je tion, in a dire tion parallel to the bending dire tion of the magneti �eld;the axial oordinate (z) is measured in the barrel and the radial oordinate(r) in the transition and end- ap regions. MDT hambers are used for thispurpose over most of the solid angle overed by the spe trometer. They pro-vide for a single-wire resolution13 of � 80 �m , and for robust and reliableoperation due to the me hani al isolation of neighboured wires.In the �rst station in the end- ap region and for pseudorapidities j�j >2, CSCs hambers are used to provide a �ner granularity whi h is requiredto ope with the demanding rate and ba kground onditions in this regionof the apparatus. The CSC are multiwire proportional hambers with ath-ode strip readout and with a symmetri ell in whi h the anode- athodespa ing is equal to the anode wire pith. The pre ision oordinate is ob-tained by measuring the harge indu ed on the segmented athode by theavalan he formed on the anode wire. Resolutions better than 60�m havebeen measured in several prototypes.3.8 Trigger ChambersThe Trigger Chambers for the ATLAS muon spe trometer serve a threefoldpurpose:- Bun h rossing identi� ation, requirin a time resolution better thanthe LHC bun h spa ing of 25 ns.- A trigger with a well de�ned pT ut-o� in moderate magneti �elds,requiring a granularity of the order of 1 m.- Measurement of the se ond oordinate in a dire tion orthogonal to theone measured in the pre ision hambers with a typi al resolution of5-10 mm.13To improve the resolution the MDT hambers are onstru ted from 2x4 monolay-ers of drift tubes for the inner and 2x3 monolayers for the middle and outer stations.The onstru tion of proptypes has demostrated that they an be built with the requiredme hani al a ura y of 30�m.

70 3. Des ription of the ATLAS ExperimentThe proposed system employs two di�erent types of dete tors, ResistivePlate Chambers (RPC) in the barrel (j�j � 1.4) and Thin Gap Cham-bers (TGC) in the end ap region. The trigger hambers over a totalarea of abaout 3650 m2 in the barrel and 2900 m2 in the end ap region,ea h hamber ontaining at least two dete tor layers. The total number of hannel is about 350.000 for the barrel and 440.000 in the end aps.The RPC is a gaseous dete tor providing a typi al spa e-time resolutionof 1 m x 1ns with digital readout. The basi RPC unit is a narrow gasgap formed by two parallel resistive bakelite plates, separated by insulatingspa ers.The TGC hambers are similar in design to multi-wire proportional hambers, with the di�eren e that the anode wire pith is larger than the athode-anode distan e. Signals from the anode wires, arranged parallelto the MDT wires, provide the trigger information together with readoutstrips arranged orthogonal to the wires. These readout strips are also usedto measure the se ond oordinate.To from a trigger signal, several anode wires are grouped and fed to a ommon readout hannel.3.9 Trigger and Data-a quisition systemThe high design luminosity of 1034/ m2s of the LHC will lead to over 20intera tions per bun h rossing. Thus, ea h se ond lose to 109 intera tionso ur. Most of these intera tions are minimum bias events that have alimited interest. The dete tor onsist of very omplex system produ inglarge ammount of data, e.g. the SCT and PIXEL dete tors read out �6 million and � 100 million hannels respe tively. Current data storagete hnology limits the ammount of data that an be stored to the order of100 MB/s. The bun h rossing rate is 40 MHz but it will only be possible towrite events to tape at a rate below 100 Hz. This means that within se ondsthe data ow from the dete tor has to be redu ed by a fa tor 400.000 whi his only possible using several trigger levels.The trigger system is design to bridge this gap, maintaining nearly allinteresting physi s events, while eÆ iently reje ting the minimum bias ba k-ground. The system is to be apable of a fast re onstru tion of (part of) thedata from the di�erent di�erent dete tors to look for signatures of interestingphysi s.The ATLAS trigger[11℄ and data-a quisition (DAQ)[12℄ system is basedon three levels of online event sele tion. Ea h trigger level re�nes the de-

3.9. Trigger and Data-a quisition system 71 isions made at the previous one and, where ne essary, applies additionalsele tion riteria. At the �rst level only general features and a few dete torsare read out while the level-3 trigger provides full s ale physi s analysis.

Figure 3.14: Regions of interest (ROI).The �rst trigger level[10℄, alled (LVL1), identi�es the regions in thedete tor where interesting features were found, the so- alled Region of In-terest, ROIs, (see �g.3.14). This level, due to the high frequen y, dealsonly with the fast muon trigger hambers (high-pT muon measurement) and oarse-granularity alorimeter data (sear h for high-pT ele trons, photons,jets and large missing ET ) as it is shown in the table 3.5. This triggerlevel is designed to take a de ision within 2.0 �s and redu es the rate on itsoutput to 75 kHz (upgradeable to 100 kHz). The muon system has spe ial

Table 3.5: Some Simulated Trigger Rates at LVL1 at high luminosity.trigger hambers with a short drift-time but limited resolution. The datafrom the alorimeters are read out with a oarse (�� x �') = (0.1 x 0.1)resolution. The sub-dete tors are treated individually and look for muonswith pT > 20 GeV, isolated ele tromagneti lusters with ET > 30 GeV,

72 3. Des ription of the ATLAS Experimenthigh energy hadroni jets or large ETmiss. An isolated luster means that aregion around the entral luster ontains low ET .This trigger level is designed to take a de ision within 2.0 �s and redu esthe rate on its output to 75 kHz (upgradeable to 100 kHz). Events a eptedby the LVL1 are read-out from the dete tor ele troni s via the so- alledRead-Out Drivers (ROD) into Read-Out Bu�ers (ROB). Here the data arestored until the event is either reje ted or a epted by the next trigger level(LVL2)[12℄. In the latter ase, the data are transferred to the last triggerlevel, so- alled Event Filter[13℄, (see �g 3.15).

CALO MUON TRACKING

Regions of Interest(RoIs)

ROLs

SFOs

SFIs

Event Building

Front−endpipelinememories

LEVEL 1TRIGGER

LEVEL 2TRIGGER

EVENT FILTER

RODs

ROBs

Processorfarms

RoIB

DFM

ROD

ROL

SFI

Offline data recording

DFM

ROB

RoI

RoIB

SFO

− RoI Builder

− Region of Interest

− Sub−Farm Input

− Sub−Farm Output

− DataFlow Manager

− ReadOut buffers

− ReadOut drivers

− ReadOut LinkFigure 3.15: Three levels of the ATLAS trigger.The level-2 trigger[12℄ analyses data a ross di�erent dete tors and hasa ess to data with full pre ision information from the inner tra king de-te tor, as well as from alorimeters and muon dete tors. The main task ofthe level-2 trigger is to re�ne the analysis of LVL1 inside the ROIs getting

3.10. Computing 73region-of-interest builder (ROIB). The LVL2 does not run in a �xed timeand will pro ess many events in parallel. In total, LVL2 should redu e thetrigger rate from 75 kHz to around 1 kHz (whi h is the highest a eptablerate for LVL3). The average de ision time is estimated to be � 10 ms.The level-3 trigger[13℄ or Event Filter (EF) analyses data in the fulldete tor and will do more ompli ated physi s analysis. It performs om-plete event re onstru tion within � 1 s. Events sele ted by the EF for �nalar hiving in preparation for o�ine re onstru tion and primary analysis arepassed to permanent storage via the �nal element of the data- ow system,the Sub-Farm Output (SFO). The LVL3 will redu e the data rate down to100 Hz whi h is the highest a eptable rate for permanent storage of data.The DAQ system handles the distribution of data from the ROD tomass storage and the overall monitoring and ontrol of data taking. For thisreason the system has been fa torized in two major omponents:� The Data Flow provides the fun tionality of re eiving and bu�eringdete tor data from ROD, distributing events to the High Level Triggers(HLT), that is, LVL2 and EF, and forwarding sele ted events to massstorage.� The Online Software System ontrols the overall experiment: itprovides run ontrol, on�guration of the HLT and DAQ systems andmanages data taking partitions.3.10 ComputingComputing is ru ial for the su ess of the ATLAS experiment and thee�ort to develop and maintain the software[14℄ is being enormous. It mustbe maintained for a lifetime of about 20 years of the proje t, so, the qualityrequirements on the software have to be very high. Around 1000 person peryear are required, so that ollaboration on a very distributed basis is neededto allow this so big e�ort. The �nal purpose is to analize the numbers fromthe data getting physi s results. To get it, the software is implementedfollowing the obje t-oriented paradigm and using the C++ language.The foreseen data volume of about 1 PByte (1015) per year requires newmethods for data redu tion, data sele tion, and data a ess for physi s anal-ysis. The basi goal is that every physi ist in ATLAS must have the best pos-sible a ess to the data to be analysed, irrespe tively of his or her lo ation.The proposed s heme onsist of ar hiving the \raw data" (1 PByte/year)sele ted by Event Filter system[12℄. A �rst pro essing is performed on alldata shortly (a few hours) after data taking. For this step, basi alibration

74 3. Des ription of the ATLAS Experimentand alignment onstants must be available. The purpose is to evaluate thebasi physi s quantities required by most analyses and to lassify events intophysi s hannels. The produ ed data have to be a essible at the event leveland, below that, at the re onstru tion and physi s level. ATLAS is usingan obje t-oriented data-base for this purpose.3.10.1 Computing ModelThe main requirement on the Computing Model is to enable all members ofthe ATLAS Collaboration speedy a ess to all re onstru ted data for anal-ysis during the data-taking period, and appropriate a ess to raw data fororganised monitoring, alibration and alignment a tivities. The model pre-sented here makes substantial use ofGrid Computing on epts, thereby al-lowing the same level of data a ess, and making available the same amountof omputing resour es, to all members of the ATLAS Collaboration.The Computing Model embra es the Grid paradigm and a high degree ofde entralisation and sharing of omputing resour es. However, as di�erent omputer fa ilities are better suited to di�erent roles, a degree of hierar hy,with distin t roles at ea h level, remains. This should not obs ure the fa tthat all of the roles des ribed are vital and must re eive due weight. Therequired level of omputing resour es means that o�-site fa ilities will bevital to the operation of ATLAS in a way that was not the ase for previousCERN-based experiments.The primary event pro essing o urs at CERN in a Tier-0 Fa ility.The RAW data is ar hived at CERN and opied (along with the primarypro essed data) to the Tier-1 fa ilities around the world. These fa ilitiesar hive the RAW data, provide the repro essing apa ity, provide a ess tothe various pro essed versions and allow s heduled analysis of the pro esseddata by physi s analysis groups. Derived datasets produ ed by the physi sgroups are opied to the Tier-2 fa ilities for further analysis. The Tier-2fa ilities also provide the simulation apa ity for the experiment, with thesimulated data housed at Tier-1s. In addition, Tier-2 entres will provideanalysis fa ilities and some will provide the apa ity to produ e alibrationsbased on pro essing some raw data. A CERN Analysis Fa ility provides anadditional analysis apa ity, with an important role in the data-intensive alibration and algorithmi development work.ATLAS will negotiate relationships between Tier-1s and Tier-2s and alsoamongTier-1s themselves to try to optimise the smooth running of the sys-tem in terms of data transfer, balan ed storage and network topologies.

3.10. Computing 75Tier-0 at CERNThe Tier-0 fa ility at CERN is responsible for the ar hiving and distributionof the primary RAW data re eived from the Event Filter. It provides theprompt re onstru tion of the alibration and express streams and the some-what slower �rst-pass pro essing of the primary event stream. The deriveddatasets: ESD, primary AOD and TAG sets (see appendix for des riptionof them) are distributed from the Tier-0 to the Tier-1 fa ilities des ribedbelow.The Tier-0 must provide an extremely high availability and responsetime in the ase of errors. To a ount for failures and network outages, adisk bu�er orresponding to about 5 days of data produ tion will be requiredfor the data owing into the Tier-0.A ess to the Tier-0 fa ility is granted only to people in the entralprodu tion group and those providing the �rst-pass alibration.

Figure 3.16: Tier-0 at CERN is responsible for the ar hiving and distribution of theprimary RAW data. The derived datasets: ESD, primary AOD and TAG sets are dis-tributed to Tier-1. Tier-2 will host 1/3 of the available urrent primary AOD and the fullTAG samples.Tier-1 Fa ilitiesApproximately 10 Tier-1 fa ilities are planned world-wide that will serveATLAS. They take responsibility to host and provide long-term a ess andar hiving of a subset of the RAW data (on average 1/10th ea h). They alsoundertake to provide the apa ity to perform the repro essing of the RAWdata under their uration, and to provide ATLAS-wide a ess to the derivedESD, AOD and TAG datasets, with the most up-to-date version of the dataavailable with short laten y (\on disk") and the previous version availablebut perhaps with a longer laten y (\on tape"). The Tier-1s also undertake

76 3. Des ription of the ATLAS Experimentto host a se ondary low-laten y opy of the urrent ESD, AOD and TAGsamples from another Tier-1, and the simulated data samples from Tier-2fa ilities to improve a ess and provide fail-over. All of the datasets hostedare onsidered to be for the ollaboration as a whole, and the storage andCPU pledged to be funded by the Tier-1 for that purpose.The Tier-1s must allow a ess to and provide apa ity to analyse allof the hosted samples, and will provide part of the alibration pro essing apa ity. Modest RAW data samples must be available at short laten y toallow alibration and algorithmi development. They will also host some ofthe physi s working group DPD samples.Tier-1 fa ilities are expe ted to have a high level of servi e in terms ofavailability and response time. A ess to the Tier-1 fa ilities is essentiallyrestri ted to the produ tion managers of the working groups and to the entral prod ution group for repro essing.

Figure 3.17: Tier1 Sites in the world.Tier-2 Fa ilitiesTier-2 fa ilities may take a range of signi� ant roles in ATLAS su h as pro-viding alibration onstants, simulation and analysis. This range of roleswill result in di�erent sizes of the fa ilities. Tier-2 fa ilities also provideanalysis apa ity for physi s working groups and subgroups. They typi allywill host 1/3 of the available urrent primary AOD and the full TAG sam-ples. They will also host some of the physi s group DPD samples, mostlikely in a ordan e with lo al interest. In addition, they will provide all ofthe required simulation apa ity for the experiment.

3.10. Computing 77The Tier-2s will also host modest samples of RAW and ESD data for odedevelopment. Some Tier-2s may take signi� ant role in alibration followingthe lo al dete tor interests and involvements. In prin iple, all members ofthe ATLAS virtual organisation have a ess to a given Tier-2. In pra ti e(and for operational optimisation), heightened a ess to CPU and resour esmay be given to spe i� working groups at a parti ular site.3.10.2 Relations with the LCG proje t and with Grid mid-dleware providersA omplex set of tools and distributed servi es to enable the automati distribution and pro essing of the large amounts of data that we expe t to olle t is developed and deployed by ATLAS in ooperation with the LHCComputing Grid (LCG) Proje t and with the middleware providersof the three large Grid infrastru tures (the 3 \ avours") to whi h we havea ess:- Grid3/OSG in the USA,- NorduGrid/ARC in S andinavia and a few other ountries,- LCG-2/EGEE in most of Europe, in Canada and in the Far East.The tools are designed in a exible way, in order to have the possibility toextend them to use other types grid middleware that may be deployed in thefuture on resour es that are made available to ATLAS. These tools and theservi e infrastru ture on whi h they depend, while initially developed in the ontext of entrally managed, distributed Monte Carlo produ tion exer ises,will be re-used where possible to reate systems and tools for individualuser a ess to data and ompute resour es, providing a distributed analysisenvironment for general usage by the ATLAS Collaboration.The LHC Computing Grid (LCG) Proje t was set up at the beginningof 2002 to deploy and operate Grid middleware for the LHC experimentsand help them to integrate Grid tools with their software base. Currentlythe LCG proje t has a dual role:1. it a ts as an umbrella organisation for all Grid middleware deploymentsthat are relevant for LHC experiments;2 it deploys and operates one parti ular middleware suite (LCG-2 andlater updates) in ooperation with the European Union funded EGEEmiddleware proje t.

78 3. Des ription of the ATLAS Experiment3.11 Appendix1: Event StoreThe physi s event store holds a number of su essively derived event repre-sentations, beginning with raw or simulated data and progressing throughre onstru tion into more streamlined event representations suitable for anal-ysis. Constituent omponents are des ribed in the following paragraphs.1. RAW Data: RAW data are events as output by the Event Filter (EF,the �nal stage of the HLT) for re onstru tion. The model assumesan event size of 1.6 MBMB, arriving at an output rate of 200 Hz(in luding 20 Hz of alibration trigger data). Events arrive from theEvent Filter in \bytestream" format, re e ting the format in whi hdata are delivered from the dete tor, rather than in any obje t-orientedrepresentation. Events will be transferred from the EF to the Tier-0in �les of at most 2 GB. Ea h �le will ontain events belonging to asingle run ( orresponding to a prolonged period of data-taking usingthe same trigger sele tions on the same �ll in the a elerator), but theevents in ea h �le will not be onse utive nor ordered.2. Event Summary Data (ESD): ESD refers to event data written asthe output of the re onstru tion pro ess. ESD is intermediate in sizebetween RAW and Analysis Obje t Data (see below). Its ontent isintended to make a ess to RAW data unne essary for most physi sappli ations other than for some alibration or re-re onstru tion. ESDhas an obje t-oriented representation, and is stored in POOL ROOT�les. The target size is 500 kilobytes per event3. Analysis Obje t Data (AOD): AOD is a redu ed event represen-tation, derived from ESD, suitable for analysis. It ontains physi sobje ts and other elements of analysis interest. The target size is 100kilobytes per event. It has an obje t-oriented representation, and isstored in POOL ROOT �les.4. Tag Data (TAG): TAG data are event-level metadata - thumbnailinformation about events to support eÆ ient identi� ation and sele -tion of events of interest to a given analysis. To fa ilitate queries forevent sele tion, TAG data are stored in a relational database. Theassumed average size is 1 kilobyte per event.5. Derived Physi s Data (DPD): DPD is an n-tuple-style represen-tation of event data for end-user analysis and histogramming. Thein lusion of DPD in the Computing Model is an a knowledgment ofthe ommon pra ti e by physi ists of building subsamples in a format

3.11. Appendix1: Event Store 79suitable for dire t analysis and display by means of standard analysistools (PAW, ROOT, JAS et .), though software providers ertainlyexpe t that analysis, histogramming, and display via standard toolswill be possible with AOD as input.6. Simulated Event Data (SIM): SIM refers to a range of data types,beginning with generator events (e.g., from Pythia or similar pro-grams) through simulation of intera tions with the dete tor (e.g., Geant4hits) and of dete tor response (digitization). It may also in ludepileup, the superposition of minimum bias events, or the simulationof avern ba kground. Events may be stored after any of these pro- essing stages. The storage te hnology of hoi e is POOL ROOT �les.Digitised events may alternatively be stored in bytestream format fortrigger studies or for emulation of data oming from the Event Filter.Simulated events are often somewhat larger than RAW events (ap-proximately 2 MB in size), in part be ause they usually retain MonteCarlo \truth" information.Other formats are allowed in the software and pro essing model that arenot in luded in the baseline. For example, the Derived Re onstru tion Data(DRD) is an option being onsidered for the early phase of data takingfor a subset of the data. It onsists of raw data augmented with partiallyre onstru ted obje ts to allow easy alibration and optimisation of dete tor ode. This format is only of use if the trade-o� between storage ost andCPU to derive the partial-re onstru tion is in the favour of storage. Thisin turn depends on the sample size required and the number of times thesample is passed-over by the dete tor groups

80 Referen es:Referen es:[1℄ ATLAS Collaboration: ATLAS Dete tor and Physi s Performan eTe hni al Design Report Vol 1, CERN/LHCC/99- 14 (1999)[2℄ ATLAS Collaboration: ATLAS Dete tor and Physi s Performan eTe hni al Design Report Vol 2, CERN/LHCC/99- 15 (1999)[3℄ ATLAS Collaboration:ATLAS Te hni al Proposal for a General-Purpose pp experiment at the Large Hadron Collider CERN,CERN/LHCC/94-93, (1994)[4℄ ATLAS Collaboration: ATLAS Calorimeter Performan e,CERN/LHCC/96-40 (1996).[5℄ ATLAS Collaboration: LIQUID ARGON CALORIMETER, Te hni alDesign Resport CERN/LHCC/96-41 (1996)[6℄ ATLAS Collaboration: TILE CALORIMETER, Te hni al Design Re-sport CERN/LHCC/96-42 (1996)[7℄ ATLAS Collaboration: MUON SPECTROMETER, Te hni al DesignResport CERN/LHCC/96-44 (1996)[8℄ ATLAS Collaboration: INNER DETECTOR, Te hni al Design Re-sport Vol 1, CERN/LHCC/97-16 (1997)[9℄ ATLAS Collaboration: INNER DETECTOR, Te hni al Design Re-sport Vol 2, CERN/LHCC/97-17 (1997)[10℄ ATLAS Collaboration: Level 1 Trigger Te hni al Design ResportCERN/LHCC/98-14 (1998)[11℄ ATLAS Collaboration: Trigger Performan e Status ReportCERN/LHCC/98-15 (1998)[12℄ ATLAS Collaboration: DAQ, EF,LVLE2 and DCS Te hni al ProgressReport CERN/LHCC/98-16 (1998)[13℄ ATLAS Collaboration: High-Level Trigger, Data A quisition and Con-trols TDR CERN/LHCC/2003-022 (2003)[14℄ ATLAS Collaboration: ATLAS Computing Te hni al ProposalCERN/LHCC/96-43 (1996)

Chapter 4Calorimetry4.1 Introdu tionIn this hapter, the basi on epts of ele tromagneti and hadroni alorimetry are reviewed. In on rete, the main features of ele tron andhadron showers are des ribed.The aim of alorimetry is to perform the energy measurement of an in- ident parti le by total absorption of its kineti energy. Calorimeters playan important role at high-energy ma hines be ause, in ontrast to other de-te tors su h as magneti spe trometers, their fra tional resolution improveswith energy. In parti ular, at the LHC, alorimeters will be leading dete -tors in many measurements, su h as the re onstru tion of physi s hannelsof prime interest.4.2 Basi on epts of CalorimetryThe primary goal of the alorimeters is the energy measurement of ele -trons, photons and jets, and the measurement of the missing transverseenergy. The alorimeters however also provide position and angular mea-surements and parti le identi� ation.The aim of alorimetry is to perform the energy measurement by totalabsorption of the in ident parti le whi h loses its energy through a seriesof inelasti ollisions in the alorimeter material. Eventually, most of thein ident energy is dissipated and appears in the form of heat, but as thein rease of temperature is almost negligible, this measurement is not useful.Only some fra tion of the deposited energy (usually very small) is dete tablein the form of a readable signal (i.e. s intillation light, Cherenkov light, or81

82 4. Calorimetryionization harge). Calorimeters are designed to provide a readable signalproportional to the energy deposited by the in ident parti le. The important hara teristi s are the linearity and resolution of the measured energy.Calorimetri parti le dete tor an be divided in two types:� homogeneous alorimeters, whi h ombine in only one material thepassive fun tion (i.e. the absorption of the generated shower, tryingto make it to be as ompa t as possible) and the a tive fun tion of thedete tor (i.e. the formation and olle tion of a measurable signal inthe most eÆ ient way).� sampling alorimeters, whi h are made of alternative layers of high-Z passive absorber (lead, opper, iron) and a tive medium (LAr, gas hambers, s intillators). This te hnique allows building ompa t de-te tors and optimizes the read-out method in terms of signal unifor-mity, spatial resolution, et .However, only a part of the total energy is deposited in the a tivelayers. The sampling fra tion is de�ned as the ammount of energymeasured (i.e. the energy deposited in the a tive layers in a sampling alorimeter) as a fra tion of the total energy deposited1.The latter option is used within the ATLAS experiment, in both EM andhadroni alorimeters.Calorimeters provides many attra tive apabilities and features that haveled them to be essential dete tors for high energy physi s experiments:� They are sensitive to harged as well as neutral parti les, in fa t, alorimeters represent the only devi e whi h provides information onthe kinemati s properties of neutral parti les.� The energy measurement is based on the total absorption of the in i-dent parti les through series of inelasti ollisions degradin its energy.The average number <N> of se ondary parti les is proportional to theenergy of the in ident parti le E. As the produ tion of se ondary parti- les i a statisti al pro ess, the un ertaintly in the energy measurement1In the EM alorimeter of ATLAS:- For the Barrel, maintaning a onstant sampling fra tion as a fun tion of the radius:the dE/dx sampling fra tion is 0.252 (0.282) for j�j < 0.8 (j�j >0.8)- For the end- ap, the sampling fra tion depend on the � and the alorimeter depth.Cell energies are stored after applying a alibration (ele tromagneti s ale), wi h takes intoa ount the di�erent sampling fra tion of the various alorimeter regions. For TileCal,the sampling fra tion whi h was 1/40 with Geant3, need to be updated to 1/38.

4.2. Basi on epts of Calorimetry 83is governed by statisti al u tuations in <N>. Therefore, the relativeenergy resolution of the alorimeter �E improves as 1p<N> � E�1=2,i.e., the relative a ura y of the energy measurement improves as theenergy of the in ident parti le is larger. The resolution improves within reasing energy2: �EE = apE .� The ideal alorimeter should ontain the whole shower. Therefore, thedepth of a alorimeter dete tor should mat h the s ale of the longi-tudinal shower pro�le3, whi h in rease only with the logarithm of thein ident parti le energy (see next se tions).� Calorimeters an be segmented to a very high degree, whi h allowsa pre ise measurement of the impa t point and the dire tion of thein oming parti les and helps in parti le identi� ation.� Their di�erent response to ele trons, muons, and hadrons an be ex-ploit for parti le identi� ation.� The energy information an be available on a relatively fast time s ale,depending on the nature of the a tive medium (TileCal hara teris-ti response time is about � 10 ns, LAr alorimeters an also be fastthough the dire t shaping of the harge signal). Tis feauture is essen-tial for online event sele tion (trigger de�nition).4.2.1 Ele tromagneti CalorimetryWhen the average energy of the shower parti les is higher than the riti- al energy, EC4, ele trons, positrons and photons intera t with the materialmainly via two ele tromagneti energy loss me hanisms through whi h theele tromagneti as ade grows and propagates (see �g. 4.1):- ele trons and positrons lose energy by bremsstrahlung radiation- photons do so by pair produ tionAlthough the probability of these pro esses depend on energy, at enoughhigh energy one an assume a onstant ross-se tion, be ause the energydependen e is small. It allows to onstru t simple but still useful models.2Contrary to magneti spe trometers, where resolution obeys �pp � p.3It an be ompared to magneti spe trometers, whi h have to in rease the size of theintrumented magneti �eld with p1=2 to keep a given relative momentum resolution �pp .4The riti al energy, EC , is de�ned as the value of the ele tron energy at whi h theenergy-loss rate for ionization and bremsstrahlung are equal

84 4. Calorimetry

Figure 4.1: Left:Energy loss me hanisms for ele trons and positrons. Right: Photonintera tion ross se tions vs. energy for lead. The total ross se tion is the sum of the ross se tions for the photoele tri e�e t, Compton s attering, and pair produ tion.Hen e the ele tromagneti as ades are hara terized by the material onstant alled the radiation length (X0), whi h is de�ned as the meandistan e in the absorber over whi h a high-energy ele tron redu es its energyby a fa tor 1e only due to bremsstrahlung, i.e. dE=dx = �E=X0.As a shower develops, more and more parti les are produ ed by \bremss"radiation and pair produ tion, but the average energy of these parti lesde reases as the shower ontinues. When the average energy rea hes EC , thenumber of se ondary parti les is at its maximum and further multipli ationstops. Before that point, at higher energies than EC , bremsstrahlung pro essdominates ans se ondary photons produ e more than one harged parti les(mostly e+e� pairs); later, when the se ondary parti les energy is de reasedbelow EC , ionization pro ess dominates. At lower energies, ea h photononly produ e Compton ele tron, whi h will lose its energy by ionization,without new \bremss" emission. Therefore, after the maximum de�ned byEC , the number of se ondary parti les gradually de reases and, �nally thismeans the end of the shower.The longitudinal development of the shower an be des ribed in analmost material independent way in terms of the radiation length X0. Thiss aling in X0 is rather well on�rmed by observations (see �gure 4.2). Onthe other hand, the transversal development of the as ade is dominatedby multiple s attering and ontained within�2RM , where RM is the Moliereradius5.5The Moliere radius governs the radial spread of the as ade. It is de�ned as the ratiobetween the radiation length and the riti al energy, X0/EC . So, the parameter R = 2RM

4.2. Basi on epts of Calorimetry 85

Figure 4.2: Simulation of longitudinal development of 10 GeV ele tron showers in Al,Fe and Pb.4.2.2 Experimental requirement and limitation of ele tro-magneti alorimetersAs has been exposed, energy measurement is the main goal of alorime-ters, but often position and angle measurements, are algso performed withthem, as well as parti le identi� ation.Energy measurementThe most important aspe t of energy measurement are:a) Linearity. Non-linear response ould be a major on ern in exper-iment where parti le energies over a large range6. For instan e, inATLAS, one has to measure ele trons with ET from few GeV (H !ZZ ! 4e) up to a few TeV (Z'! e+e�). The EM Calorimeter of AT-LAS is required to have a linearity of response better than 0.5% in theenergy range up to 300 GeV, to ensure optimal mass resolution. Athigher energies, this requirement an be somewhat relaxed.b) Energy resolution. It gives the un ertainty in a alorimeter mea-surement and is usually parametrized by the following quadrati sum:�EE = apE � bE � (4.1)where the di�erent term are:is the radius whi h ontain the 95% of the transversal development of the as ade.6Operating in a high magneti �eld an also be a sour e of poor linearity at low energy.

86 4. Calorimetry- a es the sto hasti term or intrinsi resolution whi h in ludes:i) The statisti al intrinsi u tuation. For homogeneous alorimeters, the intrinsi resolution is only due to the statis-ti al u tua ion of the number od dete ted primary parti les.ii) The sampling u tuation, whi h is the main ontributionto the energy resolution in the sampling alorimeters. Thesignal is detemined by the number of harged tra ks rossingthe a tive layers. The total tra ks length (T) is proportionalto the in ident parti le energy but the number of tra k seg-ments inter epted in the a tive layers is only:N / fsamp � T (4.2)where fsamp is the sampling fra tion of the alorimeter mate-rial. Then the intrinsi resolution is given by the u tuationin the number of tra k segments N:�(E)E = 1pN / 1qfsampE(GeV ) (4.3)This formula illustrates the energy dependen e of the res-olution. As a very large fra tion of the energy depositedby low-energy ele trons (MeV) in the high-Z material (ab-sorber), the energy resolution is improved by de reasing theabsorber thi kness (fsamp will be larger for smaller thi kness)7. the statisti al u tuations related with the pro essed thatprodu e and limit the signal, su h as the di�erent physi sintera tions andiii) quantum and olle ting eÆ ien ies, e.g. the number of pho-ton from s intillators or the number of photoele trons fromPMs;- b is the noise term, whi h des ribe the noise and may be dom-inant at low energy. Besides the ele troni noise, a se ond on-tribution is important in LHC alorimeters: the pile-up noise al-ready explained. This e�e t is translated in a high multipli ity of harged and neutral parti les with a low average momentum (�500 MeV/ ) whi h impa t in the alorimeter during ea h bun h rossing. The u tuations in the mean value of this pile-up on-tribute as a noise term to the energy resolution.7This s aling law is valid as long as the absorber thi kness is large enough that the rossing onse utive layers are not orrelated.

4.2. Basi on epts of Calorimetry 87- is the energy-independent term, dominant at the higherLHC energies, and it in ludes many ontributions:- Non-uniformities of the alorimeter from both the ele troni and the me hani al design.- Lateral and longitudinal leakage.- Degradation of the energy resolution due to the material infront of the alorimeter.- Signal variation with temperature or deterioration of the a -tive medium.- Dead spa eDepending on the energy range involved in an experiment, the optimiza-tion of these three parameters an be very di�erent.Position and angular measurementThe segmentation of alorimeters in strip or towers, whi h are read bydi�erent readout elements, has been used to �nd shower impa t positions.In pra ti e, alorimeters an rea h position resolutions at the level of afew mmpE . The energy dependen e omes dire tly from the energy resolutionin ea h of the ells.The need for an angular measurement provided by the ele tromag-neti alorimeter has been stressed re ently in the ontext of the h ! hannel produ ed in pp ollision at the LHC8. Su h a measurement requiresat least two segments in depth.Parti le identi� ationRough parti le identi� ation is performed in the ele tromagneti alorime-ters using as a basis the lateral and longitudinal shower por�les and ompar-ing them to those expe ted from ele tromagneti versus hadroni showers.The typi al pattern of energy deposition of muons also allows to identifythem in most ases. The demands are quite di�erent depending on thephysi s pro ess to be studied.4.2.3 Hadroni CalorimetryWhen a hadron passes through matter, it intera ts with the nu lei of themedium through strong intera tion pro esses. These pro esses are more8The angle enters into the Higgs mass resolution, and sin e at high luminositythe vertex will not be known pre isely, it is ne essary to measure this angle with the alorimeter.

88 4. CalorimetrydiÆ ult to des ribe and predi t than ele tromagneti ones. Mainly,the de-velopment of the hadroni shoewer an be understood in two phases: they an be divided in two di�erent groups (see �g. 4.3):� High-energy as ade phaseThe intera tion of a highly energeti in ident hadron with the nu- leus in the matter auses multiple produ tions of se ondary parti les.Mesons ��, �0 are most of them. If the energy is suÆ ient, other par-ti les are produ ed as well (fast protons, neutrons and heavier frag-ments). The nu leus (or its remnant) is always left in an ex ited state.All the reated parti les (ex ept of �0, see bellow), if having enoughenergy, an take part in se ondary nu lear intera tions, thus produ ingthe hadroni shower.� Nu lear pro esses phaseThe ex ited nu leus de reases its energy by evaporation of nu leons(e.g. slow neutrons) and by -transitions.

Figure 4.3: S hemati of the hadroni shower development.Hadron showers develop through a as ade of strongly intera ting parti- les initiated by an in oming hadron. A s hemati view of a hadroni showeris shown in �gure4.3. From ea h intera tion some hadroni parti les (pions,protons, neutrons, ...) are generated whi h extend the shower until the en-ergy is below the threshold for nu lear intera tion. During this sequen e,photons from �0 de ay are also produ ed, whi h initiate ele tromagneti showers within the hadroni as ade. Hen e hadroni shower ontains two omponents: a purely hadroni part and an ele tromagneti one.� Ele tromagneti omponent : A onsiderable part9 of se ondaryparti les are �0's, whi h will shower ele tromagneti ally after the �0 !9The ele tromagneti omponent f�0 of hadroni shower varies as the logarithm oftheenergy: f�0(E) = 0.11 ln E(GeV).

4.2. Basi on epts of Calorimetry 89 de ay, without any further nu lear intera tions. The size of theele tromagneti omponent is largely determined by the produ tion of�0 in the early stages of the shower development and it depends onthe in ident energy.� Hadroni omponent :- High energy hadrons, whi h further ause the multiple produ -tion.- Invisible energy follows from the ases, when either some energyamount is spent on breaking the nu lei (binding energy) or someparti les es ape the dete tion (muons and neutrinos; they areprodu ts of the harged pion de ays). This part (� 15-20% at10 GeV in ident parti le) does not ontribute to the measuredsignal.- Ionization energy loss of harged parti les.- Low-energy neutrons.

Figure 4.4: longitudinal pro�le of energy deposition for pion showers of di�erent energies.The distribution of the deposited hadron energy is similar to that of anele tromagneti shower, but shower dimensions are very di�erent (see �g.4.4). The radial spread is aused by nu lear intera tions with an averagepT of 350 MeV. Consequently both the longitudinal and radial spread aremu h larger for hadroni than for ele tromagneti as ades and also the u tuations are larger due to the large variety of di�erent possible pro esses.The longitudinal shower pro�le is des ribed in units of the intera tion length

90 4. Calorimetry�int, whi h has the meaning of the mean distan e between inelasti ollisionsof hadrons with nu lei: �int = ANA�� (4.4)where A is the absorber mass number, � is the density, NA is the Avogadro's onstant and � is the inelasti ross-se tion.Lateral shower pro�le shows a relatively high energeti ollimated ore,due to �0 produ tion in the shower, with an halo produ ed by shower par-ti les of lower energy, whi h move further away from the shower axis. Thelateral dimensions s ale with �, but also depend on the energy of the in identparti le.The shower dimensions an be used to distinguish between hadroni andele tromagneti showers, most easily in materials with large Z. In this ase,the ratio �=X0 is high and, therefore, the hadroni showers are even mu hlonger and wider than the ele tromagneti showers.4.2.4 Energy resolution and limitation of hadroni alorime-tersAs for ele tromagneti alorimeters, one an parametrize the energyresolution by the relation 4.1. The �rst term, a, is the quadrati sum ofsampling u tuations and intrinsi resolution.a) The sampling u tuations are roughly twi e larger for hadroni showers than for ele tromagneti showers in the same alorimeter. InATLAS experiment:- in EM alorimeters the typi al values are a � 10%,- in hadroni alorimeters they typi ally amount to a � 50%.b) Intrinsi u tuations in hadroni shower development are greaterthan those for an ele tromagneti shower. This is not only be ausethe shower is produ ed by relatively few intera tions, but also be ausepro esses develop very di�erently.One of the most important parameters for energy resolution in a hadroni alorimeter is the ratio of observed signal for the ele tromagneti (e) ompo-nent and the non-ele tromagneti or \pure" hadroni omponent (h) of anhadroni shower, the so- alled eh ratio. The onsequen es of eh 6= 1 in lude:- A ontribution to the energy resolution due to u tuations in the fra -tion of the ele tromagneti omponent;

4.2. Basi on epts of Calorimetry 91- A non-linear response with energy;- A non-gaussian signal distribution;- Constant term deviations, whi h dominate the energy resolution athigh energies.- The e=� ratio is energy-dependent as well and its relation to the e/hratio is given by the formula10� e�� = e< f�0 > e+ (1� < f�0 >)h = e1 + (e=h� 1)0:11lnE (4.5)The ratio e=� an simply be measured at Test Beams and the ratioe/h is then determined by the previous relation.The ompensation ( eh = 1), an be a hieved by in reasing the response ofthe non-EM omponent or by redu ing the EM part of the hadroni shower:a) The EM response an be de reased by ombining a low-Z a tive ma-terial with a high A-absorber in order to suppress the response fromthe photoele tri e�e t in the a tive material.b) The non-EM response an be in reased:i) by using a �ssionable material as an absorber, su h as depleteduranium. The extra energy reated in the nu lear �ssion rea tion an be dete ted in the readout materialii) by using a hydrogenous material as the a tive omponent. In su hmaterial, due to elasti n-p s attering, as the masses of a neutronand a proton are approximately the same, a neutron transfers toa proton about one half of its energy in ea h ollision. So, protonswill take up an appre iable fra tion of the energy of the neutron,and will produ e a visible ionization signal.Therefore, the e/h ratio an be tuned by hanging the a tive/passive layersvolume ratio (so- alled sampling fra tion).Another possibility is the o�-line orre tions. Highly granular alorime-ters provide detailed information on the longitudinal shower pro�le. As theradiation length X0 is mu h smaller than �int in high-Z absorbers, the lon-gitudinal dimension of the EM as ade is mu h shorter than that of the10Sin e the fra tion of the hadron energy spent on the �0 produ tion (i.e. onvertedto the EM omponent) u tuates (< f�0 >' 0:11 ln E(GeV)), it in uen es the energyresolution..

92 4. Calorimetryhadroni shower. This an be exploited to separate the EM omponent andthen appropriated weighting fa tors an be applied.The se ond term in the energy resolution parameterization, b, as well asthe onstant term, , has the same ontributions than the ones for the EM alorimeters. However, there is an additional ontribution from eh 6= 1 thatis typi ally the main irredu ible ontribution to the onstant term.The two general-purpose LHC experiments have hosen hadroni alori-meters without ompensation. The ATLAS entral hadroni alorimeter,TileCal, is made of large s intillating tiles based on a sampling stru turewith interleaved steel absorber and s intillating plates read out by wave-length shifting �bers. The e/h ratio for su h a alorimeter is around 1.1-1.2.The introdu tion of depth segmentation allows the appli ation of software orre tions that restore linearity, thereby ful�lling the requirements withoutthe onstraints imposed by the design of a ompensating alorimeter.

Referen es: 93Referen es:[1℄ ATLAS Collaboration:ATLAS Te hni al Proposal for a General-Purpose pp experiment at the Large Hadron Collider CERN,CERN/LHCC/94-93, (1994)[2℄ ATLAS Collaboration: ATLAS Dete tor and Physi s Performan eTe hni al Design Report Vol 1, CERN/LHCC/99- 14 (1999)[3℄ ATLAS Collaboration: ATLAS Dete tor and Physi s Performan eTe hni al Design Report Vol 2, CERN/LHCC/99- 15 (1999)[4℄ ATLAS Collaboration: ATLAS Calorimeter Performan e,CERN/LHCC/96-40 (1996).[5℄ ATLAS Collaboration: LIQUID ARGON CALORIMETER, Te hni alDesign Resport CERN/LHCC/96-41 (1996)[6℄ ATLAS Collaboration: TILE CALORIMETER, Te hni al Design Re-sport CERN/LHCC/96-42 (1996)General Bibliography of parti le dete tors:- R.C. Fernow, Introdu tion to experimental parti le physi s, CambridgeUniversity Press, 1986- D. Green, The physi s of parti le dete tors, Cambridge UniversityPress, 2000- C. Grupen,Parti le dete tors, Cambridge University Press, 1996- K. Kleinkne ht, Dete tors for parti le radiation, Cambridge UniversityPress, se ond edition, 1998- G.F. Knoll, Radiation dete tion and measurement, 3rd ed., Wiley, NewYork, 1999- W.R. Leo, Te hniques for nu lear and parti le physi s experiments. AHow-to Approa h. Se ond revised edition, Springer Verlag, 1994More spe ialisti Bibliography for Calorimetry:- R. Wigmans, Calorimetry : energy measurement in parti le physi s,Oxford Clarendon, 2000

94 Referen es:- G. Lutz, Semi ondu tor radiation dete tors : devi e physi s, SpringerVerlag, 1999- W. Blum and L. Rolandi, Parti le dete tion with drift hambers, SpringerVerlag, 1993- Tejinder S. Virdee, CALORIMETRY, EP Division, CERN and Impe-rial College of S ien e Te hnology and Medi ine, London, UK- Venkatesh S Kaushik, Ele tromagneti Showers and Shower Dete tors,Dept of High Energy Physi s, Univ.of Texas at Arlington, 2002Via internet:- R.K.Bo k and A.Vasiles u,The Parti le Dete tor Briefbook, CERN,1998, http://physi s.web. ern. h/Physi s/Parti leDete tor/BriefBook/- D.E.Groom et al., The Review of Parti le Physi s, The EuropeanPhysi al Journal C15, 1(2000)http://pdg.web. ern. h/pdg/2001/ ontents sports.html- H. Spieler, Introdu tion to Radiation Dete tors and Ele troni s, Le -ture Notes - Physi s 198, Spring Semester 1999 - UC Berkeleyhttp://www-physi s.lbl.gov/%7Espieler/physi s 198 notes 1999/index.html- H. Spieler, Radiation Dete tors and Signal Pro essing, Le ture Notes- VII. Heidelberger Graduate Le tures in Physi s, University of Hei-delberg { O t. 8 - 12, 2001http://www-physi s.lbl.gov/%7Espieler/Heidelberg Notes/index.html- C. Joram,Parti le Dete tors 1-5, CERN Summer Student Le ture Pro-gramme, July 2001http://do uments. ern. h/AGE/ urrent/fullAgenda.php?ida=a01471- O.Bruning, A elerators 1-5, CERN Summer Student Le ture Pro-gramme, July 2001http://do uments. ern. h/AGE/ urrent/fullAgenda.php?ida=a01490- E.J.N. Wilson, Introdu tion to Parti le A elerators, CERN Le turesfor postgraduates students, O tober 2001http://at -apwg.web. ern. h/at -apwg/wap/Wilson.html- C.Booth, Nu lear and Parti le Dete torshttp://www.shef.a .uk/uni/a ademi /N-Q/phys/tea hing/phy311/

Referen es: 95- C.Gruppen, Physi s of Parti le dete tionhttp://www.nikhef.nl/�i73/instrumentation.html- Geant4 Workshop, February 2002http://geant4.sla .stanford.edu/UsersWorkshop/- Em Shower simulation demonstrationhttp://www2.sla .stanford.edu/vv /egs/basi simtool.html- S. Humphries, Prin iples of Charged Parti le A elerationhttp://www.ee e.unm.edu/fa ulty/humphrie/ pa/ pa.htm

96 Referen es:

Chapter 5Full Simulation andRe onstru tion in ATHENA5.1 Introdu tionThe requierements for the dete tor performan e[1℄ and physi s perfor- man e[2℄are sometimes on i ting:� Full simulations using the GEANT[3℄ pa kage have been promoteredby the dete tor simulation (Inner Dete tor, LAr and Tile Calorime-ters and Muon System) and ombined-performan e (b-tagging, ele -trons/photons, jets/EmissT , muons and trigger) working groups. Thesesimulations have to be performed in an environment ontaining manyintera tions per beam- rossing and high rates of ba kground noise fromlow-energy neutrons.� Nevertheles, Fast simulation of high-statisti s signal and ba kgroundsamples of omplete physi s events are used by the physi s-simulationworking groups (Higgs bosons, supersymmetry, B-physi s and topphysi s).In some ases, results from full simullation and re onstru tion have beenused to improve, re�ne and enri h the fast-simulation program1.Monte Carlo (MC) simulation te hniques are widely used in High EnergyPhysi s (HEP) in order to ompare the theoreti al models to the experimen-tal results and to make studies of the potential of a physi s experiment. Su h1The results from full simulation are used as parametrization in Atlfast, for examplethe energy resolution in alorimeter. 97

98 5. Full Simulation and Re onstru tion in ATHENAsimulations are used for generating the physi s pro esses a ording to a er-tain theoreti al framework and also for parametrising the dete tor response.In this hapter, the tools used for generating the Monte Carlo event sam-ples for the analysis presented in this thesis are reviewed. The di�erent stepson the ATLAS simulation are summarized in se tion 5.2. The frameworkand the main omponents of the Athena are exposed in se tion 5.3. TheATLAS o�ine software organization is explained in se tion 5.4. The mainalgorithms of Athena are des ribed in se tion 5.5, in spe ial, the steps ofthe jet re onstru tion in Athena (se tion 5.5.4) as well as the available soft-ware pa kages related with this task. Then, in se tion 5.6, the Monte Carloevent generation with the Pythia pa kage is presented. Finally the di�erentreleases of Athena used in this thesis are explained in the last se tion.5.2 Full Simulation: GEANTThe ATLAS simulation program an be logi ally divided into three separatedmodules:- event generation;- dete tor simulation;- digitisation;Every dete tor simulation has to start with a des ription of the dete torgeometry. For the ATLAS dete tor almost every detail is in luded in the de-te tor des ription2. However, some simpli� ations are used in the materialswhi h do not a t as a tive dete ting elements3.The event generation phase is exe uted separately in order to havea onsistent input stream, whi h an be used many times. It allows usa systemati omparison among the di�erent physi s Monte Carlo genera-tor programs[4℄ (PYTHIA[5℄, HERWING[6℄, ISAJET[7℄...), provinding ananalysis framework at the event level.The GEANT environment is used for the geometry des ription and thefull dete tor simulation in luding the tra king of the parti les and theele troni s response of the a tive dete tor elements. The simulation of thedete tor is important during the design phase to develop a dete tor with an2Taking the TRT as an example, the arbon �bre shells of the modules, the straw walls,the gas omposition inside and outside the straws, and the wires are all in luded.3In the support stru ture, the ooling and the ele troni s, the materials are assumedto have a at distribution in the ' oordinate.

5.2. Full Simulation: GEANT 99optimal dis overy potential within the onstraints from te hnology, surviv-ability and �nan es. When the �nal dete tor is taking data the simulationsbe ome important for alibration and understanding of the data. The de-te tor simulation part of the ATLAS geometry in GEANT is the most time onsuming and riti al; it an be run with di�erent initial onditions (e.g.geometri al setup) on the same set of physi s performan e. All the ATLASsubdete tors have been des ribed to a very high level of detail, in luding in-a tive material ( ryostats, support stru tures, servi es, et ) that have beenshown to have a dire t impa t on the physi s performan e of the experiment.For the Inner Dete tor the most important physi s pro esses simulatedare multiple s attering, ontinuous energy loss, bremsstrahlung for ele trons, onversions for photons and nu lear intera tions for the hadrons. To geta urate results from a GEANT simulation it is thus ne essary to haveboth: the orre t distribution and omposition of the materials.For the alorimeters the des ription of the shower pro esses are the mostimportant. The showers are simulated by following all the parti les reatedin the showering pro ess. Parti les are tra ed down to an energy of 100 keVat whi h point they stop and deposit their remaining energy. For ele tromag-neti showers the physi s pro esses of pair produ tion and bremsstrahlungare rather simple whereas the nu lear pro esses involved in hadroni show-ers are ompli ated and are not understood in as great detail. In parti ularthe u tuations in the response of the hadroni alorimeter are diÆ ult tosimulate with suÆ ient a ura y.Also the magneti �eld is simulated through a ombination of spe i� programs to evaluate the �eld in the Inner dete tor, alorimeters and Muonsystem. The �eld map is read in the initialisation phase, so that it an bealso used by the re onstru tion program.The information is stored on tape at the end of ea h event through anautomated pro edure, where the user an reprodu e the dete tor response atthe digitisation step. The information olle ted, although dependent on thegeometry used by GEANT for event tra king, is nevertheless very generaland does not ontain any assumption on the dete tor readout stru ture.It onsists of hit positions (for tra king dete tors) and energy losses (for alorimeters), and it provides the basis for the simulation of the dete torresponse whi h takes pla e in the digitisation step.The digitisation step is a se ond level of dete tor simulation, pla edjust at the interfa e with the re onstru tion program, where the physi alinformation registered is olle ted, re-pro essed in order to simulate thedete tor output, and eventually written out to be used by the re onstru tionprograms. The simulated data should at this point be equivalent in format

100 5. Full Simulation and Re onstru tion in ATHENAto the data that will eventually be re orded with the ATLAS dete tor. Thesimulation of noisy and dead hannels in the ele troni s is also a part of thedigitisation phase. The digitisation step is very fast, ex ept when pile-upand high luminosity is in luded.The re onstru tion step in a dete tor simulation involves the re on-stru tion of the kinemati information and parti le identi� ation. For theInner Dete tor and the muon system, tra ks are re onstru ted from the hitsin the individual dete tor elements. In the alorimeter, the deposited en-ergy in ells is obtained and grouped together in lusters. At a later stage inthe re onstru tion all information an be ombined to obtain the kinemati information of the event.The output is stored in a menu-driven ombined n-tuple whi h allowsrapid he ks, analysis in PAW/ROOT framework and omparisons betweenalgorithms. The goal of the Combined Physi s Ntuple (CBNT) is to providean easy a ess to basi quantities from the ATLAS subdete tor (tra ks,ele tromagneti luster, jets, muon ...) and to more elaborated quantities ombining information from several dete tors (e=gamma=tau identi� ation,overall muon re onstru tion...).5.3 Athena FrameworkAthena[8℄ is the ATLAS o�ine software framework that represents a on- rete implementation of a underlying arquite ture. An arquite ture onsistof the spe i� ations of a number of omponents and their intera tions withea h other. A omponent is a \blo k" of software whi h has a well spe i�edinterfa e and fun tionally. An interfa e is a olle tion of methods alongwith a statement of what ea h method a tually does, i.e., its fun tionality.ATLAS re onstru tion is now being developed in the Athena framework,based on Gaudi[9℄[10℄, initially developed by LHCb[11℄. So, with GAUDI,in HEP experiments, a framework an be used to develop all kinds of eventdata pro essing appli ations running in the various pro essing environments.Examples in lude the high level triggers that a quire their data dire tly fromthe online system, the event simulation software that runs over o�ine datain a bat h environment and the event visualization software whi h is usedintera tively. In that sense, ATHENA is a framework written in C++ thatis the spe i� implementation for ATLAS.

5.3. Athena Framework 1015.3.1 Athena ComponentsIt is intended that almost software written by physi ists, whether for eventgeneration, re onstru tion or analysis, will be in form of spe ialisations ofa few spe i� omponents. Here, spe ialisation means taking a standard omponent and adding to its fun tionality while keeping un hanged theinterfa e. Within the appli ation framework this is done by deriving new lasses from one of the base lasses. In Fig. 5.1, the ATHENA-GAUDIobje t diagram is shown. The most important ATHENA omponents are:� Algorithms form the basi building blo ks of user appli ations, andgenerally a ept input data, manipulate it in some way, and gener-ate new output data. They represent the primary algorithm part ofan appli ation, performing, for example, tra k �nding and �tting, theasso iation of alorimeter hits into lusters and towers, and the asso- iation of parti le types with tra ks and lusters. Algorithms an besimple or omposite, i.e., may delegate pro esses to sub-Algorithms:- inherents from Algoritm lass- implements three methods for invo ation by framework:initialize(), exe ute(), �nalize().The exe ute() method is alled on e per physi s event.Algorithms an also a t as �lters, indi ating that a parti ular eventdoes not meet its sele tion or �lter riteria.� Data Obje ts are what are passed between Algorithms, a ting astheir input and output.Physi s analysis and event re onstru tion implies the manipulation ofmathemati al or physi al quantities: points, ve tors, matri es, hits,moments,et ., by algorithms.� Converters hange obje ts from one representation to another. Theirexisten e is mainly for te hni al reasonse. One parti ular use withinAthena is to provide expli it/impli it onversion from/to persistentdata to/from transient data.� Transient Data Store(s) (TDS): In order to redu e the ouplingbetween Algorithms, several so- alled transient stores are available.They a t as the temporary repository for data obje ts.There are dif-ferent transient stores with di�erent lifetime poli ies:

102 5. Full Simulation and Re onstru tion in ATHENA{ the event data store and transient event store,{ the dete tor data store,{ histogram store, ntuple store...Retrieving and registering of data with the transient stores is light-weight and does not involve physi al opying of data.� Servi es are a globally available software omponents that providespe i� apabilities of the framewok, e.g., Message servi e, Histogramservi e, et � Properties are Control and Data parameters for Algorithm and Ser-vi es that an be adjustable. They allow us to run time on�guration.Properties an be spe i�ed via a text �le (jobOptions) that is read dur-ing the startup phase of the appli ation, and, if s ripting is enabled,intera tively at run time from the s ripting language shell.

Figure 5.1: ATHENA-GAUDI obje t diagram, taken from [?℄5.4 ATLAS o�ine software organizationThe ATLAS o�ine software is grouped into di�erent pa kages. A pa kageis a set of algorithms and lasses that arry out a ommon appli ation:

5.5. Athena Algorithms 103for example, the GeneratorModules pa kage is omposed by the Algorithmsthat interfa e the di�erent Monte Carlo event generators like Pythia, Tauolaand Herwig.All these pa kages are embedded within the ATHENA framework thatprovides the needed servi es and utilities in order to run ea h appli ation.In ea h pa kage, the Data Obje ts are distinguished from the AlgorithmObje ts. For example, hits and tra ks may be onsidered as Data Obje ts,and the Algorithms to manipulate these Data Obje ts will be en apsulatedin di�erent obje ts su h as Tra kFinder.The methods in the Data Obje ts will be limited to manipulations of in-ternal data members. The Algorithms will, in general, pro ess Data Obje tsof some type and produ e new Data Obje ts of another type. For example,the Tra kFinder Algorithm will produ e tra k Data Obje ts from hit DataObje ts.The ATLAS o�ine software is organized in releases, that is, when sub-stantial modi� ations are done to the pa kages, a new release is onstituted.All releases are kept in the ATLAS CVS (Con urrent Versions System)[12℄repository.Moreover, a Con�guration Management Tool (CMT)[13℄ is used to build( ompile and link) and run the software.5.5 Athena AlgorithmsWith the ompletion of the �rst data hallenge, whi h meant pro essingseveral Terabytes of simulated data in worldwide distributed sites, ATLASre onstru tion software has rea hed a mature stage. Through years of de-velopment �rst in Fortran, now migrated to C++ in the exible Gaudiframework, the algorithms are now fairly omplete. This se tion des ribesthe main algorithmsThe sequen ing and on�guration of Algorithms are spe i�ed at run timethrough an ASCII jobOption �le. Binary libraries are loaded at run timeas well. This makes the on�guration of a job very exible, so that one ane.g. easily swit h between a very detailed simulation of the data ow anda oarser one, or swit h between (or even run simultaneously) two di�erent alorimeter lustering algorithms.It also allows an independent development of the ir a 300 pa kages in-volved in re onstru tion, by a hundred people world-wide. The developmentfollows a six month y le for major validated releases to be used by physi- ists and Data Challenges. There are also developer releases every three

104 5. Full Simulation and Re onstru tion in ATHENAweeks whi h fa ilitates the integration e�ort.A wide variety of algorithms have been developed in order to extra tthe best physi s from the Atlas dete tor. Studies are so far based on avery detailed Monte-Carlo simulation, with the performan es of ea h dete -tor arefully tuned on test beams data. In 2004, a barrel wedge with allthe ATLAS dete tors (tra king and alorimetry) and a alorimeter end- apwedge was put in the test beam.Data are being analyzed with an evolution of the software des ribed here,so that:(i) it is made robust against real data pe uliarities (mis- alibration andmisalignments, noisy or dead hannels...)(ii) algorithms an be tested in a real environment.A repa kaging is on-going so that all algorithms ommonalities (tools) arefa tored out, and that algorithms performing the same tasks with di�erentstrategies share the same interfa e. This will make ease algorithms improve-ment and new algorithms development, and their optimization for a varietyof physi s hannels and running onditions. High level trigger algorithmswill also share a large amount of tools with the o�ine re onstru tion.5.5.1 Tra kingTra k re onstru tion is des ribed in [14℄[15℄[16℄[17℄ 4. Tra king is per-formed up to pseudo rapidity 2.5 with three layers of pixels and four layers ofstereo sili on strip dete tors, followed by a straw tra ker providing typi ally30 drift time measurements per tra k, in addition to transition radiationdete tion apability. The transverse impa t parameter resolution at highpT approa hes 10 mi rons, degraded in the 1-10GeV/ range by multiples attering. The momentum resolution is multiple s attering dominated at1.5% up to 20 GeV/ . The addition of high luminosity pileup does not de-grade signi� antly the tra king performan e (ex ept speed) as the tra kerhas been optimized to resolve tra ks in high pT jets where the tra k densityis larger.4The tra k re onstru tion in the Inner Dete tor is performed by xKalman++ or iPa-tRe pa kages. The tra k re onstru tion in the Muon System is performed by Muonboyor Moore pa kages.

5.5. Athena Algorithms 1055.5.2 Ele tron and photon identi� ationEle tromagneti lusters are sear hed for with a sliding window algo-rithms[18℄. Re tangle lusters of typi ally 3 ells in eta (granularity 0.025)and 5 in phi (granularity 0.025) are preferred, for their robustness againstpile-up, underlying event and material e�e ts. The larger size in phi al-lows to re uperate photon onversion and ele tron bremsstrahlung, it analso be in reased if a onversion is re onstru ted. High pT ele tron/photonidenti� ation relies on the lateral and longitudinal shower shapes. The �nergranularity of the front sample (1/8 in � ) allows the reje tion of jets withleading neutral pion. Typi al jet reje tion of 3000 is obtained for a photoneÆ ien y of 80%. This is suÆ ient for the fake photon ontribution not tobe dominant for low mass Higgs sear h in the important H ! hannel.(see �g.5.2).Figure 5.2: Expe tedH ! signal at the LHC for an integrated luminosity of 100fb�1.Left: the signal re onstru ted in ATLAS for mH=120 GeV is shown on top of the irre-du ible ba kground. Right: the signal re onstru ted in CMS for mH=130 GeV isshown after ba kground subtra tion.For ele tron identi� ation[19℄, an ele tron tra k (�tted allowing for bremssenergy loss) is sear hed for and mat hed in E=p. Transition Radiation (TR)hits[20℄ in the straw tra ker add a reje tion fa tor of 100 for 95% eÆ ien yto rea h overall a reje tion of almost 100000 for 70% eÆ ien y. Additionalparti le isolation requirements using tra king and alorimeter isolation analso be used but need to be tuned a ording to the hannel of interest. Forlow PT (below 7 GeV/ ) ele tron re onstru tion, tra ks satisfying TR hitidenti� ation are extrapolated to the e.m. alorimeter, where the energydeposition around the tra k impa t is tested against the ele tron showerhypothesis.The pre ise energy measurement of the ele tromagneti obje t is ompli- ated by the material (between one third and one radiation length) in frontof the alorimeter. Early photon onversion and ele tron bremsstrahlung

106 5. Full Simulation and Re onstru tion in ATHENA ause energy to be deposited in the material or soft ele tron to be deviatedby the magneti �eld outside the luster. The �rst order e�e t an be or-re ted by weighting the energy in the presampler and, for photon, by anexpli it re onstru tion of the onversion. Typi al energy resolution of 1.5%at pT = 50 GeV/ is obtained, with weak dependen e on pseudorapidityand luminosity.5.5.3 Muon identi� ation and re onstru tionThe muon spe trometer provides a standalone muon identi� ation[21℄and measurement from typi ally three stations in the toroids (�tted withtra king dete tors using four di�erent te hnologies), ea h apable of re- onstru ting a 3D segment of the muon traje tory. The eÆ ien y is typ-i ally 95%, due to holes for dete tor support and servi es. The eÆ ien ydrops at very high pT (above 500 GeV/ ) due to atastrophi energy loss inthe alorimeters, for whi h ele tromagneti showering disturbs the patternre ognition. Below 6 GeV/ , the muon energy loss in the alorimeter is ofthe order of its initial energy so that it is not possible anymore to follow themuon in the inhomogeneous magneti �eld.The re onstru ted muon is ba ktra ked to the intera tion point throughthe alorimeter, orre ted for its estimated energy loss, and ombined withits inner dete tor tra k[22℄ in order to improve the momentum resolutionfor pT up to 20GeV= 5.A omplementary approa h under study is to extrapolate the inner de-te tor tra k into the muon spe trometer, it would allow:(i) to de rease the identi� ation threshold to 4 GeV/ by using the innerstation only.(ii) to help sorting out the pattern re ognition for very high PT muon.Additional identi� ation information from m.i.p. energy deposit in the alorimeter is also investigated.5.5.4 Jet re onstru tionThe main task in the jet re onstru tion are:� Jet �nding5The typi al resonan es for mass resolution obtained are 45MeV= 2 for J= ! �+��,2:9GeV= 2 for Z ! � + �� (dominated by the natural width of the Z), 1:5GeV= 2 forH ! Z ! (�+�)Z(�+��) with a Higgs boson mass of 130GeV= 2.

5.5. Athena Algorithms 107� Jet energy alibration� Jet identi� ationSo, the existing software in Athena divides the problem of the jet measure-ment in various steps (see also �g. 5.3).1) ProtoJet building: In order to abstra t the input of jet algorithms,this is a prepro essing step that takes various obje ts via whi h jet an be re onstru ted and onverts them into a ProtoJet data obje t.Be ause this is the nexus point of input from di�erent pa kages, theissue of pa kage dependen y is non-trivial6.2) Jet �nding: In this step, one pro eeds using ET algorithms (moreinformation in Chapter 7) that luster parti les, alorimeter ells, tow-ers, et ., for nearness:- The Cone jet algorithms de�ne nearness in a geometri fashion:jets are omposed of hadrons whose 3-momenta lie within a onede�ned by a ir le in eta and phi.- In ontrast, KT jet algorithms de�ne nearness in terms of relativetransverse momentumOn e the parti les have been lustered together in a jet, in prin iplethere is an additional step of momentum adition of all the parti les ina jet alled the re ombination s heme.3) Asso iating information to the jet: To asso iate sub system infor-mation (e.g., luster, tra king, et .), to the jet using set of interfa es(so- alled helper lasses) that given a jet ould provide with the re-quired information.4) Jet energy alibraton: The re onstru ted jet energy will be or-re ted for various e�e ts asso iated with the dete tor (e/pi, magneti �eld, ryostati et ). The response of various sub-dete tors is nor-malized with respe t to EM s ale. Various methods have been usedin ATLAS to do energy orre tion for the TDR studies: Ben hmarkpro edure, H1 weighting, Sampling method, et , in luding weights forea h alorimeter ompartment, the presambler, the EM and hadroni alorimeter ans also a ryostati orre tion.The �rst step onsists on alibrating the experimentally measured jet6It is important to keep tra k of the dependen y of the various pa kages availabein Athena related with the jet re onstru tion (JetRe , JetEvent, TauRe , EFlowRe ,AtlFast..) with the rest of sotware pa kages in Athena, whi h an reate nasty loops.

108 5. Full Simulation and Re onstru tion in ATHENAenergy in the alorimeter su h as to reprodu e the parti le level energyinside the luster.5) Jet avour identi� ation: At present there is no ode available toidenti� ate the avor of the jet. It is important to know about thisquestion be ause the alibration will depend on the hypothesis (e.g. ifit is a light quark or a b-jet or a tau-jet).6) From re onstru ted jet to asso iated parton: The �nal stepof jet measurement onsists of inferring the energy of the parton thefragmentation of whi h resulted in the measured jet.

Figure 5.3: Di�erent steps of the jet measurement in Athena.To optimize the jet resolution, non-linear weights whi h use the longi-tudinal segmentation of the alorimeter are �tted. The best resolution isobtained by using seven sets of weights of the form:wi(j�j) = ai(j�j) + bi(j�j)=E + i(j�j)log(E) (5.1)where the index runs on the layers of the ele tromagneti and hadroni alorimeters. The j�j dependen e allows to take into a ount the varyinge�e tive length of the alorimeters, the material distribution and the de-graded measurements in the barrel end- ap transition region. The typi alresolution of: �E=E = 65%q(E)� 2% (5.2)is obtained at low pseudo-rapidity j�j � 0:8:Work has started on an energy ow algorithm whi h, after building lusters in the alorimeters with a nearest neighbor approa h, attempt to lassify them as ele tromagneti or hadroni , and bring them to the orre ts ale to take into a ount the non- ompensating nature of the alorimeters(by default anything in the EM alorimeter is brought to the e.m s ale).

5.5. Athena Algorithms 109Identi�ed ele trons and muons are properly subtra ted from the alorimeterenergy, and tra k measurements are used as well. The goal is to improve onthe jet resolution by a proper parti le hypothesis assignment.The Available Software in AthenaThere are several pa kages available in Athena related with jet re onstru -tion:1) JetRe : Contains algorithms related with jet �nding and energy or-re tion.2) Jet Event: Contains the data lasses related with jet re onstru tion.3) TauRe : A dedi ated pa kage for tau re onstru tion.4) E owRe : An energy ow pa kage for ATLAS, ombining alorime-try, tra king and parti le ID information in order to improve energyresolution for jets and ETmiss.5) CaloNavPro essors: Provides pro essors to navigate omposite ob-je ts.6) NavigationRep: Sets up the representation domain used in navigat-ing omposite obje ts.7) LAr, Tile and AtlFast pa kages: that produ e ell, tower and luster in the alorimeter.8) CombinedJetRe : A new pa kage for energy orre tion and alibra-tion algorithms.5.5.5 Missing transverse energyThere are two aspe ts that play an important role in the measurement ofthe missing transverse energy (ETmiss) at the LHC. First of all, ETmiss is animportant signal for new physi s, for example, in the produ tion and de ayof SUSY parti les su h as H� in the H� ! �� hannel, and of SM Higgsboson through the H ! ZZ ! ll�� hannel. Therefore, minimization offake high-ETmiss tails produ ed by instrumental e�e ts, su h as jets badlymeasured in a alorimeter ra k is mandatory in order to observe events hara terized by true missing transverse energy.Se ondly, good ETmiss resolution is needed when re onstru ting a narrowinvariant mass distribution for new (heavy) parti les involving neutrinos

110 5. Full Simulation and Re onstru tion in ATHENAamong their de ay produ ts. These two fa tors are losely related to theperforman e of the alorimeters: good energy resolution, good response,linearity and hermeti overage are required.The urrent algorithm is devoted to ompute the visible transverse mo-mentum in the alorimeter from all ells above a threshold, expressed insigma units of the expe ted noise. The resolution s ales with the squareroot of the visible transverse energy:�px = 0:48qXET (5.3)and is fairly independent of the physi s hannel (e.gW ! l�l or A0 ! �+��)provided this dependen e is taken into a ount. There is under study is thepossibility to ompute the visible transverse energy from the energy owre onstru tion.5.5.6 Other sofwtare algorithmsThe b-jet taggingThe b-jet tagging is an important tool for low mass Higgs sear h due to thelong list of de ay hannels where b quarks are involved. The b-jet taggingrelies on the ombination of the transverse and longitudinal tra k impa t pa-rameter (IP) of the jet tra ks after severe quality requirements to avoid fakedispla ements7. The reje tion degrades at larger pseudo-rapidity mainlybe ause of material e�e ts, leading to deterioration of impa t parameterresolution and produ ing more high IP tra ks from onversion and hadroni intera tions.The � identi� ationHadroni � de ay identi� ation is ru ial in the pseudos alar super-symmetri Higgs dis overy hannel A0 ! �+ �� . Being the � being the heaviest lepton,often appears in the most opious de ay modes of other super-symmetri parti les. Hadroni tau de ay appears as a very narrow isolated jet (whi h an be estimated thanks to the �ne granularity of the front ele tromagneti alorimeter sampling) with small tra k multipli ity. The pT dependen e ofthe identi� ation is very strong8.7Typi al u-jet reje tion of 100 for H ! b�b with mH =120 GeV/ 2 and 60% b-jeteÆ ien y is obtained.8The width of a QCD jet in reases with energy when it de reases for a � given thehigher relativisti boost.

5.6. Monte Carlo event generators 1115.6 Monte Carlo event generatorsEvent generators simulate the s attering pro esses in high energy physi s. In�gure 5.4 the s heme of the generators situation inside Athena frameworkis shown. Su h pro esses an be omplex and large programs are neededto simulate the large variety of intera tions. In the following subse tions,the Pythia MC generator used for the analysis presented in this thesis issummarized.

Figure 5.4: S heme of the generators situation inside Athena framework.5.6.1 PythiaPythia, written in Fortran, is one of the most general event generators,sin e it in ludes a large number of s attering pro esses. The program ansimulate the ollisions of ee, pp, p�p and ep. From the version 6.1 on, theoriginal Pythia and Jetset programs have merged. For this thesis, Pythiaversion 6.201 was used. Together they ontain theory and models fora number of physi s aspe ts, in luding hard and soft intera tions, partondistributions, initial and �nal state parton showers, multiple intera tions,fragmentation and de ay.

112 5. Full Simulation and Re onstru tion in ATHENAPythiaModuleIn order to run Pythia within the ATHENA framework, one makes use ofthe PythiaModule Algorithm from the GeneratorModules pa kage (versionGeneratorModules-01-02-08 was used). PythiaModule is an interfa e tothe Fortran Pythia ode. The PythiaModule Algorithm runs Pythia withinATHENA and puts the generated events in the Transient Data Store so they an be used later by other Algorithms like Atlfast. The Pythia parametersare set from the jobOptions Servi e via a text jobOptions �le.5.7 Athena releases usedFor the analysis presented in this thesis, several pa kages were employed,within the Athena release:- 6.2.0 for Energy Flow analysis in Atlfast ( hapter 8)- 7.8.0 and 8.2.0 for lustering algorithm analysis with simulated parti- les in Athena ( hapter 9 and 10)- 9.1.2 and 10.0.2 for lustering analysis with Combined Test Beam data( hapter 11 and 12)On the other hand, the Atlfast [23℄[24℄ simulation pa kage was used for fastevent simulation and is going to be reviewed in the next hapter.

Referen es: 113Referen es:[1℄ ATLAS Collaboration: ATLAS Dete tor and Physi s Performan eTe hni al Design Report Vol 1, CERN/LHCC/99- 14, 25 May 1999[2℄ ATLAS Calorimeter Performan e, CERN/LHCC/96-40, ATLAS TDR1, (1996).[3℄ Geant4 Users do uments:http://wwwasd.web. ern. h/wwwasd/geant4/G4UsersDo uments/Overview/html/index.html[4℄ Atlas Monte Carlo Interfa es:www-theory.lbl.gov/ ianh/monte/Generators/[5℄ T.Sjostrand, Comput. Phys. Commun. 82 (1994):, T.Sjostrand et al,Comput. Phys. Commun. 135 (2001) 238; T.Sjostrand, L. Lonnbladand S Mrenna PYTHIA 6.2 - Physi s and Manual, [online℄ hep-ph/0108264, august:2001. Available from: http://weblib. ern. h/.[6℄ G. Mar hesini, B. R. Webber, G. Abbendi, I.G. Knowles, M.H. Seymourand L. Stan o. The HERWING Manual. Cop. Phys. Comm 71 (1992)15[7℄ ISAJET web page: www.phy.bnl.gov/ isajet/[8℄ Athena User and Developer Guide v.2.0 & Releaseshttp://atlas.web. ern. h/Atlas/GROUPS/SOFTWARE/OO/ar hite -ture/General/[9℄ M. Cattaneo et al.: in Pro eedings of 2001 Conferen e for Computingin High Energy and Nu lear Physi s, Beijing[10℄ Gaudi Data Pro essing Appli ations Framework, Developers GuideCorresponding to Gaudi release v9, De 2001[11℄ LHCb Collaboration, http://lh b.web. ern. h/lh b/[12℄ http://atlas.web. ern. h/Atkas/GROUPS/SOFTWARE/OO/tools/ vs-server.html; http://www. vshome.org[13℄ http://www. mtsite.or[14℄ xKalman web: home. ern. h/ droussea/xkalman/xkalman.html

114 Referen es:[15℄ IPATREC: inner dete tor pattern-re ognition and tra k-�ttingatlasinfo. ern. h/Atlas/GROUPS/SOFTWARE/DOCUMENTS//IPATREC/ipatre .html[16℄ MuonBoy web info: atlas-samusog.web. ern. h/atlas-samusog/muonboy/Muonboy.htm[17℄ Moore: Muon Spe trometer tra k re onstru tion pa kage for ATLAS:people.na.infn.it/ bigliett/moore/MooreDo /MooreDo /[18℄ Mehdiyev, R ; Metreveli, Z ; Nevski, P ; Salihagi , D ; Test of Slid-ing Window Algorithm �r Jets Re onstru tion in ATLAS Hadroni Calorimeters . ATL-CAL-99-002[19℄ Rei hold, A; Spiwoks, R; Tsesmelis, Emmanuel. Ele tron Identi� ationUsing the ATLAS Inner Dete tor. ATL-INDET-93-027; ATL-I-PN-27.-Geneva : CERN, 04 Aug 1993 .[20℄ Mitsou, V A. The ATLAS Transition Radiation Tra ker. ATL-CONF-2003-012; hep-ex/0311058.- Geneva : CERN, 28 Nov 2003[21℄ Novk, G S; Pos h, C; Riegler, W. Parti le Identi� ation in the ATLASMuon Spe trometer / Novk, G S; Pos h, C; Riegler, W. ATL-MUON-2001-013; Geneva : CERN, 09 Jul 2001[22℄ Lagouri, T. A Muon Identi� ation and Combined Re onstru tion Pro- edure for the ATLAS Dete tor at the LHC at CERN / Lagouri, T.ATL-SLIDE-2003-007; CERN-ATL-SLIDE-2003-007.- Geneva : CERN[23℄ C++ version of Atlfast in Athena,http://www.hep.u l.a .uk/atlas/atlfast[24℄ E.Ri hter-Was, 'ATLFAST 2.0 A fast simulation pa kage for ATLAS',ATLAS Note ATL-PHYS-98-131 (1998)

Chapter 6ATLFAST: the FastSimulation6.1 Introdu tionIn this hapter the ATLAS[1℄ fast simulation and re onstru tion program,ATLFAST, is des ribed: its main hara teristi s (se tion 6.2), its organiza-tion (se tion 6.3) and the di�erent Athena Algorithms in Atlfast, so- alledMakers, for the di�erent obje ts de�ned in Atlfast , in parti ular, the makersfor jet are explained (se tion 6.3.3).6.2 Atlfast: Fast Simulation and re onstru tionATLFAST[2℄[3℄ is a parti le-level simulation program whi h allows for fastanalysis of the fully generated event in the pp ollisions. It provides a fastparti le-level simulation and re onstru tion. ATLFAST is a C++ Obje tOriented implementation of a ATLAS fast simulation pa kage whi h run inthe Athena framework.The task of ATLFAST is to take imput four-ve tors and to provide or-responding out put re onstru ted quantities as obje ts: ele trons, muons,photons, ells jets and tra ks. It performs smearing of parti les four mo-mentum and uses a simple alorimeter s heme from whi h lusters and jets an be re onstru ted. It also performs tra k �nding and smearing.Atlfast has some hara teristi s and advantages respe t to full dete torsimulation and re onstru tion:- less CPU- onsuming than full simulation,115

116 6. ATLFAST: the Fast Simulation- the needed approa h for qui k and approximate estimates of signaland ba kground rates for espe i� hannels,- the only pra ti al tool for high-statisti s studies of omplex ba k-ground pro esses.ATLFAST an be used for fast simulation of signal and ba kgroung,in luding parametrisation of the most ru ial dete tor aspe ts:- jet re onstru tion in the alorimeters- pT and energy smearing for leptons and photons (see �g. 6.1)- magneti �eld e�e ts- missing transverse energy

Figure 6.1: Comparison betweeen Full Simulation and Fast simulation exe ution, takenfrom [2℄.It provides, starting from the list of parti les in the event (see �g. 6.2):- ells and lusters,- isolated leptons (ele trons and muons) and isolated photons- a list of re onstru ted jets,- the expe ted missing transverse energy,- re onstru tred harged tra ks.

6.2. Atlfast: Fast Simulation and re onstru tion 117

Figure 6.2: S heme of the di�erent steps in Atlfast: from Generators to Output �le(Ntuple), passing for the Atlfast obje ts ( ells, lusters, re onstru ted parti les, jets ...)and the Atlfast algorithms, taken from [6℄.In most ases, the dete tor-dependent parameters are tuned to what isexpe ted for the performan e of the ATLAS dete tor from full simulationand re onstru tion.The main goal of the Atlfast pa kage is to reprodu e as well as pos-sible the expe ted dete tor performan e in terms of the resolution andparti le-identi� ation for important physi s signals. A reasonably a u-rate parametrisation of photon, ele tron and muon momentum resolutionis in luded, as well as a parametrisation of the hadroni alorimeter energyresolution and the e�e t of the ATLAS magneti �eld on jet re onstru -tion. The re onstru tion of helix tra k parameters in the Inner Dete tor isalso provided with separate parametrisations of the resolutions for muon,ele tron and pion tra ks.Not all the dete tor e�e ts an be readily parametrised in fast simulationand only the basi information of the dete tor geometry is used, for example:- the �- overage for pre ision physi s and for the alorimetry,- the size of the barrel/end- ap transition region for the EM Calorimeter,- the granularity of the hadroni (ATLFAST takes this value for thewhole alorimeters: EM + HAD).

118 6. ATLFAST: the Fast SimulationNo e�e ts related to the detailed shapes of parti le showers in the alorime-ters, the harged tra k multipli ity in jets, et , are taken into a ount. Inparti ular, the energy isolation of leptons is only simulated in a rude way.In the following, the main features of ATLFAST whi h are interested forthis analysis and their relationship to the full simulation and re onstru tionresults are des ribed.6.3 ATHENA-Atlfast organizationAthena Algorithms are alled Makers, following the terminology of an earlierFortran version of Atlfast. The Makers read input from the TES and makethe output obje ts, whi h are written to the TES. Some makers produ emore than one obje t per event: eg JetMaker generally writes many jets perevent.

Figure 6.3: Exe ution order of Algorithms in AtlfastAlgs.The ATHENA-Atlfast pa kage is organized in several subpa kages. Themost important ones are AtlfastAlgs and AtlfastEvent.� AtlfastAlgs ontains the ATHENA-Algorithms that are responsiblefor the re onstru tion of tra ks, jets, isolated leptons and missingtransverse e nergy.

6.3. ATHENA-Atlfast organization 119� AtlfastEvent is a subpa kage that holds the Data Obje ts produ edby AtlfastAlgs algorithms, namely re onstru ted parti les, ells, lusters, jets and tra ks.In the analysis for this thesis we have used spe i� ally, AtlfastAlgs-00-00-09 and AtlfastEvent-00-00-09 versions.All these Data Obje ts are ontained in Data Colle tion obje ts, su has JetColle tion, and they are kept in the Transient Data Store. The Stan-dardNtupleMaker Algorithm is in harge to onvert this Data Obje ts intopersisten y, by putting all their information in a HBOOK ntuple.The sequen e of exe ution of the di�erent Algorithms in AtlfastAlgs anbe seen in Fig. 6.3.6.3.1 Cells and ClustersThe transverse energies of all unde ayed parti les ex ept for neutrinos,muons and the SUSY LSP, are summed up in the alorimeter ells of gran-ularity in � x ' oordinates over the full alorimeter overage (j�j < 5), bydefault:�� x �� = 0.1 x 0.1 in j�j < 3.2, for Barrel,�� x �� = 0.2 x 0.2 in 3.2 < j�j < 5, for Forward- aps.The efe t of the solenoidal 2 T magneti �eld on the '-position of hargedparti les with pT above threshold (default:pT < 0.5 GeV) is parametrised.It is assumed that the ontribution from harged parti les with pT bellowthis threshold an be safely negle ted. A �xed- one algorithm is used forthe luster re onstru tion, but other algorithms an be a tivated as options(e.g. Sliding Windows algorithm, kT -algorithm, et .).All alorimeter ells with transverse energy greater than a given thresh-old (default: ET > 1.5 GeV) are taken as possible initiators of lusters.These are s anned in order of de reasing ET to verify whether the total ETsummed over all ells in a one �R = p�2� +�2' ex eeds the mimimumrequired threshold for a re onstru ted luster (default: ET > 10 GeV).The re onstru tion one is de�ned separately for the barrel/end up(j�j <3) and forward (j�j >3) part (default: �R =0.4). (It is possible toinvoke also the algorithm for a se ond hoi e of the �R value, �R =0.7).As oordinates of the re onstru ted lusters, (� lu; ' lu), are taken the �; 'of the bary entres of the ones weighted by the ell ET , for all ells insidethe one around the initiator ell.No energy smearing is applied yet to these lusters, sin e some of themrepresent photon lusters or ele tron lusters. Appropriate energy smearing

120 6. ATLFAST: the Fast Simulationwill be applied only after luster identi� ation. In the ATHENA-Atlfastversion, ell energy sharing of ells belonging to overlapping jets is not takeninto a ount (while it is done in the Fortran version).Figure 6.4: Exe ution order of the CellMaker algorithm and ClusterMaker algorithm.In the original Atlfast Fortran version it was not a publi output entity:it was used purely as an internal representation of the alorimeter. It is onlyin the more re ent times that requests for this to be ome an output entitywere made.� Cell is represented by a lass Cell whi h reates Cells from MonteCarlo Parti les and store in TES (see �g. 6.4).� Clusters are formed by summing the ell energy around initiators.6.3.2 Isolated ele trons, photons and muonsThose photon and ele tron andidates that are isolated from any hadroni a tivity are sear hed for in the parti le list. The photon and ele tron fourmomenta are smeared with a parametrisation that was derived from fullsimulation studies. Isolation riteria in terms of distan e from other lustersand of maximum transverse energy deposition in a one around the pho-ton/ele tron andidate, as well as the geometri al a eptan e, are veri�ed(default: separation by �R > 0.4 from other lusters and ET < 10 GeV ina one �R = 0.2 around the photon/ele tron).Isolated muons are also sear hed for in the parti le list. Their momen-tum is smeared a ording to a resolution parametrised as a fun tion of themuon pT , j�j and �. Three options depending on whi h subdete tors are as-sumed to be used for the muon measurement an be invoked: Muon Systemstandalone, Inner Dete tor standalone and ombined Inner Dete tor plusMuon System. Isolation riteria in terms of distan e from other lusters

6.3. ATHENA-Atlfast organization 121and of maximum transverse energy deposition in a one around the muon andidate, as well as the �du ial geometri al a eptan e, are applied.However, Atlfast does not orre t for eÆ ien ies in the re onstru tionand identi� ation of muons, ele trons nor photons, so the estimated eÆ- ien ies (from full simulation studies) should be in luded by the user in theevent analysis.6.3.3 Jet Re onstru tion in AtlfastClustered ells are used for the jets re onstru tion. As a default, a onesize of �R = 0.4 is used. The energie of lusters, whi h have not beensele ted as asso iated with isolated ele trons or photons, are smeared withthe energy resolution, parametrised a ording to results from full simulationof the hadron alorimeters. Two options an be invoked:- low luminosity- high luminosity, where expe ted pile-up e�e t are in luded.The measured momenta from non-isolated muons whi h fall inside the lus-ter one and are within j�j <2.5 are added to the smeared luster energy.Re onstru tion with the JetFinder library of alternative jet algorithms isalso implemented. Finally, the resulting jets with ET above a given thresh-old (in the present work we take di�erent values of ET for the di�erentrange of energies of the QCD jets, see hapter 8, se tion 8.6) as labeled asre onstru ted jets.Jet MakerThe main purpose of the Jet Maket is to over the fun tionality of smearingthe Cluster formed by ClusterMaker and to omplete the Jet onstru tion byadding non-isolated muons. Jets are Clusters whi h have not been asso iatedwith isolated parti les (ele trons or photons) and whi h have to pass somepre-de�ned kinemati riteria, see (�g. 6.5).In order to form Jets, JetMaker smears the luster four-momentum, addsnon-isolated muons whi h fall in a prede�ned R- one around the Jet and tagthe Jet with a avour.The JetCandidate is kept and labelled as a re onstru ted Jet if its energyis greater than a given threshold and its � passes the � �du ial ut. Optionsfor low and high luminosity allow to tune the smearer algorithm, adding tothe smearing fun tion a pile-up e�e t for high luminosity.The default jet �nder algorithm builds jets from ells not in the lusters, lusters and non-isolated muons.

122 6. ATLFAST: the Fast Simulation

Figure 6.5: Exe ution order of the JetMaker algorithms.6.3.4 Missing transverse energyThe missing transverse energy (ETmiss) is al ulated by summing up thetransverse momenta of identi�ed isolated photons, ele trons and muons,jets, and non-isolated muons not added to any jet luster. Those transverseenergies deposited in ells that were not used for luster re onstru tion arealso in luded in the total sum and they are smeared a ording to the sameenergy resolution fun tion that was applied in the ase of jets.6.3.5 AtlfastB Algorithm for jet energy alibration and mis-taggingAtlfastB Algorithm is the new version in ATHENA-C++ of the old ATLFAST-Fortran pa kage. It provides us a omplete treatment of jets in Atlfast-ATHENA, doing mainly the next taks:� performing jet energy alibration and� omputing eÆ ien ies for � , b and jet tagging and reje tion6.3.6 Jet energy re alibrationThe e�e t of the energy loss outside the one is orre ted using a pjetT -dependent alibration fa tor al ulated as an average, namelyKjet = ppartonT =pjetT ,were ppartonT denotes the transverse momentum of the parton whi h initiatedthe jet (before FSR). The set of alibration fa tors, separately for b-jetsand light-qurk jets, is provided in the supplementary pa kage ATLFAST-B. This alibration is pro ess independent, however, it might be optimiseddepending on the pT average of the iniating partons.

6.3. ATHENA-Atlfast organization 1236.3.7 Tra k re onstru tionThe tra k re onstru tion is provided for harged and stable parti les insidethe Inner Dete tor overage. A tra k is des ribed by the following helixparameters.� d0 - impa t parameter� z0 - proje tion of the impa t parameter onto the z axis� ot(�) - theta is the angle of the parti le tra k with at the origin� q=pT - harge / transverse momentum� r0 - radius of urvature of the helix� �0 - azimuthal angleThese re onstru ted tra k parameters are smeared with parametrisationfrom Inner Dete tor studies. Parametrisation for muons, pions (in ludingtails) and ele trons (in luding bremsstrahlung) as well as the respe tive re- onstru tion eÆ ien ies, are available.

124 Referen es:Referen es:[1℄ ATLAS Collaboration, ATLAS Dete tor and Physi s Performan eTe hni al Design Report CERN/LHCC/99-14, ATLAS TDR 14 (1999).[2℄ C++ version of Atlfast in Athena,http://www.hep.u l.a .uk/atlas/atlfast[3℄ E.Ri hter-Was, ATLFAST 2.0 A fast simulation pa kage for ATLAS,ATLAS Note ATL-PHYS-98-131 (1998)[4℄ E.Ri hter-Was, Do umentation of the algorithms for fast simulation ofATLAS dete tor (working do ument), June, 2000[5℄ Getting start with ATLFAST++, in http://root. ern. h/root[6℄ P. Sherwood, ATlfast introdu tion, Software Tutorial 5 Mar h 2004[7℄ Athena User and Developer Guide v.2.0 & Releaseshttp://atlas.web. ern. h/Atlas/GROUPS/SOFTWARE/OO/ar hite ture/General/[8℄ T.Sjostrand, Comput. Phys. Commun. 82 (1994):, T.Sjostrand et al,Comput. Phys. Commun. 135 (2001) 238; T.Sjostrand, L. Lonnbladand S Mrenna PYTHIA 6.2 - Physi s and Manual, [online℄ hep-ph/0108264, august:2001. Available from: http://weblib. ern. h/.[9℄ http://atlas.web. ern. h/Atkas/GROUPS/SOFTWARE/OO/tools/ vs-server.html; http://www. vshome.org[10℄ http://www. mtsite.org[11℄ http://proi-gaudi.web. ern. h/proi-gaudi[12℄ Gaudi Data Pro essing Appli ations Framework, Developers GuideCorresponding to Gaudi release v9, De 2001

Chapter 7Jet Algorithms in ATLAS7.1 From partons to re onstru ted jetsThe de�nition of a jet is not unique and the orresponden e betweenthe parton energy and its dire tion with the measured jet hara teristi s isin uen ed by many e�et s (see �g. 7.1) that have to be onsidered from thevery beginning of the parton produ ed in the hard-s attering pro ess[2℄[3℄:� Fa tors related to physi s,- Fragmentation- Initial (ISR) and Final state radiation (FSR)- Underlying Events- Minimum Bias events (ATLAS high luminosity)1� Fa tors related to dete tor performan e- Ele troni noise2- Magneti �eld3- Di�erent alorimeter response to harged and neutral hadrons(non-linearity)- Lateral shower size, granularity (losses outside the one, two jetseparation, � jet identi� ation)- E�e ts of dead material and ra ks between alorimeters- Longitudinal leakeage (very high pT jets)1The e�e t of the Minimum Bias events are �0.5 GeV in a tower ��x��=0.1x0.1, andaround 3.5 GeV (14 GeV) in a one of dR=0.4 (0.7) (with ele troni noise in luded).2The ele troni noise e�e t in ATLAS is around 200 MeV in a tower ��x��=0.1x0.1and around 0.7 GeV (1.4 GeV) in a one of dR=0.4 (0.7).3The pT uto� is aplied to remove the harged parti les that keep around inner dete torand not get the alorimeter. In ATLAS the pT uto� is 0.5 GeV.125

126 7. Jet Algorithms in ATLAS- Lateral shower size, granularity and ele troni noise, related tothe performan e of the dete tor, whi h an be optimised.

Figure 7.1: The orresponden e between the parton energy and its dire tion with themeasured jet is in uen ed by many physi s and dete tor e�et s.The representation of jets in the dete tors (espe ially alorimeters) showsa more or less severe distorsion of the original orrelations due to dete tore�e ts (shower spread, signal u tuations, ineÆ ien es...). It implies thatjets at the dete tor level are mu h less well de�ned that at the orrespondinggeneration at parti le level. That means that the role of the re onstru tionis very important.To understand all those e�e ts, it is useful to have a ess to di�erentjet algorithms[8℄ both in the framework of the fast simulation programATLFAST[2℄[3℄ and of the detailed simulation GEANT[11℄. Many jet al-gorithms have been used in past experiments and new ideas to ope withthe spe i� environment of a high luminosity hadron ollider like LHC may ome up.

7.2. Role of Jets in LHC Physi s 1277.2 Role of Jets in LHC Physi sIn the study of physi s hannels, jets are used in many di�erent ways[2℄:- in the re onstru tion of resonan es su h as W ! jj, Z ! b�b ...- in measuring jet multipli ity and total jet energy in SUSY sear hes- for jet vetoes in the entral region down to low pT of �15 GeV forba kground reje tion- for jet tagging in the forward region- in QCD studies.Spe i� physi s analyses may put emphasis on di�erent requirementssu h as ontrolling the energy s ale rather than a hieving the best eÆ ien yor the best resolution. Minimum Bias events at high luminosity will restri tthe area of the alorimeter over whi h the jet energy an be integrated,hen e the optimum ` one' size will be di�erent for di�erent luminosity on-ditions. Physi s e�e ts su h as �nal state radiation or olour re ombinationin fragmentation are hannel dependent. Hen e, there is no unique opti-mum strategy for jet re onstru tion, and the eÆ ien y and alibration willdepend on the algorithm, the level of Minimum Bias events and the physi s hannel.7.3 Jet MeasurementJet measurement an be broadly divided in three steps:� Jet Re onstru tion : Energy deposit in the alorimeter is lusteredby jet re onstru tion algorithm. All jet �nders are based on the idea ofre-establishing the kinemati hara teristi s of original partons (quarksand gluons) that still are kept in the �nal parti le whi h form the jets,using loseness in dire tion: one algorithms[4℄ or relative tranversemomentum : KT algorithm[17℄[18℄, both with their own advantagesand disadvantages: hoi e of distan e s ales, signal/ba kground opti-mization, theori al un ertainties...� Energy Calibration : Energy of a jet is alibrated to take intoa ount:- the fa t that the ATLAS alorimeters are non- ompensated, whi himplies that re onstru ted energies depend on unknown parti le omposition of the jet.

128 7. Jet Algorithms in ATLAS- the existen e of dead material in the dete tor, wi h gives pla eto some energy missing.- the e�e t of the magneti �eld over the harged parti le traje -tory, whi h originates that parti les with very small transverseenergy do not rea h the alorimeters and keep turning inside theinner dete tor, et � Flavour identi� a ion : The �nal step is the tagging of the quarkswhi h form the initial partons, in other words, try to identify their avour : b-tag, �-tag, et .At hadron olliders[2℄, the most prominent signature for a hard s at-tering pro ess taking pla e is the produ tion of parti les with a large totaltransverse momentum, i.e. the jets. The measurement of jets allows to draw on lusions about the hard s attering pro esses. To do so one has to takeinto a ount the evolution of the partoni system from the hard s atteringto the observed set of hadrons. This evolution in ludes:- parton showering: the reation of the additional parton, typi ally withde reasing transverse momenta- fragmentation: of oloured partons to the olourless hadrons- short lived parti le de aysbut also in ludes:� the e�e ts of the underlying event� multiple intera tions in a single bun h rossing7.3.1 Experimental aspe ts of the jet energy re onstru tionThe sample of jet re onstru tion[2℄ used are all 2!2 pro es from theQCD jets generated by PYTHIA 6.2[18℄. The energy deposited in the sensi-tive parts of the various alorimeter ompartments is �rst onverted to totalenergy using the ele tromagneti (EM) s ale. The various alorimeters havedi�erent degrees of non- ompensation and hen e a di�erent response to the harged hadrons jet omponent. Any re onstru tion algorithm will have toapply additional weights to take that e�e t into a ount.In addition, the energy loss as a fun tion of � is di�erent for the neutraland harged hadron omponents od the jets (see �gure7.2). Due to thewidth of the jets, the impa t of the dead material in the verti al ra k atj�j � 1 and of the orners of the ryostat walls at j�j � 1.45 are merged anda�e t a broader region than in the ase of single parti les.

7.4. Jet Algorithm 129

Figure 7.2: The energy loss of parti les depends on the polar angle (pseudorapidity).7.4 Jet AlgorithmJets are not learly de�ned objets like elementary parti les, but rather followfrom de�nition whi h is not unique. The de�nition of jets[2℄ depends on theirinternal stru ture. Thus, it is importan to provide dire t measurements of it.The orresponden e between parton energy and dire tion, and the measuredjet hara teristi s is in uen ed by many fa tors:- the absolute alorimeter alibration.- the jet dire tion and the mass determination- the jet hadronization s heme: parton fragmentation- the quality of the dete tor simulation- the �nal state radiation- the jet algorithm itselfTo understand all those e�e ts, it is useful to apply di�erent jet algo-rithms. Jet algorithms start from a list of \parti les" that we take to be alorimeter towers or hadrons at the experimental level. Algorithms asso- iate lusters of these parti les into jets, su h that the kinemati al propertiesof the jets (e.g. momenta) an be related to the orresponding propertiesof the energeti partons produ ed in the hard s attering pro ess. Thus thejet algorithm allows us to \see" the original partons (or at least their �n-gerprints) in the hadroni �nal state.Di�eren es in the properties of re onstru ted jets when going from theparton to the hadron or alorimeter level are a major on ern for a goodjet algorithm. Ea h parti le i arries a 4-momentum pmui, whi h we taketo be massles. The algorithm sele ts a set of parti les, whi h are typi allyemitted lose to ea h other in angle, and ombines their momenta to formthe momentum of a jet. The sele tion pro ess is alled the \jet algorithm"and the momentum addition rule is alled the \re ombinaton s heme".

130 7. Jet Algorithms in ATLASHistori ally one algorithms[21℄ have been the hosen jet algorithm forhadron-hadron experiments[11℄4. The other main approa h is based on lus-tering algorithms[14℄[15℄[16℄, e.g. the KT algorithm[17℄[18℄.7.4.1 Cone AlgorithmThe intuitive pi ture is that jets should be omposed of hadrons or partonsthat are, in some sense, nearby ea h other. The fundamental one jet ideais that nearness is de�ned in a simple geometri fashion: jets are omposedof hadrons or partons whose 3-momenta lie within a one de�ned by a ir lein the angular variables (�,�), where �= - ln tan(�=2) is the pseudorapidityand � is the azimuthal angle (see �g. 7.3).The lassi al \ one" algorithm builds a jet around a seed whi h is rep-resentative of the ore of the jet and identi�ed usually as the tower withhighest ET , where ET is transverse energy ET = Esin�. A one jet of ra-dius R onsist of all of the parti les whose traje tories lie in an area A = �R2of spa e.

Figure 7.3: In the one algorithm the jet is re onstru ted inside a one around the towerwith the highest ET .This algorithm has several variants[2℄. The most basi approa h onsistsof using the tower with the highest ET as the jet seed and building a onearound the seed. Cells belonging to the one are not available for subsequentjet �nding. The parameters are the EseedT ut, the one opening radius andthe minimumET of the jet (to prevent ex essive merging of noise and energynot asso iated with the hard s attering). Usually the entroid of the jet isre al ulated from the list of towers ontained in the one. This is the baselineused by ATLFAST.Intuitively we also expe t the jets to be aligned with the most energeti parti les in the �nal state and orrespondingly we expe t to be able to4Be ause these algorithms have easier alibration

7.4. Jet Algorithm 131identify a unique set of jets on an event-by-event basis. This uniquenessexpe tation is realized by identifying jets with stable ones. A stable onehas the property that the geometri enter of the one oin ides with theET weighted entroid of the parti les in the one5 (see �gure7.4).

Figure 7.4: Iterations of the position of the entroid of the luster and the orresponding one, until the one axis oin ides with the stable entroid.It is important to re ognize that jet algorithms involve two distin t steps:- The �rst step is to identify the onstituents of the jet, i.e., the list of alorimeter towers, hadrons or partons that have to be in luded in thestable one, i.e., the jet.- The se ond step involves onstru ting the kinemati properties thatwill hara terize the jet, i.e., determine into whi h bin the jet will5This approa h is obtained by iterating the position of the entroid of the luster andthe orresponding one, until the one axis oin ides with the stable entroid.

132 7. Jet Algorithms in ATLASbe pla ed. The simpli ity and intuitive appeal of the one algorithmjustify its wide spread usage at hadron olliders and it has proved tobe a very useful tool.

Figure 7.5: Cones will be split and the shared towers will be assigned to the losestproto-jet in (�,�) spa e.

Figure 7.6: If two protojets share more than 50% of the transverse energy of the lowerET protojet, the two jets are merged.Unfortunately, nothing prevents the �nal stable ones from overlapping.A single parti le may belong to two o more ones. As a result, a pro eduremust be in luded in the one algorithm to spe ify how to split (see �gure7.5) or merge (see �gure 7.6) overlapping ones. There are di�erent strate-gies for jet energy sharing or jet merging, i.e., based on the por entage oftransverse energy shared by the lower ET proto-jet. Proto-jets sharing afra tion greater than f (tipi ally f=50%) will be merged.Spe i� physi s analyses may put emphasis on di�erent requirementssu h as ontrolling the energy s ale rather than a hieving the best eÆ ien yor the best resolution. Minimum-bias events at high luminosity will restri tthe area of the alorimeter over whi h the jet an be integrated, hen e theoptimum \ one" size will be di�erent for di�erent luminosity onditions.

7.4. Jet Algorithm 1337.4.2 KT AlgorithmInspired by QCD, a se ond lass of jet algorithm, alled KT lustering al-gorithms, has been developed. These algorithms su essively merge pairsof \parti les" in order of in reasing relative transverse momentum. Theystart from the full set of �nal hadrons, approximated by the towers in the alorimeter, and pairs the \ losest" ones. They work as follow:- Compute for ea h pair (i,j) and for ea h parti le (i) the quantities:dij = min(PTi ; PTj )�R2D2 and di = (P 2Ti) (7.1)- Find the minimum of fdij ; djg = dmin- If dmin = di then it is alled a jet and is removed from the list- If dmin = dij removed pre luster i and j from the list and repla ethem with a new merged parti le em ij to give a singel jet by E-s hme:Eij = Ei +Ej and Pij = Pi + Pj- Iterate until all parti le are in jets. (see �g. 7.7)

Figure 7.7: The open arrows represent pre lusters in the event, and the solid arrowsrepresent the �nal jets re onstru ted by the KT algorithm. The six diagrams show su - essive iterations of the algorithm. In ea h diagram, either a jet is de�ned (when it iswell separated from all other pre lusters), or two pre lusters are merged (when they havesmall relative kT ). The asterisk labels the relevant pre luster(s) at ea h step.

134 7. Jet Algorithms in ATLAS

Table 7.1: Advantages and disadvantages between one algorithm and kT algorithm.Sin e a KT algorithm fundamentally merges nearby parti les, there is a lose orresponden e between jets re onstru ted in the alorimeter and jetre onstru ted from individual hadrons, leptons and photons. Furthermore,every parti le in an event is assigned to a unique jet. It implies that nomerging/spliting methods will be needed.On the other hand, these algorithms require looping many times over thetowers, whi h arry out more time onsuming. In table 7.1, one an see theadvantages and disadvantages between one algorithm and kT algorithm.However, there are diÆ ulties with the subtra tion of energy from spe -tator fragments and from pile-up of multiple hadron-hadron intera tions,sin e the KT jets have no �xed shape, pres riptions for dealing with theextra energy have been diÆ ult to devise.Variants of the KT lustering algorithm use di�erent merging riteria,and di�erent ways of ending the merging pro ess, for example applying a ut on the distan e or stopping at a ertain jet multipli ity.Figure 7.8: Comparison between one algorithm and kT algorithm.

7.4. Jet Algorithm 1357.4.3 MGS AlgorithmIn this ase, all towers are lassi�ed in order of de reasing ET . The �rsttower is assigned to the �rst luster, the next tower will be assigned to thesame luster or a new depending on the distan e �R = p(��)2 + (�')2.One parameter of the algorithm is the \resolution", the minimum distan ebetween two jets. All towers in the list are sequentially assigned to the losest luster or a new luster is started, the luster entroid being re-evaluatedea h time a tower is added.This me hanism provides automati ally energy sharing, while the shapeand size of the luster are not prede�ned. Optionally a �xed one size anbe required.7.4.4 Performan e of the jet algorithms (TDR Results)Results from a parti le level study using ATLFAST at low luminosity showthat the one algorithm with �R =0.7 has the best performan e in thatenergy range: the ratio of re onstru ted jet energy to parton energy is almostindependent of energy and lose to 1.The one algorithm with �R =0.4 shows losses varying from 10% at lowET to about 3% at 200 GeV. The KT and MGS algorithm shows a atterdistribution in ET but with an average loss of about 8%.The �gure 7.9 shows the ase of low luminosity without Minimum Biasevents while the �gure 7.10 represents the ase of high luminosity whereMB has been simulated with Pythia (equivalent to 25 su h events with alorimeter shaping fun tions).

Figure 7.9: Results from a parti le level study using ATLFAST at low luminosity (with-out Minimum Bias events) for one algorithm with �R =0.7 and �R =0.4 ompared withthe KT and MGS Algorithm.

136 7. Jet Algorithms in ATLAS

Figure 7.10: Results from a parti le level study using ATLFAST at high luminosity(where Minimum Bias has been simulated) for one algorithm with �R =0.7 and �R =0.4 ompared with the KT and MGS Algorithm.7.5 A tual Jet Re onstru tion in ATLASIn the a tual s heme of ATLAS there are 3 algorithms implemented for theJet Re onstru tion[30℄: �xed (seeded) one, seedless one, Kt;- �xed one. This algorithm use a �xed value for the radius of the one(typi ally �=0.7). It is a fast algorithm, but it is not infrared safe. Itwill be needed split and merge post-pro essing, as well as orre tionsof the loss of energy out side the one ( alled out-of- one orre tions),due to showering e�e ts (espe ially in the forward regions). On theother hand, we also must be arefull with the pile-up noise.- seedless one. This algorithm use as seed every ell, parti le et , soit implies that the algorithm will be very slow, but tha advantage isthat it is ollinear safe;- Kt. The performan e of this algorithm is prohibitive if it is used with alorimeter ells (�N ells33), but the hosen is preferred in ATLASafter the pre- lustering level (0.2x0.2 or so);All three algorithms show similar performan e features on simulated eventswithout noise and pile-up; Respe t to the number of jets above 10 GeV/ Pt in fully simulated SUSY events are about 5.6 (seeded one), 5.7 (Kt) and6.0 (seedless one), and the average transverse energy 114/118/126 GeV forseeded one/Kt/seedless one, respe tively. (see �g. 7.11);

7.5. A tual Jet Re onstru tion in ATLAS 137

Figure 7.11: Number of jets and the average transverse energy above 10 GeV/ Pt infully simulated SUSY events for Seeded one, Kt and Sedless.The in lusion of pile-up and ele troni noise introdu es interesting prob-lems: the jet onstituents ( alorimeter towers, ells) must have a valid 4-ve tor with E>0. It implies the needed of uts and the posibility of positiveenergy bias. Presently jet re onstru tion in noise and pile-up environmentis not well understood, espe ially for Kt [31℄;

138 7. Jet Algorithms in ATLAS7.6 Appendix 1: Jet Algorithms in CDFDuring Run I, CDF and D0 experiments used an iterative one jet algo-rithm to re onstru t jets in the �nal state from the energies measured in the alorimeters. In this algorithm, ones in the (�-�)-spa e are drawn aroundan initial list of seed towers with ET above �1 GeV, and proto-jets are om-puted from the energy and dire tion of the towers inside the ones. New ones are then de�ned around the proto-jet dire tions and the pro edure isiterated until a stable on�guration is a hieved. Finally, overlapping jetsare merged or separated following a pure experimental pres ription whi hdepends on the relative ontribution of the overlap region to the jet energies.In omparisons with �xed-order pQCD predi tions, it has been repeat-edly pointed out that the Run I jet algorithm presents severe theoreti aldiÆ ulties related to the fa t that it does not preserve the ne essary in-frared and ollinear safety (see �g. 7.13 and �g. 7.14). Several stud-ies has been performed to establish a better jet algorithm for Run II atTevatron[22℄[23℄[24℄.The KT algorithm, where parti les are lustered a - ording to their separation in transverse momentum (inspired by pQCDshower evolution), has been proposed as the theoreti ally preferred algo-rithm for future hadron-hadron studies. Although the algorithm has beenused with great su ess by LEP and HERA experiments, early studies atTevatron would suggest that the presen e of a signi� ant underlying eventa tivity and multiple intera tions would make theKT algorithm not suitablefor pp ollisions.Alternatively, improved one-based jet algorithms have been developed.In parti ular, the MidPoint algorithm introdu es additional seeds at themid-points of ea h pair of parti les to highly redu e the sensitivity to softand ollinear emissions. This was a hieved by adding seed lo ations for trial ones between pairs of stable seed-based ones. It works as follow:- Iterate ones starting at ea h seed tower- Put seed inMidPoint (�-�) for ea h pair of stable ones whose enterspi and pj separad by less than 2R- Iterate a one starting at the MidPoint pi + pj- Split or merge overlapping onesWith this algorithm ross se tions better behaved and al ulable in pQCD... but perhaps there will be small merging/splitting dependen e.

7.6. Appendix 1: Jet Algorithms in CDF 139

Figure 7.12: The MidPoint algorithm split or merge overlapping ones whose enters piand pj separad by less than 2R.The performan e of the di�erent jet algorithms will be explored duringthe Run II at Tevatron as testing ground for future LHC[3℄[4℄ (mainly in thegeneral pourpose dete tor CMS[25℄[26℄ and ATLAS[21℄[27℄[28℄[29℄) analysesand strategies.Figure 7.13: An ilustration of infrared sensitivity in one algorithm. In this example,jet lustering begins around seed parti les, shown here as arrows with length proportionalto energy. The presen e of soft radiation between two jets may ause a merging of thejets that would not o ur in the absen e of the soft radiation.Figure 7.14: An ilustration of ollinear sensitivity in jet re onstru tion. In this example,the on�guration of the left fails to produ e a seed be ause its energy is split among severaldete tor towers. The on�guration on the right produ es a seed be ause its energy is morenarrowly distributed.

140 Referen es:Referen es:[1℄ ATLAS Collaboration: ATLAS Dete tor and Physi s Performan eTe hni al Design Report Vol 1, CERN/LHCC/99- 14, 25 May 1999[2℄ ATLAS Collaboration: ATLAS Dete tor and Physi s Performan eTe hni al Design Report Vol 2, CERN/LHCC/99- 15, 25 May 1999[3℄ M. Bosman, Jets and ET miss at the LHC, presentation in Calor2000Conferen e of Calorimetry on behalf of ATLAS CMS ollaborations.[4℄ Ian C. Bro k. Jets at the LHC. 04/02/05[5℄ C++ version of Atlfast in Athena,http://www.hep.u l.a .uk/atlas/atlfast[6℄ E.Ri hter-Was, ATLFAST 2.0 A fast simulation pa kage for ATLAS,ATLAS Note ATL-PHYS-98-131 (1998)[7℄ Geant4 Users do uments:http://wwwasd.web. ern. h/wwwasd/geant4/G4UsersDo uments//Overview/html/index.html[8℄ Bosman, M; et al. Jet Finder Library: version 1.0. ATL-SOFT-98-038;[9℄ ATLAS Collaboration:ATLAS Calorimeter Performan e,CERN/LHCC/96-40, ATLAS TDR 1, (1996).[10℄ T.Sjostrand, Comput. Phys. Commun. 82 (1994):, T.Sjostrand et al,Comput. Phys. Commun. 135 (2001) 238; T.Sjostrand, L. Lonnbladand S Mrenna PYTHIA 6.2 - Physi s and Manual, [online℄ hep-ph/0108264, august:2001. Available from: http://weblib. ern. h/.[11℄ G. Sterman and S. Weinberg. Jets from Quantum Chromodynami s.Phys. Rev. Lett. 39, 1436 (1977).[12℄ A. Gupta. Jet Re onstru tion in Athena. Atlas Calorimeter Energy Cal-ibration Workshop, Ringberg Castle. July 2002.[13℄ C. Iglesias. Jet Re onstru tion, Thursday Meetings, IFAE,Bar elona,2003[14℄ T. Sjostrand, Comp. Phys. Comm. 28 227 (1983)

Referen es: 141[15℄ Dokshitzer, Yu L ; Leder, G D ; Moretti, S ; Webber, B R . Better JetClustering Algorithms. hep-ph/9708 (1997) 001[16℄ S. Moretti, L. Lnnblad and T. Sjstrand. New and Old Jet ClusteringAlgorithms for Ele tron-Positron Events. hep-ph/9804296 (1998) 001[17℄ M. Seymour, Zeit. Phys. C62 127 (1993).[18℄ S.D. Ellis and D.E. Soper, Phys. Rev. D. 48 2160 (1993).[19℄ Stenzel, H and Tapprogge, S. Prospe t of Studies with QCD Jets inATLAS, ATL-PHYS-2000-003[20℄ Tapprogge, S. Experimental aspe ts of QCD studies at the LHC, ATL-PHYS-99-012,[21℄ A.P Cheplakov, R, Saint-Denis and AS. Thompson. Jet alibrationfor the �xed one algorithm in ATLFAST. ATL-PHYS-2003-010; ATL-COM-PHYS-2003-009[22℄ Gerald C. Blazey et al., Run II Jet Physi s: Pro eedings of the Run IIQCD and Weak Boson Physi s Workshop, hep-ex/0005012, May 2000.[23℄ M. Martinez. Jet Algorithms in CDF, Talk at the First RTN-Workshop:The 3rd generation as a Probe for New Physi s. Rome, De . 17th 2002.[24℄ R. Lefevre, M. Martinez and O. Norniella. Measuring In lusive JetCross Se tion using KT algorithm at CDF RunII. 3rd RTN Workshop,De ember 2003, Bar elona.[25℄ A. Nikitenko, Jet Physi s with CMS, Workshop on Hard Probes inHeavy Ion Collisions at the LHC 13 O t 2001. CERN[26℄ S.Hoppe. Jet Algorithms 1. University of Bonn Jetseminar, Bonn, 15.O t. 2004[27℄ J. Sjlin, Jet re onstru tion in the ATLAS Barrel Calorimeter. ATL-TILECAL-2000-009[28℄ R. Lefvre and C. Santoni. A study of the jet energy re onstru tion.ATL-PHYS-2001-011;[29℄ R. Mehdiyev, ZV. Metreveli,P. Nevski and D. Salihagi . Test of Slid-ing Window Algorithm �r Jets Re onstru tion in ATLAS Hadroni Calorimeters. ATL-CAL-99-002;

142 Referen es:[30℄ P. Lo k, Jet Re onstru tion in ATLAS Status and Comments, presentedat Standard Model SW Meeting, ATLAS WEEK, June 2003[31℄ Talks presented by A. Gupta and D. Constanzo at the ATLAS Physi sWorkshop Athens 2003

Chapter 8Energy Flow in Atlfast8.1 Introdu tionThe performan e of Energy Flow algorithms will be limited by the overlapof parti les. In this analysis1, the maximum potential gain in ET resolutionof the Energy Flow algorithm at LHC with the ATLAS dete tor is estimatedtaking into a ount only shower shape e�e ts in a simpli�ed way2, using thefast simulation and re onstru tion pa kage of ATLAS[1℄: Atlfast[2℄[3℄. Theimpa t of Underlying event and Minimum bias events at low luminosity hasbeen also onsidered.8.2 Aim of this hapterThis study is a �rst step in the exploration of the potential of the EnergyFlow algorithm at LHC with the ATLAS dete tor. The aim of the EnergyFlow Algorithm is to make optimal use of the dete tor information om-bining the measurement of the energy deposition in towers or ells of the alorimeter with the re onstru ted tra ks in the entral dete tor to improvejet energy resolution and missing transverse energy, EmissT .Here we report on a study of the omposition of jets (parti le densities,PT spe tra and nature, et ) at parti le level as well as the e�e ts of Under-lying event and Minimum bias events at low luminosity. These studies havebeen arried out in order to better understand the environment and the im-portan e of the overlap between harged and neutral parti les when doing1This analysis has been published as internal note of the Software Group of the ATLASexperiment as ATL-SOFT-INT-2005-001 with the title: "Study of jet omposition atparti le level and its impli ations for Energy Flow algorithms".2This parti le level study should be followed up by full simulation of dete tor response,to obtain a realisti estimate of the energy resolution that an be rea hed by a study inATLAS with an Energy Flow approa h. 143

144 8. Energy Flow in Atlfastlater full simulation and atta king the hart of the problem of luster-tra kasso iation and energy substra tion.8.3 Energy Flow Con eptThe Energy Flow algorithm was introdu ed for the �rst time in theALEPH[4℄ dete tor in 1994-1995, and it was extensively developed in thefour experiments at LEP[5℄. The re onstru tion of individual parti les( harged or neutral) in LEP dete tors was very diÆ ult be ause of oarse alorimeter granularity, small magneti �eld, la k of longitudinal segmenta-tion, and additional dead material in front of or inside the alorimeter.Nowadays, the Energy Flow te hnique has been improved by experi-ments, su h as CDF[6℄ and D0 (Tevatron, Run II), H1[7℄, ZEUS[8℄ andTESLA[9℄.The �gure 8.1 shows that a substantial improvement in the jet energyresolution was obtained for a sele ted sample of events from CDF Run Idata taken at the Tevatron, using an energy- ow approa h optimised forthe spe i� features of the CDF alorimeter on a sample of well-balan edphoton-jet events[10℄. The jet energy resolution is improved from 15% to12% for a jet transverse energy of about 50 GeV.

Figure 8.1: Improvement in jet energy resolution obtained as a fun tion of jet transverseenergy in well-balan ed photon-jet events for the CDF dete tor at the Tevatron. Alsoshown is the jet energy resolution expe ted in ATLAS from detailed simulation doen forthe ATLAS TDR [2℄.

8.3. Energy Flow Con ept 145The expe ted ATLAS jet energy resolution is also shown in �g. 8.1, asobtained using only the alorimeter information. It will learly be a mu hmore hallenging task to e�e tively bene�t from energy- ow algorithms inthe ase of the ATLAS alorimeter given its ex ellent energy resolution oftypi ally 8-10% for a jet transverse energy of 50 GeV.Preliminary results based on existing software tools (ele tromagneti luster �nding) and on �rst attempts at repla ing ell energies belongingto harged hadrons by the measured tra k momenta are being developpedin the general purpose dete tors of LHC, CMS[11℄ and ATLAS2[12℄ (eitherin full simulation[13℄ or fast simulation[14℄).Around 2/3 of the jet energy omes from harged parti les (mainly pi-ons and kaons). However lassi al jet re onstru tion algorithms only use alorimeter energy information. The on ept of the Energy Flow algorithmis to exploit the measurement of harged tra k momentum instead of energy.For low momentum harged parti les, the tra king error is mu h smallerthan the alorimetri energy error[15℄. A simple al ulation of the relationbetween the pT resolution of the inner dete tor and the energy resolutionof the Hadroni alorimeter of ATLAS an be done. The resolution of thetra king system, in the general ase, is managed in ATLAS TDR and isgiven by the formula: �( 1pT ) = 0:36 � 13PTpsin � (8.1)where the tra k resolution appears in TeV �1 and the PT in GeV. As we aregoing to study only the entral barrel ase, we an assume � = 0 and sin�= 1, so for this parti ular ase, the relative resolution, �(pT )pT , in terms of per ent, %, an be written as follows:�(PT )PT = 0:036%pT � 1:3% (8.2)On the other hand, the energy resolution of the hadroni alorimeter in the entral barrel area for the ase of the jets is given by:�(E)E = 50%pE � 3% (8.3)

146 8. Energy Flow in Atlfast

0

2

4

6

8

10

12

14

0 50 100 150 200 250 300 350 400Figure 8.2: Transverse momentum (PT ) in the Inner Dete tor and energy resolution inthe Hadroni Calorimeter as fun tion of the parti les energy in the Barrel (at � = 0).So, for one pion of 10 GeV the tra king resolution, 1:3%, is mu h smallerthan the energy resolution, 16% (see �g. 8.2). This behaviour appearsfor low momentum and it implies that it should be interesting to use theEnergy Flow algorithm for pT values smaller than 140 GeV, value whereboth resolutions are equal.The basi idea of the algorithm is to substitute the random u tuations ofenergy in the alorimeter by the well measured harged parti le momentum,in order to obtain better resolution in jet energy.In this analysis we use alorimeter energy resolution for neutral hadronswhile we use tra ker resolution for harged hadrons. We �rst lo alize the ex-pe ted energy deposit in ele tromagneti (EM) and hadroni (HAD) lusterby the harged hadrons in order to remove it and substitute its ontributionto the resolution by the measurement of the momentum.The use of the tra k momentum improves the resolution only if the luster is isolated. Then, if the tra k shares a luster with a neutral parti le,the gain in resolution from tra k will be limited by loss of resolution of theremaining luster. So, the eÆ ien y of the algorithm is limited by the overlapbetween neutral and harged parti les in the ells of the alorimeter, e�e tsthat we will study in more in detail.The method is simple but however its realization is hallenging: it re-quires building the parti le ID asso iated with the tra k. This starts runninginto diÆ ulties in a high tra k multipli ity environment and oarse alorime-ter granularity: it requires use of advan ed lustering algorithm apable ofeÆ ient isolation of the individual showers, together with an energy deposi-tion model.

8.4. Parameterization of the energy in Atlfast 1478.4 Parameterization of the energy in AtlfastThis study is performed with the parti le level fast simulation pa kage de-veloped by the ATLAS omputing ommunity, named Atlfast. This pa kageis by de�nition too simplisti and limits the validity of the �nal results, butthey an be used as input to full simulation studies.In Atlfast there is no detailed simulation of the parti le showers in the alorimeter3, neither of the harged tra ks in the inner dete tor. In addition,this fast simulation pa kage smears luster and jets rather than their on-stituent ells4. So in Atlfast, the dete tor-dependent parameters are tunedto what is expe ted for the performan e of the ATLAS dete tor from fullsimulation and re onstru tion.There is only a parameterization of the hadroni alorimeter energy reso-lution, as well as a reasonably a urate parameterization for photon, ele tronand muon energy or momentum resolution. A simulation of the eÆ ien yin the Inner dete tor and the re onstru tion of the helix tra k parameters isalso provided with separate parameterizations on the resolutions for muon,ele tron and pion tra ks.The parameterizations used in Atlfast were derived from full simulationstudies:� Resolution in EM Calorimeter (photon and ele tron andidatesare smeared with this parameterization), for barrel (j�j < 1:4) and forend aps (j�j > 1:4) regions, respe tively:�(PT )PT = 0:245pT � 0:007 (8.4)�(PT )PT = 0:306 � ((2:4 � �) + 0:228)pT � 0:007 (8.5)� Resolution in the HAD Calorimeter (hadrons are smeared withthis parameterization) for entral barrel (j�j < 3) and for extendedbarrel (j�j > 3) regions, respe tively:�(E)E = 0:5pE � 0:03 (8.6)3Ex epting the FastShower pa kage done by K. Mahboubi et al. (Mainz) whi h an beused in Atlfast to give transverse shower shape parameterization at a granularity of 0.1 x0.14Ele tromagneti and hadroni ells in Atlfast have the same granularity ��x�� = 0.1x 0.1, while in the real ATLAS dete tor EM ells have lower size ��x�� �0.025 x 0.025

148 8. Energy Flow in Atlfast�(E)E = 1:0pE � 0:07 (8.7)� Resolution in the Inner Dete tor (parameterizations for muon,ele tron and pion tra ks), in the simplest ase:�(PT )PT = 0:00036pT � 0:013 (8.8)and in the ase where the tra k resolution depends on � values:�(PT )PT = 0:0005(1 + j�j 107000 )pT � 0:012 (8.9)Only when the high luminosity option is sele ted, pile-up events are in ludedin the parameterization in a simple mode as a deterioration of the energyresolution. Anyway, this analysis will be done at low luminosity, so pile-upevents are not in luded.So, as there is no detailed simulation of the showers in the alorimeterneither of the tra ks, only some physi al aspe ts like the overlap an be stud-ied by Atlfast. When the in uen e of the behaviour of the hadroni showeris bigger it will be needed to ontinue the analysis with Full Simulation[16℄where the dete tor response is modelled in a very a urate way, making useof the GEANT pa kage[17℄8.5 Generation with PYTHIA 6.2For this analysis we have generated 1000 events of QCD jets, applying thefollowing onditions in Pythia[18℄ program:� generation of jets with di�erent range of transverse momentum: 20-40GeV, 40-80 GeV, 80-160 GeV, 160-320 GeV, 320-640 GeV and 640-1280 GeV, to provide adequate statisti s in the full range of ET 5,showing the variation of the improvement in the resolution with theenergy.� In a �rst step, the studies have been done without in luding neitherUnderlying Events nor Minimum bias e�e ts. Later, in se tions 8.9.3and 8.9.4 8.9.4 and 8.9.4, the e�e ts of the additional low pT parti- les that they indu e are investigated and their ontribution to thedeterioration of the resolution.5The separation between the values is bigger and bigger be ause the probability tohave jets at that energies is smaller and smaller, due to the shape of the distribution ofthe pT of the jets.

8.6. Re onstru tion and Simulation with Atlfast 149� ISR and FSR, initial and �nal state radiation, are in luded in theanalysis be ause they have in uen e in the �nal dire tion of the jet.� �parton <5.0, i.e., partons oming from hard s attering are generatedonly inside the alorimeter overage.8.6 Re onstru tion and Simulation with AtlfastFor the re onstru tion of the jets of quarks and gluons we have used in thiswork the Release 6.2.0 of the ATHENA-Atlfast pa kage, and the following onditions have been sele ted in the AtlfastStandarOptions �le:� Jets are re onstru ted using the Cone algorithm for two di�erent valuesof the radius �R= 0.4 and 0.7, where �R=p��2 +��2. We will seehow the improvement in the resolution hanges with the radius.� A minimum value of the PT of the jet is required in order to preventex essive merging of noise and energy not asso iated with hard s at-tering. We take di�erent PminT values depending on the radius of the one: for �R=0.4, PminT = 15 GeV is taken, while for �R=0.7, PminT =20 GeV is taken. These values for the PminT are hosen su h that thenumber of jets be de reased and stabilized (see �g. 8.3).� Finally, jets are generated only into the inner dete tor overage (j�jetj <2:5) be ause later on we will use in ombined way alorimeter andtra king information. We apply j�jetj <2.0 in order to assure the om-pleted re onstru tion of the jet from the one with R=0.4 and 0.7.

Figure 8.3: Multipli ity of jets for the two radius of the jet one: �R=0.4 and 0.7, andfor the ET jet ranges of 20-40 GeV, 40-80 GeV and 80-160 GeV. The best PminT ut for�R=0.4 is �15 GeV and for �R=0.7 is 20 GeV, values for whi h the number of jets hasde reased and stabilized.

150 8. Energy Flow in AtlfastIn the table 8.1 appear the numbers of generated QCD jets for the dif-ferent ases after applying all these sele tion riteria.Number of QCD jets in Atlfast:20-40 40-80 80-160 160-320 320-640 640-1280�R =0.4 649 1628 2276 2993 3666 4282�R =0.7 288 1414 2091 2755 3369 4009Table 8.1: Numbers of generated QCD jets for the di�erent ases after applying thesele tion riteria.8.7 Parti le level omposition of the jetsWe re onstru ted the jet energy deposited in the alorimeter summing theET of the parti les that fall inside the one of R=0.4 or 0.7 entred at�jet-�jet oordinates.Only stables parti les are onsidered. These parti les are mainly: a fewtens of harged hadrons (�� and k�), a similar amount of photons ( omingfrom �0 de ay into ), a lesser extent neutral hadrons(klo and neutrons)and very few leptons (e�, �� and neutrinos). The �g. 8.4 shows an exampleof the re onstru tion of jets with R=0.4 or 0.7 with the where the di�erent olor bin represent the di�erent stable parti les whi h form the jet.

Figure 8.4: Re onstru tion of the jet from stable parti les inside a one of radios 0.4and 0.7 after passing a ertain sele tion.Moreover, we apply the following sele tion riteria, before obtaining the�nal results and plots:� a minimum value of theET of the harged parti les is required, ET >0.5GeV, in order to remove the parti les with very small value ofET whi hdo not rea h the alorimeters and loop inside the inner dete tor avity.

8.7. Parti le level omposition of the jets 151� only sele ted parti les deposited in the alorimeter into the � values ofthe inner dete tor overage (j�jetj < 2:5) are taken into a ount, dueto the ombined used of alorimeter and tra king measurements.

Figure 8.5: View of the ATLAS Inner dete tor and Calorimeters system. The overagein of the Inner Dete tor is j�j < 2:5.8.7.1 Number of parti les forming the jetsThe table 8.2 shows the number of sele ted stable parti les for various asesof ET range. Some initial observations an be made:� there are mainly harged hadrons and photons� the amount of leptons (e�, �� and neutrinos) is negligible (<0.5%).� the multipli ity of the harged and neutral parti les is similar�R=0.4 Total Part Charged Had Neutral Had Photonsin jet per jet % per jet % per jet %40-80 GeV 13.2 6.17 46.6 0.94 7.1 6.02 45.580-120 GeV 17.2 8.17 47.1 1.11 6.4 7.92 45.7160-320 GeV 20.9 9.97 47.3 1.30 6.1 9.63 45.7�R=0.7 Total Part Charged Had Neutral Had Photonsin jet per jet % per jet % per jet %40-80 GeV 13.4 6.39 47.6 0.95 7.0 6.02 45.080-120 GeV 17.6 8.43 47.1 1.13 6.3 8.17 47.5160-320 GeV 21.7 10.32 47.3 1.34 6.1 9.98 45.9Table 8.2: Number of sele ted stable parti les into jets in various ranges of ET for�R=0.4 and 0.7.

152 8. Energy Flow in AtlfastIf we ompare the results for di�erent values of ET range of the sameradius (see table 8.2):- The number of parti le per jet in rease with the transverse energy6- A similar ontribution from harged hadrons (�� and k�) and photons(�0 ! ) is obtained.Also if we ompare the numbers of parti les for the two values of �R wesee similar values at the di�erent ET ranges.8.7.2 Jet energy in the alorimeterThe ET deposited by sele ted stable parti les has been analysed .The meanvalue of the total ET of jets re onstru ted from MC Truth parti les and byAtlfast is similar, as one an see in �g.8.6 for the ase of jets with 40-80GeV and �R = 0.4. It means that the re onstru tion of the jets from thesele ted stable parti les in the one has been well done.

Figure 8.6: Total ET of re onstru ted jets from parti les and from Atlfast for �R=0.4and Pt jet 40-80 GeV.Similarly, in the tables 8.12 the di�erent values of ET deposited by thestable parti les are shown for various ases of ET range. We observe that:� The ontribution of the ET deposited by harged hadrons is the longest,about 2/3 parts of the total.� The leptoni ontribution (e�, �� and neutrons) is negligible (<1%).6Two e�e ts may play a role. As the energy of the parton in reases more parti les aregenerated during the fragmentation. At the same time, they get more ollimated.

8.7. Parti le level omposition of the jets 153�R=0.4 Charged Had Neutral Had PhotonsET per jet % ET per jet % ET per jet %40-80 GeV 22.6 61.2 4.6 12.5 9.2 25.280-120 GeV 40.4 61.3 7.8 11.8 16.9 25.6160-320 GeV 69.1 61.4 13.1 11.9 28.9 25.7�R=0.7 Charged Had Neutral Had PhotonsET per jet % ET per jet % ET per jet %40-80 GeV 24.2 61.1 4.9 12.4 9.9 25.280-120 GeV 42.6 61.3 8.2 11.8 17.8 25.7160-320 GeV 73.5 61.4 14.0 11.7 30.8 25.7Table 8.3: ET (in GeV) of sele ted stable parti les into jets for various ranges of ET for�R=0.4 and 0.7.Again, if we ompare the results of transverse energy deposited by theparti les inside the one for di�erent ET ranges with the same � R (seetable 8.3), we an draw several on lusions:� The ET deposited by parti les in rease as the ET range of jet is bigger.� The ontribution from harged hadrons is more than twi e that fromphotons, as expe ted sin e the gammas ome from �0 de ay.� The per entage of ea h type of parti le is onstant (it must be inde-pendent of �R, it only depends on physi s).Finally, omparing the ET deposited by parti les for the two radii �Rof the re onstru ted jet one:� The results for �R=0.7 are similar to that for �R=0.4, in the two ases the ET of the parti les in rease as the ET of the jet is bigger.� The ET deposited for the parti le per jet is bigger in �R=0.7 than in�R=0.4, as �R in reases the proportion of the initial parton energyinside the one is bigger.� The energy sharing between parti les does not hange for the two oneradii.

154 8. Energy Flow in Atlfast8.7.3 Jet ET fra tion arried by harged hadronsIn view of the previous tables and numbers, we an extra t two importantresults about harged hadrons:- Their number is � 47% of the total of parti les.- Their transverse energy deposited is � 60% of the total energy.8.8 Study of the overlapping of parti lesWe are going to apply the Energy Flow Algorithm to the harged hadrons,but not to all, only to the harged hadrons hitting alorimeter ells withoutoverlap with neutral parti les. So, we need to:- de�ne the alorimeter ell hit by the parti les- do a ell lassi� ation based on the type of parti les hitting it.A grid of 81 \ ells" around the entral oordinate �jet-�jet of the re on-stru ted jet is de�ned, as one an see in the �g 8.7. These \ ells" orrespondto the energy proje ted in the tower with a granularity �� x �� = 0.1 x0.1, as in the Atlfast's ode. We want to analyse:� the type of parti le ( harged or neutral) whi h hits in ea h \ ell", inorder to do a lassi� ation of the \ ells".� the number of parti les inside ea h lassi�ed \ ell".� the transverse energy deposited in ea h \ ell".

Figure 8.7: A grid of \ ells" with a granularity �� x �� = 0.1 x 0.1 is de�ned aroundthe entral oordinate �jet-�jet of the re onstru ted jet.

8.8. Study of the overlapping of parti les 1558.8.1 Classi� ation of the \ ells"In order to later apply the Energy Flow Algorithm, \ ells" will be dividedinto three lasses, in a similar way as in previous analysis in CDF[19℄[20℄[10℄.For ea h lass of \ ell" a di�erent method to determine the energy olle tedin the \ ell" is adopted, whi h relies on the kind of parti les hitting the ell,(see also �g 8.8).� Charged ells: \Cells" hit only by harged hadrons (�� and k�).� Neutral ells: \Cells" hit only by photons.� Mixed ells: \Cells" hit by harged and neutral parti les.In the last lass of \ ells" the overlapping between harged hadrons andphotons or neutral hadrons will be analysed.

Figure 8.8: The lassi� ation of ells depends on whi h parti le fell in it. Only hargedhadrons: Charged, only photons: Neutral and a mixing between neutral and hargedparti les: Mixed Cells.Figure 8.9 shows the frequen y at whi h \ ells" are lassi�ed as harged,neutral or mixed. The density is higher in the enter of the bin distribution,it means that the overlapping takes pla e mostly in the �rst \ring"�R<0.1,as it is possible to see better in �g. 8.10.

156 8. Energy Flow in Atlfast

Figure 8.9: Number of times that ea h \ ell" is lassi�ed as Charged, Neutral or MixedCell per jet in the �-� plane, for 40-80 GeV jets with �R=0.4.In �gure 8.10, the number of the lassi�ed \ ells" is analysed as a fun -tion of the radius �R. The majority of the parti les are in the entral\ring"(�R<0.1), mainly in the ase of the Mixed Cells, whi h implies thatthe overlapping will be an important e�e t.Figure 8.10: Number of times that ea h \ ell" is lassi�ed as Charged, Neutral or MixedCell per jet as a fun tion of the radius �R, for 40-80 GeV jets with �R=0.4. Most are inthe entral \ring", (� <0.1).The table 8.4 shows the ell lassi� ation for the total grid in the �-�plane (DR<0.4) and for the entral region (�R<0.1), where most of the ETis deposited.�R=0.4 Charged ells (%) Neutral ells (%) Mixed ells (%)�R<0.4 �R<0.1 �R<0.4 �R<0.1 �R<0.4 �R<0.140-80 GeV 40.1 18.6 48.8 18.6 11.1 8.780-160 GeV 38.5 16.5 45.7 16.5 15.8 12.0160-320 GeV 36.4 14.8 44.6 14.8 19.0 13.9Table 8.4: Proportion of Number of lassi�ed ells for the total grid (�R<0.4) and forthe entral region (�R<0.1).

8.8. Study of the overlapping of parti les 157Also the ET deposited in Charged Cells by the harged hadrons, inNeutral Cells by the photons and in Mixed Cells by the mixing of neutraland harged parti les for ea h one of the 81 \ ells", has been evaluated. The�g. 8.11 and �g. 8.12 show the results for jet range at 40-80 GeV.

Figure 8.11: ET deposited in the �-� plane by harged hadrons in Charged Cells,photons in Neutral Cell and mixing neutral- harged parti les in Mixed Cells per jet at40-80 GeV with �R=0.4.Figure 8.12: ET deposited in Charged, Neutral and Mixed \ ells", as a fun tion of theradius DR, in the ase of 40-80 GeV with DR=0.4.Finally, the table 8.5 shows the mean value of the ET deposited in ea hjet and the proportion in % respe t to the total ET of the re onstru ted jetfrom the stable parti les. Again, the values are shown for some ranges ofET of the jet for the ase of DR=0.4�R=0.4 ET jet Charged ells Neutral ells Mixed ells(GeV) per jet(GeV) (%) per jet(GeV) (%) per jet(GeV) (%)40-80 35.50 16.31 45.8 6.73 18.9 12.56 35.380-160 65.94 21.84 33.8 8.67 13.4 35.28 54.6160-320 94.20 23.72 25.2 9.59 10.2 60.68 64.4Table 8.5: ET deposited in Charged, Neutral and Mixed \ ells' respe t to the total ETof the re onstru ted jet from the stable parti les.

158 8. Energy Flow in AtlfastThis table shows that up to � 45% of the total ET , in the best ase, omes from harged hadrons. So the Energy Flow algorithm will be appliedto an important portion of the jet energy. However this proportion of energyde reases qui kly as the range of ET of the jets gets larger. At the sametime, the energy deposited in the Mixed Cell in reases, be ause the overlapof parti les is bigger. So, the gain of resolution with the appli ation of thealgorithm will de rease with energy.8.8.2 Jet ET resolution with and without Energy FlowThe energy resolution of the photons into Neutral ells is al ulated a ord-ing to the parameterization of the EM Calorimeter, whereas for the MixedCells is approximated 7 by the parameterization of the HAD Calorimeter.

Figure 8.13: Energy resolution of the harged hadrons from HAD Calorimeter, � 13%,for the ase of 40-80 GeV and DR=0.4.

Figure 8.14: Momentum resolution of the harged hadron tra ks from Inner Dete tor,�1%,for the ase of 40-80 GeV and DR=0.4.7This is an approximation be ause in Mixed Cells, as well as hadrons, there are alsoele trons and photons and the resolution of their energy is al ulated for simpli ity fromthe parameterization of the Hadroni Calorimeter instead of by the EM Calorimeter

8.8. Study of the overlapping of parti les 159For the energy deposited by the harged hadrons into the Charged ells,usually the HAD alorimeter parameterization is taken by Atlfast, but sin ewe apply Energy Flow method, we are going to substitute the energy alorime-ter resolution by the tra k momentum resolution of the inner dete tor.One an see in previous plots, for the ase of 40-80 GeV and �R=0.4,the di�eren e between the energy resolution of the harged hadrons fromHAD Calorimeter, � 13% (see �g. 8.13), and the momentum resolution ofthe tra k from Inner Dete tor,� 1% (see �g. 8.14), mu h better.This di�eren e in the energy resolution of the harged hadrons fromHAD alorimter to inner dete tor implies an improvement in the jet ETresolution when the Energy Flow algorithm is applied. For the ase of40-80 GeV jets with �R=0.4 (�g.8.15), the improvement is �40%, sin eapplying Had Calorimeter parameterization the resolution is �7.9% while ifthe parameterization of the inner dete tor is applied it redu es to �4.8%.

Figure 8.15: For the range of 40-80 GeV and �R=0.4, the resolution in the ET of the jetapplying HAD Calorimeter parameterization is �7.9% (top) while if the parameterizationof the inner dete tor is applied the resolution improves �4.8% (bottom).

160 8. Energy Flow in AtlfastThe table 8.6 shows the jet energy resolution for the two s enarios(hadroni alorimeter energy resolution and tra k momentum resolutionfrom inner dete tor) and the relative improvement.�R=0.4 RMS (HAD) RMS (INNER) Improvem(%)20-40 GeV 0.094 0.046 51.540-80 GeV 0.079 0.048 39.080-160 GeV 0.062 0.042 31.0160-320 GeV 0.051 0.039 23.6320-640 GeV 0.041 0.034 16.9640-1280 GeV 0.032 0.029 9.6�R=0.7 RMS (HAD) RMS (INNER) Improvem(%)20-40 GeV 0.091 0.032 64.740-80 GeV 0.076 0.049 35.780-160 GeV 0.062 0.043 30.7160-320 GeV 0.049 0.039 20.4320-640 GeV 0.039 0.033 16.6640-1280 GeV 0.031 0.028 9.5Table 8.6: Jet energy resolution for the two s enarios (hadroni alorimeter energy reso-lution and tra k momentum resolution from inner dete tor) and the relative improvement.The range of 20-40 GeV has worse results be ause there is a bias in thejet sele tion, due to the uts applied in the generation of the jets are lose tothe jet energy. To generate jets in Atlfast, we applied uts in the minimumvalue of the PT of the jets:- PminT = 15 GeV for �R=0.4- PminT = 20 GeV for �R=0.7.

Figure 8.16: Left: re onstru ted jet by Atlfast at 20-40 GeV with a ut PminT =15 GeVfor �R=0.4. Right: re onstru ted jet from parti les at 20-40 GeV with �R=0.4.

8.8. Study of the overlapping of parti les 161

Figure 8.17: Left: re onstru ted jet by Atlfast at 20-40 GeV with a ut PminT =20 GeVfor �R=0.7. Right: re onstru ted jet from parti les at 20-40 GeV with �R=0.7.In the 20-40 GeV range, as it is possible to see in the �gures 8.16 and8.17, the mean value of ET for the re onstru ted jets from the sele ted stableparti les are very lose to this ut:- ET Mean = 21.65 GeV for �R=0.4 (see �g. 8.16)- ET Mean = 24.38 GeV for �R=0.7. (see �g. 8.17)So, there may be an important portion of the andidate jets that are not onsidered in the analysis.To sumarize, with this simpli�ed model, we see that there is potentiallyan important gain in resolution. From the results, we an extra t that theimprovement de reases as the jet energy in reases. This improvement in theresolution is larger at low PT , rea hing values up to �40%. At a few 100GeV the overlap between harged and neutral parti les in reases and thegain in resolution for jets be omes marginal.Figure 8.18: Variation of the jet energy resolution for the two s enarios (hadroni alorimeter energy resolution and tra k momentum resolution from inner dete tor) forjets with �R=0.4 (left) and �R=0.7 (right).However, the �gure quoted should not be interpreted as a realisti es-timate of performan e be ause shower u tuations have not been in ludedand will limit the improvement.

162 8. Energy Flow in Atlfast8.9 PT spe trum of parti les, Underlying Eventsand Minimum BiasAs we have seen, the best results of the Energy Flow Algorithm havebeen obtained at low ET . In this se tion, we are going to study the rangeof 40-80 GeV and the one �R=0.4 in more detail.8.9.1 Transverse Energy of single parti lesTo ontinue the Energy Flow analysis in Full Re onstru tion, we needto al ulate the transverse energy deposited by the parti les whi h formthe jets (mainly pions and photons). In Figure 8.19, the ET distributions ofpions and photons are shown for low ET jets. The average ET is �2 GeV forpions and �1 GeV for photons, about half the value of hadrons as expe ted,taking into a ount the ut o� at 0.5 GeV for harged parti les.

Figure 8.19: The average ET distributions of pions (top) and photons (bottom) for lowET jets with one �R=0.4.Therefore, the fra tion of low PT parti le inside the jet one of radius0.4 is around the 25% for harged parti les and �18% for neutral parti les,the rest of the jet is omposed by parti les of high PT , so the bulk of the jetenergy is arried by a small number of the most energeti parti les. Taking

8.9. PT spe trum of parti les, Underlying Events and Minimum Bias 163into a ount this information, we must work not only with sets of parti lesof low PT when we want to ompare Monte Carlo simulation results withreal data.On the other hand, we must onsider, for future analysis in Full Simula-tion, the problem that the Energy Flow method an generate for jets withenergeti harged fragments. Compared to soft harged fragments, the e�e tof the magneti �eld on these parti les is small and, therefore, they enter the alorimeter in the same region where also the photons (from the �0 de ay)deposit most of their energy, and the probability of the overlap between harged and neutral parti les inside the alorimeter ell will be in reased.8.9.2 E�e t of Underlying EventsThe general analysis shown in this hapter has been done without onsider-ing neither Underlying Events (UE) nor Minimum Bias (MB) Events, onlytaking into a ount the 'Hard s attering' omponents, that onsists of theout oming two jets whi h have been generated by a hard 2-to-2 partons attering whi h intera t at short distan e with large PT transferred.Protons are not fundamental parti les. They are formed by quarks andgluons. In addition to the hard s attering, multiple intera tions an takepla e: a se ond, a third... softer 2-to-2 s attering, and they ontribute tothe Underlying Events[21℄[22℄[23℄. So, the UE Corre tions onsider all the ontributions to the jet energy not oming from the original partons, i.e., iseverything ex ept the hard s attering and onsist of:� The beam-beam remnants� Multiple intera tions� ISR and FSRIn our analysis, we have generated the QCDjets in luding the e�e t ofISR and FSR be ause they have in uen e in the �nal dire tion of the jetsas well as in the multipli ity of them. So, when we ompare here QCDjetswith Underlying Events we try to understand mainly the e�e t of addingmultiple intera tions in the analysis.Due to UE, the measured jets may be signi� antly more energeti thanthe jets intended by nature, so if we in lude the UE in the analysis weexpe t to �nd an in rease of the transverse energy asso iated with ea hre onstru ted jet.

164 8. Energy Flow in AtlfastOn the other hand, UE have also an in uen e in the multipli ity ofthe parti les whi h form our re onstru ted jets and we expe t to �nd anin rease in the multipli ity of harged hadrons and photons, as it an beseen in �g.8.20 and �g.8.21.

Figure 8.20: The multipli ity of harged hadrons in rease from �7.0 harged hadronsper jet to �7.7, i.e., around 10%, when the Underlying Events are in luded.Figure 8.21: The multipli ity of photons in rease from �7.1 photons per jet to �8.1,i.e., around 14%, when the Underlying Events are in luded.O upan y of ells and Density parti les per eventWe ompare the number of parti les per event that hit in ea h alorime-ter ell with a granularity of 0.1 x 0.1 in the �-� plane in both ases:a) when only QCDjets (with ISR and FSR in luded) have been generated:QCDjetsb) when the multiple intera tion is onsidered and Underlying Events arein luded: UE+QCDjetsThe table 8.7 shows as the o upan y of ells8 is more than the doble whenwe onsider the UE+QCDjets respe t to when only QCD jets are taken intoa ount.8These numbers have been extra ted from the \total parti les versus eta" distributionswith a bin equal to the granularity of the alorimeter (i.e. �� =0.1). Also the histogramshave been normalized by 64, be ause the granularity of the alorimeter is ��x�� = 0.1 x0.1, so, �� = 0.1 � 2�/64, and we have supposed that there is symmetry in � oordinate.

8.9. PT spe trum of parti les, Underlying Events and Minimum Bias 165O upan y of Cell (part / ell)Total Total Parti Charged HadParti les (PT ut) (PT ut)QCDjets 0.030 0.024 0.008UE+QCDjets 0.085 0.060 0.017Table 8.7: O upan y of ell (part / ell) with a granularity of 0.1 x 0.1 in the �-� planefor only QCDjets and for UE + QCDjets.Therefore the density of parti les per unit of pseudorapidity is analysedfor only QCDjets and for UE + QCDjets (see table 8.8) to ompare withprevious analysis (see table 8.9). The mean value of the parti le density,dN/d�, de reases when we apply the PT ut to the harged parti les9.Density Parti les in eta (part /eta)Total Total Parti Charged HadParti les (PT ut) (PT ut)QCDjets 19 15 5UE+QCDjets 54 38 11Table 8.8: Density parti les in eta (part /eta) for only QCDjets and for UE + QCDjets.

Table 8.9: LHC predi tion for Underlying Events and Minimum Bias Events for pp ollision at energies of p14 TeV, taken from A. Moraes studies[24℄.9PT>0.5 GeV to remove the parti les that do not rea h the alorimeter due to thee�e t of the magneti �eld.

166 8. Energy Flow in Atlfast8.9.3 Appli ation of Energy Flow with Underlying EventsWe apply the Energy Flow algorithm to QCDjets for the range of 40-80GeV and �R=0.4 with Underlying Events. As the �gure 8.22 shows whenthe parametrization of the hadroni alorimeter is applied to the harged ells the resolution in energy is �7.9%. When the parameterization of theinner dete tor is applied the resolution is �4.9%. So, the appli ation of theEnergy Flow algorithm gives an improvement �38% and the results are verysimilar to the ones obtained without Underlying events.

Figure 8.22: ET resolution of the jet applying Had Calorimeter parameterization (top)and applying inner dete tor parameterization (botom) for harged ells in 40-80 GeV jetsre onstru ted with �R=0.4.

8.9. PT spe trum of parti les, Underlying Events and Minimum Bias 1678.9.4 E�e t of Minimum Bias EventsMinimum Bias studies are important in order to understand the ba kgroundto signal events. For this reason Minimum Bias studies are used to predi tradiation damage to the dete tor reated by the s attered protons.The ross se tion for hadron-hadron ollision onsists of four major pro- esses lassi�ed as non di�ra tive, single di�ra tive, double di�ra tive andelasti . The pro esses of interest for tra king studies are the inelasti non-di�ra tive with a ross se tion of the order of �70 mb from TDR studies(Pythia 5.7). More re ently, the best �t to experimental data with Pythia6.2 predi ts a ross se tion of 55 mb.

Figure 8.23: Density of harged (left) and neutral (right) parti les in the simulatedMinimum Bias events for unit of rapidityThe non-di�ra tive inelasti events, used to simulate Minimum Bias Pro-du tion, were generated using Pythia 6.203. In �g. 8.23 it is possible tosee the mean multipli ity of harged and neutral parti les in the simulatedMinimum Bias events. In the region j�j <5, the average number of hargedparti les (no pT ut applied) is 7 per MB events and per unit of rapidity,while for neutral parti les it is 8.5. These are similar results to the ones thatappear in the Calorimeter Performan e and TDR studies. The di�eren esare due to the multipli ity of the parti les that depend on the model usedfor the parton-parton intera tions in the generators, as is shown in the A.Moraes studies[24℄.Pile-Up Events at low luminosityAt high luminosities, multiple ollisions within one beam- rossing will beinevitable, ausing signal events to have several Minimum Bias events su-perimposed. The pile-up of these events on top of single parti les is essentialfor realisti studies.

168 8. Energy Flow in AtlfastIn ea h bun h rossing, the number of Minimum Bias events produ ed isdes ribed by a Poisson distribution with a mean determined by the MinimumBias ross se tion and the operating luminosity of the LHC. The expe tedaverage number of MB events per bun h rossing is expe ted to be 23 for highluminosity (1034 m�2s�1) running while for low luminosity (1033 m�2s�1),an average of 2.3 minimum bias events per bun h rossing is expe ted.We have generated Pile-Up events at low luminosity, i.e., leading a Pois-son distribution with a mean value of 2.3 events of Minimum Bias per bun h rossing. Pythia generator ontains an option to generate several events andput them one after the other in the event re ord. The program needs to knowthe assumed luminosity per bun h rossing expressed in mb�1; for the LHC ase these values are:- 0.250 for high luminosity (1034 m�2s�1)- 0.025 for low luminosity (1033 m�2s�1)Multiplied by the ross se tion for the Pile-Up pro esses studied, this givesthe average number of ollision per beam rossing. Pythia take the Pile-Upevents to be of the Minimum Bias type (with di�ra tive or elasti in ludedor not). In our ase we take into a ount only the non-di�ra tive inelasti low PT events.O upan y of ells and Density parti les per eventIn the tables 8.10 and 8.11 we ompare the number of parti les per eventthat hit ea h ell of 0.1x0.1 in the � � � plane, for the ases:a) only QCDjets (with ISR and FSR in luded)b) only Minimum Bias events ) only Pile Up at low luminosity (2.3 MB events per bun h rossing)O upan y of Cell (part / ell)Total Total Parti Charged HadParti les (PT ut) (PT ut)QCDjets 0.030 0.024 0.0080MB Events 0.024 0.016 0.0035Pile-Up 0.045 0.031 0.0075Table 8.10: O upan y of ell (part / ell) with a granularity of 0.1x0.1 for QCDjets,MB events and Pile-Up events at low luminosity.

8.9. PT spe trum of parti les, Underlying Events and Minimum Bias 169Density Parti les in eta (part /eta)Total Total Parti Charged HadParti les (PT ut) (PT ut)MB Events 15 10 2.2Pile-Up 29 20 4.8QCDjets 19 15 5Table 8.11: Density parti les in eta (part /eta) for QCDjets, MB events and Pile-Upevents at low luminosity.In this ase, when we apply the PT ut of the harged parti les (PT>0.5GeV) to the MB and Pile-Up events, the value dN/d� falls a lot be auseit is hara terised by low PT values. So the e�e t of Pile-Up events in thesignal with low PT is very small.8.9.5 Transverse Energy Deposited by Soft Pro essesUnderlying Events and Minimum Bias are both onsidered soft pro esses,i.e., these pro esses are hara terized by having a very small omponentof energy in the transverse region, whi h is the main region of interest forphysi s analysis.The �gure 8.24 show the o upan y for the 4 ases:- QCDJet+Underlying Events,- QCDjets only,- Minimumb Bias,- Pile Up at low luminosity,with and without PT ut applied, and the �gure 8.25 shows their orre-sponding energy deposit in ea h ell.Figure 8.24: Number of total parti les ( harged and neutral) in the 4 ases:QCDJet+Underlying Events (white), QCDjets (yellow), MB (grey) and Pile-Up at lowluminosity (grid histo). The �rst plot without PT ut applied and the se ond with it.

170 8. Energy Flow in Atlfast

Figure 8.25: ET deposited in ea h ell, in the 4 ases: QCDJet+UnderlyingEvents(white), QCDjets (yellow), Minimum Bias (grey) and Pile-Up at low luminosity(grid histogram). The �rst plot without PT ut applied and the se ond with it.One an see that although the o upan y of UE and Pile-Up events(of MB type) is of the same order of the QCDjets, their orrespondingenergy deposit is mu h smaller, than the QCDjets (MB �20GeV, Pile-Up�45 GeV), even more so if we apply the ut o� to the harged hadrons ofPT>0.5 GeV (MB �7GeV, Pile-Up �14 GeV).As the ontribution of the Pile Up events at low luminosity to the totalET is so small, their in uen e in the �nal energy resolution when the EnergyFlow algorithm will be applied (i.e, the sustitution of the ET by the pTtra k in harged parti les), over the ET deposited by these parti les ouldbe negligible.8.9.6 Pile-Up Events at high luminosityAt high luminosity ea h bun h rossing ontains an average of 23 MinimumBias events, and we also must take into a ount the response fun tion of thesubdete tors (i.e. in the Liquid Argon ase there are 18 bun h rossing ea htime the dete tor takes data). So, one pile-up event an onsist of almost500 MB events, although most of them are assigned a small weight, and�nally there are �40 MB events per bun h rossing.So in the high luminosity environment, the e�e t of the Pile-Up events isnot negligible respe t to the QCDjets signal. We will have a large multipli -ity of the tra ks and it will be diÆ ult to mat h orre tly to the orrespond-ing harged luster, whi h implies the risk of bad de�nition of neutral or harged lusters and the impossibility to apply the Energy Flow Algorithm.

8.10. Con lusions and further studies 1718.10 Con lusions and further studiesWe an on lude that the appli ation of the Energy Flow algorithm atparti le level in ATLAS an potentially improve the jet energy resolution.This improvement is better at lower PT rea hing values up to �40% ofrelative improvement in the resolution. Nevertheless, around 100 GeV theoverlap between parti les is higher and the gain in resolution of the energyfor jets is marginal.Respe t to the soft pro esses, the in uen e of the Underlying Eventsand the Pile-Up events at low luminosity an be negligible for Energy Flowresolutions.However, one should keep in mind that this analysis has been done usinga fast simulation pa kage but also a very \simplisti " one, where the e�e tof the dete tor and also a lot of ir umstan es have not been onsidered.Atlfast supposes that ea h parti le deposited all its energy in one ell,when in reality parti les deposit their energy in a set of ells forming a luster, whose shape and size depend on multiple fa tors as the type ofparti le (EM or HAD shower), the energy, the e�e t of the magneti �eldand the amount of material in front of the alorimeter, whi h in reasesthe multipli ity from se ondary parti les (mainly the onversion of photonsfrom �0's) and make wider the luster. By other hand, Atlfast assumed the orre ted mat h tra k- luster, but at high luminosity the multipli ity of thetra ks is very large and this is a not simple task.Taking into a ount all these fa tors requires the use of advan ed luster-ing algorithms apable of eÆ ient isolation of the individual shower togetherwith an energy deposition model. These tools have been a tually developedin Full Simulation ontext[25℄[26℄[27℄.So, the parti le level study des ribed in this hapter will be followed upwith a deeper lustering algorithm analysis (see Chapter 9 and 10 of thisthesis) and a full simulation studies where the dete tor response is modelledin a very a urate way by GEANT. Then, a realisti study of the energyresolution that an be rea hed in ATLAS with Energy Flow will be obtained.In addition, during the summer of 2004 there was a Combined Testbeam where the LArEM alorimeter and the Hadroni Tile Calorimeterwere tested together, as well as the Inner dete tor. In this ombined TBsingle pions and ele trons at very low pT (from 1 to 9 GeV) have been mea-sured, and these will be interesting data to validate Energy Flow algorithmand to understand the in uen e of the overlap between parti les[28℄[29℄ (seeChapter 11 and 12 of this thesis).

172 Referen es:Referen es:[1℄ ATLAS Collaboration, ATLAS Dete tor and Physi s Performan eTe hni al Design Report CERN/LHCC/99-14, ATLAS TDR 14 (1999).[2℄ C++ version of Atlfast in Athena,http://www.hep.u l.a .uk/atlas/atlfast[3℄ E.Ri hter-Was, ATLFAST 2.0 A fast simulation pa kage for ATLAS,ATLAS Note ATL-PHYS-98-131 (1998)[4℄ D. Buskuli et al., (ALEPH Collaboration), Performan e of the ALEPHdete tor at LEP CERN-PPE/94-170(1994), Published in: Nu l. In-strum. Methods Phys. Res., A 360 (1995) 481-506.F.Ligabue et al. (ALEPH Collaboration), Jet Calibration at LEP2,In Pro eedings of the IX Int. Conf in Calorimetry in Part.Phys.,CALOR2000, Anne y(2000).[5℄ T. Omori et al. (OPAL Collaboration), Attempt to Compensate Energyin OPAL Calorimeter Complex based on MT Pa kage, OPAL Te hni alNote TN-447 (1996).E. Du hovni et al., (OPAL Collaboration), GCE++ An Algorithm forEvent Energy Re onstru tion, OPAL Te hni al Note TN-306 (1995).[6℄ S. Lami et al., (CDF Collaboration), Studies of Jet Energy Resolution,FERMILAB-Conf-00/342-E CDF 2001 (2001).A. Bhatti et al., (CDF Collaboration), Review of Jet Clustering at Teva-tron, In Pro eedings of the IX Int. Conf in Calorimetry in Part.Phys.,CALOR2000, Anne y (2000).O.Lobban, A. Shiharan and R. Wigmans, (Texas Te h University), Onthe Energy measurement of Hadron Jets, In Pro eedings of the X Int.Conf in Calorimetry in Part.Phys., CALOR2002, Pasadena, (2002).[7℄ C. Issever et al., (H1 Collaboration), The alibration of the H1 liquidArgon alorimeter, In Pro eedings of the IX Int. Conf in Calorimetryin Part.Phys., CALOR2000, Anne y, (2000).[8℄ J. Breitweg et al., (ZEUS Collaboration), Eur. J. Physi s. C1, 81(1998).M. Wing (ZEUS Collaboration), Pre ise Measurement of the Jet En-ergies with the ZEUS Dete tor, In Pro eedings of the IX Int. Conf inCalorimetry in Part.Phys., CALOR2000, Anne y, (2000).

Referen es: 173[9℄ P.Gay, Energy ow. In Pro eedings of the Linear Collider Work-shop 2000, Fermilab, Batavia, IL, USA, 2000. http://www-l .fnal.gov/l ws2000V.L. Morgunov Calorimetry Design with Energy-Flow on ept (ImagingDete tor for High-energy Physi s), In Pro eedings of the X Int. Confin Calorimetry in Part.Phys., CALOR2002, Pasadena, (2002).[10℄ D. Costanzo. Ph. D. Thesis. Sear h for a Standard Model Higgs Bosonusing the W-pair de ay hannel at the Large Hadron Collider. July 2000.http://www.pi.infn.it/atlas/do umenti/tesi/davide/thesis.html[11℄ D. Green Energy Flow in CMS Calorimetry Fermilab-FN-0709S. Kunori (CMS Collaboration), Jet Energy Re onstru tion with theCMS Dete tor, In Pro eedings of the X Int. Conf in Calorimetry inPart.Phys., CALOR2002 Conferen e, Pasadena, (2002).D.Green et al., Energy ow obje ts and usage of tra ks for energy mea-surement in CMS, CMS NOTE 2002/036, Sept (2002).[12℄ M. Wierlers (ATLAS Collaboration), Performan e of Jets and missingET in ATLAS, talk at CALOR2002 Conferen e, Pasadena, (2002).[13℄ e owRe pa kage: Energy Flow Re onstru tion in Athena (Dan Tovey)http://atlas.web. ern. h/Atlas/GROUPS/PHYSICS/JETS/EFLOWREC//e owre .htm[14℄ C. Iglesias, Re onstru ion de Jets mediante el algoritmo Energy Flowen ATLAS, talk in VII Jornadas de Fisi a de Altas Energia, XXIXReunion Bienal, Madrid, (2003).[15℄ R. Wigmans, Calorimetry - Energy Measurement in Parti le Physi s,Internal Series of monographs on Physi s, vol 107, Oxford UniversityPress (2000).[16℄ Athena User and Developer Guide v.2.0 & Releaseshttp://atlas.web. ern. h/Atlas/GROUPS/SOFTWARE/OO/ar hi-te ture/General/[17℄ Geant4 Users do uments:http://wwwasd.web. ern. h/wwwasd/geant4/G4UsersDo uments//Overview/html/index.html[18℄ T.Sjostrand, Comput. Phys. Commun. 82 (1994):, T.Sjostrand et al,Comput. Phys. Commun. 135 (2001) 238; T.Sjostrand, L. Lonnblad

174 Referen es:and S Mrenna PYTHIA 6.2 - Physi s and Manual, [online℄ hep-ph/0108264, august:2001. Available from: http://weblib. ern. h/.[19℄ G. Latino. Ph.D Thesis, Calorimetri Measurements in CDF: A NewAlgorithm to improve the energy resolution of hadroni Jets. Univ. ofCassino, Italy. CDF/THESIS/JET/PUBLIC/5555. February 2001[20℄ A. Bo i, D. Costanzo, S. Kuhlmann, S. Lami and R. Paoletti. JetEnergy Resolution using alorimeter, tra king and shower max infor-mation. CDF/ANAL/JETCDFR/4681 (1998)S. Lami, G. Latino .An update of the Jet Energy Resolu-tion using alorimeter, tra king and shower max information.CDF/ANAL/JET/CDFR/5192 (1999)A. Bo i, S. Kuhlmann, S. Lami and R. Paoletti. Lastest results onthe Jet Energy Resolution using alorimeter, tra king and shower maxinformation. CDF/ANAL/JETCDFR/4681 (1998)[21℄ R. Field and D. Stuart. Min-Bias Data: Jet Evolution and EventShapes. CDF/ANAL/MIN-BIAS/CDFR/5067 July 1, 1999.R. Field. (Florida-CDF) The Underlying Event in Hard S attering Pro- esses. Cambridge Workshop, July 20, 2002.[22℄ D. Green (Fermilab). Minimum Bias Pileup and Missing ET at CMS.Sept 1999.[23℄ Minimum bias physi s at ATLAS:http://www.shef.a .uk/physi s/resear h/hep/atlas/physi s/ lements-nuÆeld/mbias.html[24℄ A.Moraes, I.Dawson, C. Buttar. Comparison of predi tionsfor minimum bias event generator and onsequen es for ATLASradiation ba kground. ATL-PHYS-2003-020 (2003)A. Moraes. Minimum bias and the underlying event: ATLAS tuningpresented at the Workshop on Monte Carlo tools for the LHC - CERN;31st Jul 2003.[25℄ S.Menke Status of Topologi al Clustering presented at the Software &Performan e Meeting, LAr Week (CERN), 28. Jan 2004 and Status ofTopologi al Clustering & re ent Re o-Software Changes, presented atthe Hadroni Calibration meeting (CERN), 13 May 2004.

Referen es: 175[26℄ C. Iglesias, M. Bosman,Study of jet omposition at parti le level andits impli ations for Energy Flow algorithms. ATL-SOFT-INT-2005-003,De 2004.[27℄ C.Iglesias IFIC talks: TiCal-IFIC Weekly Meetings (Valen ia, SPAIN),at my personal web page: http://i� .uv.es/�iglesiasC.Iglesias, Clustering of very low ET parti les, presented at theSoftware Workshop, Re onstru tion Working Group: Calorimetry,Sep,2004, CERNC.Iglesias, Clustering of very low ET parti les, ATLAS ommuni ationin preparation.[28℄ C.Iglesias, Clustering of very low ET parti les in Combined TB, pre-sented at the ATLAS Calorimetry CalibrationWorkshop, Hadroni Cal-ibration Session, De 2004, Trata, SlokaviaC.Iglesias, More about very low energy parti le, presented at the Tile-Cal Commissioning Meeting 2 Feb, 2005C.Iglesias, Clustering for VLE parti les in CBT, presented at the Tile-Cal Analysis and Combined Test Beam, 14 Feb, 2005, TileCal Week,CERNC.Iglesias, V. Giangiobbe. Analysis with VLE runs in Combined TB,presented at the Final Combined Test Beam Workshop, 16 Feb,2005,CERN[29℄ C.Iglesias, Clustering of very low ET parti les with 2004 CombinedTestBeam data of ATLAS, ATLAS ommuni ation in preparation.

176 Referen es:

Chapter 9Clustering algorithms inATLAS re onstru tionsoftware9.1 Introdu tionIn this hapter the di�erents tool inside the framework of Athena[1℄ to arry out the Cluster re onstru tion are shown.We introdu e the subje t in se tion 9.2 with the explanation of the mainsteps of the o�-line re onstru tion, deepingn in the luster re onstru tion, lassi� ation and alibration.In se tion 9.3 the importan e of the lustering algorithm is explained:their improve the results when the Energy Flow is applied.Finally, from the se tion 9.4 the di�erent lustering algorithms insidethe o�ine software of ATLAS are explained: Sliding Window lustering,Egamma lustering and the 3D Topologi al algorithm: CaloTopoClusters,with its di�erent apli ations and tools in 7.8.0 and 8.2.0 releases of Athena.They will be used in the next hapter in the analysis of the single parti lesat very low energy (VLE).9.2 O�-line re onstru tionThe basi idea for the energy re onstru tion and alibration is done in threemain steps:a) On the read-out ell level only very general alibration and orre -tion pro edures should ve applied su h that lo ally the best energy177

178 9. Clustering algorithms in ATLAS re onstru tion softwareestimate is obtained without biasing it toward some espe i� interpre-tations on the nature of the deposited energy.b) On the luster level topologi al information in the neighborhood ofthe read-out ell an be exploit and a �rst hypothesis on the natureof the enrgy depositiion an be made. For instan e, based on thetopology of the enrgy deposits within a luster a weighting algorithmto orre t for non ompensating nature of the ATLAS alorimeter ould be applied for hadroni energy deposits. ) On the level of identi�ed parti les the whole ATLAS dete tor in-formation is available to re�ne the energy re nstru tions: ra k, deadmaterial, et , as well as use luster merging or slimming algoritms.A simple logi al ow stru ture for the o�-line re onstru tion of the var-ious steps would be:- ell sele tion (topologi al noise suppression) and ell orre tions forele troni s and HV- luster formation based on dire t neighbours in three dimensions- luster lassi� ation based on the topology of the energy deposit withina luster- luster alibration for three hypotheses: ele tromagneti , hadroni ormuoni - luster orre tion for topology dependent orre tions- luster merging or slimming on identi�ed parti le level, luster orre -tions ( ra k, dead material et .)9.2.1 Cell sele tionSin e the ATLAS alorimeter[2℄ is non ompensating, a weighting algorithmhas to applied to hadroni energy deposits. Sin e for hadroni intera tionpart of the energy is lost in intera tion whi h do not lead to a measurablesignal, e.g. nu lear breakup, low energy neutron produ tion et ., a weightingalgorithm should be applied to hadroni energy deposits. This weightingalgorithm an, for instan e, parameterise the average invisible energy loss asa fun tion of the ell energy density. Purely ele tromagneti energy depositsare not hanged.Sin e the orre tion for invisible energy losses, ampli�es low energeti energy deposits, a topologi al noise suppression s heme is needed before the

9.2. O�-line re onstru tion 179 luster formation. In su h a s heme a seed ell is required to be abovea ertain energy threshold orresponding to an average noise level mea-sured in standard deviations �noise (E ell;seed > n �noise ). Cells neighouringthe seed are in luded if they are above a somewhat lower energy threshold(jE ell;neighbourj > m �noise ). In this ase the noise ut is symmetri , i.e.also ells with negative energies an be in luded if they are geometri ally onne ted to a high energeti ell. This pro edure avoid a major bias dueto the noise suppression. No luster with negative energies are formed.9.2.2 Cluster formationThe �rst step ould be the formation of lusters within a alorimeter layer,i.e. in two dimensions using a dire t neighbour algorithm. In a se ond stepa three dimensional luster an be formed using the main dire tion of theshower propagation. The lustering algorithms have to be tuned su h thatele tromagneti showers indu ed by ele trons and photons are ontainedin one luster. This luster ould be used on the identi�ed parti le levelfor the ele tron or photon identi� ation and the re onstru tion. In ontrast,hadroni showers an break up in many 3D-Clusters. In this s enario hardlyany jet would stay within one luster.9.2.3 Cluster lassi� ationThe next step will be the luster lassi� ation a ording to the topology ofthe energy deposit. A hypothesis on the nature of the energy deposit willbe assigned to the luster. A luster an be lassi�ed as ele tromagneti ,hadroni or muoni . Simple shape variables an provide a likelyhood forea h hypothesis. So, it will be needed to arry out:� identi� ation of ele tromagneti shower{ identi� ation of ele trons{ identi� ation of photons� identi� ation of hadrons� identi� ation of muons9.2.4 Cluster alibrationIn general, the orre tions have to based on the nature of the energy deposit,e.g. for ele tromagneti lusters dead ells an be orre ted for by using thea priori known shape of ele tromagneti showers. For hadroni lusters this orre tion might be di�erent. The following luster orre tions should be

180 9. Clustering algorithms in ATLAS re onstru tion software onsidered: HV orre tions, Dead Cell, Impa t point, invisible hadroni energy losses, Upstream and downstream losses...Anyway, to be able to revise or re�ne a de ision on the level of identi�edparti les where more information is available the probability that ea h of thethree hypotheses be valid for a given luster will be al ulated and atta hedto the luster: three di�erently alibrated energies, to arry out the luster alibration.More re�ned orre tions, whi h depend on the identi�ed parti le typeshould be applied on the parti le level.9.2.5 Identi�ed Parti le alibrationHere, in addition to the energy luster it is possible to apply orre tionsdepending on the nature of the luster. For instan e, the dead material or-re tion based on the presampler is di�erent for ele tromagneti and hadroni showers ( luster nature), but also for ele trons and photons.Therefore, as the whole ATLAS dete tor information is available, addi-tional orre tions whi h use information of other subdete tors an be ap-plied: di�eren e due to intera tions in the inner dete tor, e.g. photon on-version et ., an be taken into a ount. Other subdete tors like the ra ks intillator an be used, as well as use luster merging or slimming algoritms.In some ases it might be ne essary to undo the orre tion applied on luster level.9.3 Why Clustering is useful for Energy Flow?The main on ept of the Energy Flow algorithm[3℄[4℄[5℄[6℄ for jet-�nding isto use the tra king dete tor for the measurement of harged parti le momen-tum and use the alorimeter energy resolution for neutral parti les. The �rststep is to identify the energy deposited in the EM and HAD alorimetersby harged hadrons and substitute it with the momentum measured by thetra king dete tor for the orresponding tra k. We therefore have to re on-stru t and subtra t neutral lusters before identifying the energy deposit ofthe harged parti les in the alorimeter.We also need pattern re ognition algorithms to asso iate energy depositin alorimeter ells with parti les. There are three di�erent ontribution:- The ele tromagneti showers (from ele trons and photons) are en-ergeti , mu h lo alized and highly orrelated, so the lustering algo-rithm works well in them.

9.4. Clustering Algorithms 181- Respe t to muons, they produ e only minimum ionization but theydo it throughout all its traje tory, so we an de�ne them using tra kinginformation in alorimeter and the MIP deposit will be minimal in any ase.- Finally, the hadron showers are broad and un onne ted, so they willbe most diÆ ult to handle.The use of tra k momentum instead of the alorimeter energy improvesthe energy resolution only for isolated lusters. If the energy deposited ina luster is released by the neutral and harged parti les, the improvementin resolution is diluted by the loss in resolution from the remaining lus-ter. In omplex events and within jets, more than one parti le will deposittheir energy in the same alorimeter ell, and showers will overlap. So, theeÆ ien y of the algorithm is limited by the overlap between neutral and harged parti les in the ells of the alorimeter. We need to know moreabout this e�e t and its in uen e in the analysis.On the other hand, the method is simple but its realization is a hallenge:it requires building the parti le ID asso iated with the tra k. This startsrunning into diÆ ulties in high tra k multipli ity environment and oarse alorimeter granularity: it requires use of advan ed lustering algorithm apable of eÆ ient isolation of the individual showers, together with anenergy deposit model.So, a good lustering algorithm is essential to resolve showers as well asa splitting or merging strategy. This algorithm will be also eÆ ient as many ells are hit by the parti les.9.4 Clustering AlgorithmsIn the present ATLAS s heme[7℄ , two di�erent types of luster algorithmsare foreseen:a) One type of luster algorithm basi ally sele ts the ore of an ele tro-magneti energy deposit in order to provide an optimal measurementof ele trons and photons. This algorithm de�nes a one around the entre-of-gravity of a middle ell and it in ludes 3x5 ells (for un on-verted photons) or 3x7 ells (for ele trons and onverted photons) asgiven by the geometry of the middle layer of the EM alorimeter.b) On the other hand, for the re onstru tion of hadroni shower the en-ergy deposits in near ells have to be merged to lusters. This lus-tering algorithm is therefore alled topologi al lustering algorithm.

182 9. Clustering algorithms in ATLAS re onstru tion softwareDepending on the nature of the energy deposit: hadroni , ele tromag-neti or muoni , di�erent energy orre tions should be applied.9.4.1 Sliding Window ClusteringThe Sliding Window (SW) algorithm is simple sear h for lo al maxima ofET deposit on a grid using a �xed-size \window" made up of a group of ontiguous trigger towers in �-� spa e. Lo al maxima are found by movingthe window by �xed steps in � and �. The window an be adjusted todi�erent sizes, so that it an be optimised for di�erent parti les/energies.They an then be orre ted for di�erent modulation e�e ts, and longitudinalweights are omputed to further optimise resolution and linearity.This algorithms produ es a very preliminary lusters of ells as no or-re tions have been applied yet. The default window size is 5 x 5 ells insideea h luster, entered in the ell with the biggest value of ET . This valueusually de�nes the luster formed by ele trons and photons with energylarger than 100 GeV.Di�erent window sizes are used for less energeti parti les (ET<100GeV)are 3x5 ells (for un onverted photons) and 3x7 ells (for ele trons and onverted photons).9.4.2 EGamma ClustersEGamma re onstru tion ombines Inner dete tor tra ks information withCalorimeter Clusters (Sliding Windows) with the default value of SW lus-ters of 5x5 ells inside ea h lusterTypi ally these are the algorithms useful for the identi� ation of theele tromagneti obje ts, ele trons and photons:a) Ele tron re onstru tion is performed in two ways:- High pT ele trons are sear hed for by asso iating tra ks to slidingwindow lusters, and omputing shower shape variables, tra k to luster asso iation variables, and TR hits variables. Dedi atedtra k �tting pro edure for ele trons are being developed.- Soft ele tron re onstru tion pro eeds by extrapolating hargedtra k to the alorimeter, and building a luster around the hargedtra k impa t point. This pro edure has a better eÆ ien y for lessthan 10 GeV transverse momentum ele tron, and for ele tron in-side jet, pertinent for b-tagging.b) High pT photons are identi�ed in a similar way, with the main di�er-en e that a tra k veto is performed, expe t for re onstru ted onver-sions.

9.4. Clustering Algorithms 1839.4.3 3D Clustering Algorithm: CaloTopoClusterThe 3D Clustering algorithm[8℄ in Athena reated by Sven Menke is basedon the ell Nearest Neighbor. This algorithm was developped for LAr (inLArClusterRe pa kage) and later extended to Tile Calorimeter and imple-mented inside ATHENA environment (in Re onstru tion/CaloRe pa kage).This algorithm is also used in the BaBar experiment[9℄.The main hara teristi of this lustering algorithm is that it is indepen-dent of the sub-dete tor, i.e., it an be used for LAr and Tile Calorimeterwithout any hange in ode.Basi Prin iple of the AlgorithmThe 3D Clustering algorithm onsists in a simple topologi al lustering algo-rithm working with three di�erent signal (energy deposited in ea h alorime-ter ell) over noise threshold:� Cell ut: jE=�noisej > T ell (default T ell = 0); only ells above thisthreshold are used� Neighbor ut: jE=�noisej > Tneighbor (default Tneighbor = 3); only ellsabove this threshold are sear hed from their neighbors� Seed ut: E=�noise > Tseed (default Tseed = 30); only ells above thisthreshold are used to initiate a luster1.Additional uts on the transverse energy deposited in the alorimeter ells an also be applied on all 3 levels: seed, neighbor and ell.A luster is built around a Seed ell whose energy is above a ertainthreshold (the Seed ut). The neighbors of the seed ell are added to the luster if their energy is above another threshold (the Neighbor ut). Finallythis is repeated re ursively until this pro edure onverges (see �g.9.1).The uts on the seed and the neighbor ells depend on the noise level inea h ell. This way lusters are formed around ells with E=�noise above a ertain value and a minimum transverse energy deposited.

1Note that in this last ase, threshold is only over the positive value, no over theabsolute value of E=�noise

184 9. Clustering algorithms in ATLAS re onstru tion software

Figure 9.1: In the 3D Clustering algorithm, the lusters are formed around a seed ellabove a ertain threshold (Seed ut = E=�noise ) and they are added to the luster if theirenergy is above the threshold Neighbor ut = jE=�noisej .9.5 Des ription of CaloTopoClusterMaker in 7.8.0In the 7.8.0 release of ATHENA, the implementation of topologi al lus-tering uses an AlgTool alled CaloTopoClusterMaker to reates CaloClus-ter[10℄ obje ts from a olle tion of CaloCell obje ts by grouping them a - ording to their neighbor relations:� all2D: produ es separate lusters in ea h Layer (only lusters in thesame layer and alorimeter). When used with the \AllCalo" optionthe di�erent layers orrespond to:- 4EMB +4EMEC +4HEC +3 FCAL +3 Tile = 22 regionsThe neighbors of a ell are the 2 neighbors in +/- � dire tion, the 2neighbors in +/- � dire tion and the 4 orner ells in +/- � and +/- �.Cells at the edges of the alorimeters (or in test beam modules) mighthave fewer neighbors, but usually ells have 8 all2D neighbors.� all3D: produ es separate lusters in ea h alorimeter EM, HEC, FCal,Tile (only lusters in the same alorimeter):- EM, HEC, FCal, Tile = 4 regionsThis is all the all2D neighbors of the ell plus ells in the samplingbefore and the sampling beyond this ell overlapping at least partiallyin the �-� plane with the urrent ell. Samplings outside the urrent alorimeter are not onsidered in this option.The �noise an be de�ned in two ways:- �xed: a �xed value for all ells (ad-ho ut of ET value). This optionis only useful for testing.- ele Noise: use the ele troni noise from CaloNoiseTool (default)

9.6. CaloTopoCluster in 8.2.0 Release 185The ele troni s noise levels (in MeV on a log s ale) for all ells is shown in�g. 9.22. The plot shows that the lustering has to ope with 3 orders ofmagnitude for the hanges in noise levels ranging from about 10 MeV in the�rst EM Barrel layer up to 1 GeV in the rear FCal module.

Figure 9.2: Ele troni s noise levels (in MeV on a log s ale) for all ells as a fun tion of alorimeter layers ( olor ode) and � (x-axis).9.6 CaloTopoCluster in 8.2.0 ReleaseIn the 8.2.0 release of ATHENA, CaloTopoClusterMaker[11℄ makes Calo-Clusters not only in ea h Layer (all2D) and in ea h alorimeter EM, HEC,FCal, Tile (all3D) but also anywhere a ross all alorimeters:� super3D: It means EM+HEC+FCal+TCal = 1 super- luster. Thisis all the all3D neighbors plus those in adja ent samplings from other alorimeter systems overlapping at least partially in the �-� plane withthe urrent ell. This option is the default from this release.Respe t to the noise, in this version in addition to the �xed value and theele Noise from CaloNoiseTool, CaloTopoClusterMaker works with:- totalNoise use a quadrati sum of ele troni -noise and Pile-Up noisefrom CaloNoiseTool. This is the default option from this release.And �nally CaloTopoClusterMaker works with optional additional jEj j(Ej)thresholds against Pile-Up on ea h level (defaults: 0 MeV, 100 MeV, 1000MeV)2Figure taken from TWiki Web page for Topologi alClustering, made by S. Menke.

186 9. Clustering algorithms in ATLAS re onstru tion softwareThe PileUp noise levels (in MeV on a log s ale) for all ells as a fun tionof alorimeter layers ( olor ode) and � (x-axis) is shown inf �g. 9.33. Itis possible to see as the noise levels span 4 orders of magnitude from a fewMeV in the entral Barrel region to 10+ GeV in some FCal ells.

Figure 9.3: PileUp noise levels (in MeV on a log s ale) for all ells as a fun tion of alorimeter layers ( olor ode) and � (x-axis).Another important hange in this new version is the implementationof the Splitter. It splits lusters based on topologi al neighbouring andde�ne lo al maxima based on energy density riteria. This will be a veryinteresting tool to study the overlap between harged and neutral parti les,and perhaps it will let us to separate and subtra t the neutral ontributionto the luster mat hed to one tra k.The information about the ells whi h form the TopoClusters (en-ergy, position...) is now available in the root ntuple variables. So, it willbe possible to analyse the transverse energy deposited in the ells insideTopoClusters and study the best ut in ET of ell with and without noise4.Finally, a ROOT ma ro pa kage for ATLAS Calorimeter Event Dis-plays[12℄ , is also available in this release5, and it allows to see the distri-bution of the energy in the ells inside the TopoCluster and the possibleoverlapping between lusters.3Figure taken from TWiki Web page for Topologi alClustering, made by S. Menke.4Unfortunately, in 8.2.0 release the TopoCluster pa kage didn�t work with the optionDoNoise equal False, so it wasn�t possible to generate ntuples without noise. Anyway, wetry to see how the energy resolution gets worse when the ele troni noise is in luded5CaloEventDisplay pa kage is available in S. Menke Personal web page:http://www.mppmu.mpg.de/ menke/

9.6. CaloTopoCluster in 8.2.0 Release 1879.6.1 First luster splitter in CaloRe The �rst version of a topologi al luster splitting tool is now available.The tools name is CaloTopoClusterSplitter[13℄ and falls in the maker-type ategory of the new lustering tools in CaloRe . It re- lusters existing lus-ters around lo al maxima in energy density in a topologi al manner similarto the CaloTopoClusterMaker, it means, also based on Signal over Noisethresholds and topologi al neighbors.The Splitter split lusters based on lo al maxima of the lusters fromenergy density values. The ells in a luster are sear hed for lo al maximaby means of energy density. The found lo al maxima are used as seeds fora topologi al lustering as in the CaloTopoClusterMaker. The spe ial aseof zero thresholds for neighbors and ells is used su h that all ells in theparent luster will be re- lustered.So, the lassi� ation done by CaloTopoClusterSplitter requires identi�- ation of \Hot-Spots", needed to split lusters around lo al maxima in realphysi al observables. Given the large number of variations in terms of noiseand volumes a good hoi e seems to be the transverse energy density ET /V6, where V is the volume of the ell. The �gure 9.47 shows the ell volumes(mm3 on a log s ale) of all ells.

Figure 9.4: The ell volumes (mm3 on a log s ale) of all ells as a fun tion of alorimeterlayers ( olor ode) and � (x-axis).6Energy density is hosen instead of only transverse energy as seed for the ClusterSplit-ter be ause the granularity of the alorimeter hanges so often. Look e.g. at the Stripsand the Layer 2 ells in the EM - they di�er by an order of magnitude in volume and thustransverse energy by itself is rather meaningless if you onsider just one ell.7Figure taken from TWiki Web page for Topologi alClustering, made by S. Menke.

188 9. Clustering algorithms in ATLAS re onstru tion softwareThe tool a epts three parameters:� NeighborOption (default = "super3D")� NumberOfCellsCut (default = 4)� EtDensityCut (default = 500 MeV/600000mm3)The NeighborOption sele ts the type of neighbors looked for as in theCaloTopoClusterMaker. By default both take "super3D" - i.e. neighborsa ross all alorimeter systems, but it might be useful to restri t the lo almaxima in the splitting to separate systems ("all3D") or even separate layers("all2D").TheNumberOfCellsCut spe i�es how many neighbor ells a given ellhas to have in the parent luster in order to be quali�ed as lo al maximum andidate.All lo al maximum andidates must also pass the EtDensityCut spe -ifying the minimum ET divided by the volume of the ell in order to bea epted as lo al maximum. The default value orresponds to a transverseenergy of 500 MeV in a typi al LArEM barrel ell in the se ond layer.CaloTopoClusterSplitter re- lusters ea h existing luster into one or more lusters:- around the lo al maxima above a seed threshold- with same (or di�erent) topologi al neighbors- without ell or neighbor thresholds- keeping lo al maxima in separate lusters- with seed ells ordered in � in every iterationSo, the re- lustering works as in the normal topo luster maker, but all ells are a epted without thresholds and at ea h iteration the urrent setof seed ells is ordered in energy density su h that ells with higher energydensity are more likely to attra t a neighbouring ell.A further di�eren e to the normal topologi al lustering is that proto- lusters ontaining a lo al maximum an never be merged. Therefore thenumber of lusters resulting from the splitting of the parent is determinedby the number of lo al maxima found in the luster8. Thus the total energy8If no lo al maximum was found, the parent luster will be left un-altered in the luster ontainer. If parts of the original luster are not onne ted with lo al maximum ontainingparts (di�erent luster algorithm or di�erent neighbor option) all ells of a luster in this ategory are in luded in a rest- luster and added to the new luster list.

9.6. CaloTopoCluster in 8.2.0 Release 189of all lusters and the number of ells of all lusters should be the samebefore and after splitting.No sharing of ells between lusters is introdu ed at this point, but thismight hange in the future. The tool is enabled in the default python �leCaloTopoClusterjobOptions.

190 9. Clustering algorithms in ATLAS re onstru tion software9.7 Appendix 1: Code of CaloTopoClusterMakerCaloTopoClusterMaker in Athena 8.2.0 is a CaloClusterMakerTool whi h isused by the generi CaloClusterMaker top algorithm. The way to work ofthis algorithm is shown next:1. loop over all CaloCells in the given CaloCellContainer(s)a) make a ve tor of ells above ell threshold with Identi�erHashas indexb) reate a proto- luster for ea h ell above neighbor threshold ) reate a list (mySeedCells) for ea h ell above seed thresholdand mark them used2. sort initial mySeedCells in E=�noise in des ending order3. loop over mySeedCellsa) loop over the neighbors of the urrent elli. for neighbors above neighbor threshold merge proto- lusters;if not marked used do so and add to myNextCellsii. neighbors below neighbor threshold not belonging to anyproto- luster are in luded in parent proto- luster4. set mySeedCells = myNextCells5. return to 3. if mySeedCells is not empty6. keep proto- lusters with at least one ell above seed threshold

9.8. Appendix 2: Code of Cluster Splitter 1919.8 Appendix 2: Code of Cluster SplitterCaloTopoClusterSplitter was released in CaloRe -02-02-19 in time for Athenarelease 8.2.0. CaloTopoClusterSplitter is a CaloClusterMakerTool like Calo-TopoClusterMaker, and it works in the following way to re- luster existing lusters around lo al maxima in energy density:1. loop over all CaloCell members of all previously made CaloClustersa) store all ells as potential neighbor ells for topologi al lustering;the parent luster is kept as a referen e su h that only ells withinthe same parent luster an be re- lustered togetherb) reate a proto- luster for ea h ell ) keep as seed ells those whi h are a lo al maxwith the default value: �T > 500 MeV/600000mm3 ,being �T> maxf�T ; neighborsg, and Nneighbors � 42. sort urrent seed ells in des ending order in �T and mark them used3. loop over the urrent seed ellsa) loop over the neighbors of the urrent seed elli. in lude the neighbor ell in urrent proto- luster if it is nota lo al max itself, does not belong to a proto- luster of size1, and does belong to the same parent lusterii. add the neighbor ell to the list of next seed ells if it is notmarked used and mark it used4. opy the list of next seed ells to the urrent list5. iterate (starting at step 2) until list of urrent seed ells is empty6. opy all ells of parent lusters not re- lustered in separate lusters(one per parent luster)7. remove all original CaloClusters and reate new CaloClusters from thelo al max proto- lusters and the rest proto- lusters

192 Referen es:Referen es:[1℄ Athena User and Developer Guide v.2.0 & Releaseshttp://atlas.web. ern. h/Atlas/GROUPS/SOFTWARE/OO/ar hite -ture/General/[2℄ ATLAS Collaboration: ATLAS Dete tor and Physi s Performan eTe hni al Design Report Vol 1, CERN/LHCC/99- 14, 25 May 1999.[3℄ e owRe pa kage: Energy Flow Re onstru tion in Athena (Dan Tovey)http://atlas.web. ern. h/Atlas/GROUPS/PHYSICS/JETS/EFLOWREC//e owre .htm[4℄ C. Iglesias, Re onstru ion de Jets mediante el algoritmo Energy Flowen ATLAS, talk in VII Jornadas de Fisi a de Altas Energia, XXIXReunion Bienal, Madrid, (2003).[5℄ C. Iglesias, M. Bosman, Study of jet omposition at parti le level andits impli ations for Energy Flow algorithms. ATL-SOFT-INT-2005-003,De 2004.[6℄ D. Green Energy Flow in CMS Calorimetry Fermilab-FN-0709S. Kunori (CMS Collaboration), Jet Energy Re onstru tion with theCMS Dete tor, In Pro eedings of the X Int. Conf in Calorimetry inPart.Phys., CALOR2002 Conferen e, Pasadena, (2002).D.Green et al., Energy ow obje ts and usage of tra ks for energy mea-surement in CMS, CMS NOTE 2002/036, Sept (2002).[7℄ ATLAS Calorimeter Performan e, CERN/LHCC/96-40, ATLAS TDR1, (1996).[8℄ S.Menke talks: Status of Topologi al Clustering, Software Performan eMeeting, LAr Week (CERN), 28. Jan 2004[9℄ S.Menke,Calibration of the BaBar ele tromagneti alorimeter withpi0s, BABAR-Note-528, Nov 2000.S.Menke O�ine Corre tion of Non-linearities in the BaBar ele tromag-neti alorimeter ele troni s, BABAR-Note-527, Nov 2000.[10℄ C.Iglesias talks: TiCal-IFIC Weekly Meetings (Valen ia, SPAIN), atmy personal web page: http://i� .uv.es/�iglesias[11℄ S.Menke Status of Topologi al Clustering re ent Re o-SoftwareChanges, Hadroni Calibration meeting, 13. May 2004, CERN

Referen es: 193[12℄ ROOT ma ro pa kage for ATLAS Calorimeter Event Displays, (Calo-EventDisplay.tar.gz), 06. June 2004. S. Menke Personal web page:http://www.mppmu.mpg.de/ menke/[13℄ S.Menke Topologi al Cluster Maker Splitter - HOWTO for athena8.2.0, JetRe Phone Meeting, 02. June 2004, CERN

194 Referen es:

Chapter 10Clustering for simulatedparti les at Very Low Energy10.1 Basi Idea of the analysisThis hapter shows a omparison among di�erent ways of re onstru tingthe lusters inside the ATHENA[1℄ framework of ATLAS[2℄: TopoCluster,Sliding Window luster, EGamma luster and di�erent one algorithms. Weshow how these lustering algorithms an be tuned to obtain the best energyresolution when re onstru ting very low energy parti les.The present results are based on single parti le samples of �0�s, ���s andneutrons, simulated with Geant3 during DC11 with energy between 1 and 30GeV and simulated with and without ele troni noise in the alorimeters2.Results in this note are obtained using 7.8.0 and 8.2.0 releases of the ATLASsoftware.The main idea of this analysis[3℄[4℄ is to ompare the di�erent lusteringalgorithms inside the ATHENA framework of ATLAS. The energy resolutionobtained will be studied in order to see the gain in resolution that we ouldobtain when Energy Flow Algorithm will be applied in the future.First the transverse energy deposited in all ells of the alorimeter isevaluated and onsidered as the \referen e Energy Flow", i.e., the best res-olution that ould be rea hed for the most sophisti ated algorithm takinginto a ount the whole transverse energy in all the alorimeter.1Events generated with Geant3 and high statisti s: 107 events, to test the simulation-re onstru tion hain.2Multiparti les samples with ele troni noise have been also used to study the e�e t ofthe overlap of parti les using Splitter tool with TopoClusters (see Appendix 2).195

196 10. Clustering for simulated parti les at Very Low EnergyThen, for neutral pions the \referen e Energy Flow" is ompared withthe one obtained by the di�erent algorithms whi h main features are thefollowing:� Sliding Window luster: the default value of the luster is 5x5 ell,but also will be he ked 3x5 and 3x7 ells.� EGAMMA luster: useful for the re onstru tion of lusters in theEM region of the alorimeter.� TopoCluster[5℄in EM: as we have seen, in this ase the luster hasnot a �xed size and it is built around a Seed Cell whi h has an energyabove a ertain threshold.� �R one around seed: the luster is re onstru ted from the ellsinside a one with a ertain value of its radius �R , where �R isde�ned as �R =q��2 +��2.On the other hand, for the ase of neutrons and harged pions, as theydeposited their energy in Tile Calorimeter as well as in the EM alorimeter,the EGAMMA lusters an not be used, be ause they don't re onstru tproperly this type of parti les. So, for neutrons the \referen e EnergyFlow" will be ompared with the evaluated by:� TopoCluster in EM and Tile: For 7.8.0 release in CaloTopoCluster,only has one luster in ea h subdete tor, so, the energy from Tile andEM alorimeter must be added to obtain the total energy.� �R one around seed: where the size of the radius must be biggerthan the one orresponding to neutral pions, be ause the shower of�+'s and neutrons is wider than for �0's.Finally, for harged pions,as they have asso iated tra ks, the \referen eEnergy Flow" will be ompared with the evaluated by:� TopoCluster in EM and Tile� �R one around seed� momentum of TRACKS, only al ulated by xKalman (be ause in7.8.0 release iPatRe didn't work).

10.1. Basi Idea of the analysis 197In order to �nd the best energy resolution and the larger amount ofenergy deposited inside the lusters, the tunning of the TopoClusters willbe performed to be more apropiate for very low energy parti les.In se tion 10.3, di�erent thresholds for the EM Noise will be he ked forthe re onstru tion of TopoClusters:� EM Noise = 10 MeV: Value of EM Noise lower than the realisti ase. This value is only useful for he king, be ause the study will bedone with very low energy (VLE) parti les.� EM Noise = 70 MeV: Fix value by default for EM alorimeter.� CaloNoiseTool=true: Pa kage with a model for the ele troni noise.using the default values for the thresholds of Seed ell (E=�noise = 30) andNeighbor ells (jE=�noisej = 3).In se tion 10.4, the thresholds of Seed ell and Neighbor ells will be hanged for lower thresholds:a) Seed ut = E=�noise = 6 and Neighbor ut = jE=�noisej = 3b) Seed ut = E=�noise = 5 and Neighbor ut = jE=�noisej = 2.5 ) Seed ut = E=�noise = 4 and Neighbor ut = jE=�noisej = 2In se tion 10.5, the luster ET will be re onstru ted from the ell ETinside a one. Di�erent strategies are followed for the di�erent type ofparti les:a) Neutral pions:{ The enter is � � � of EGamma luster: EGamma- one{ The enter is � � � of TopoCluster in EM al: Topo- one{ The enter is � � � of TRUTH generated �0's: TRUTH- oneb) Charged pions:{ The enter is � � � of TRUTH generated �+'s: TRUTH- one{ The enter is � � � of TRACK at 2nd layer: TRACK- one ) Neutrons:{ The enter is ��� of TRUTH generated neutrons: TRUTH- oneAt the begining, a one with �R <1.0 is used, be ause in this �rst onta tonly it is required to sele t the one algorithm with the best resolution.

198 10. Clustering for simulated parti les at Very Low EnergyBut in se tion 10.5.3 a smaller radius, di�erent for ea h type of parti ledepending on the nature of the shower, will be taken.For the re onstru tion of the lusters from neutral pions, we will used:- �R < 0:1- ��= 0.0875 ��=0.0375 : 7x3 ells- ��= 0.0625 ��=0.0375 : 5x3 ells- �R < 0:0375: 3x3 ells (to study very on entrate ET deposit)For the ase of harged pions and neutrons:- �R < 0:1- �R < 0:2- �R < 0:4The omparison of the best lustering algorithm will be arried out inthe se tion 10.6.Finally, from the se tion 10.7 the ele troni noise is in luded to studyits in uen e in the size of the TopoClusters and the ET resolution. Thesesamples were generated used the 8.2.0 release, whi h have several new apli- ations for the TopoClusters:- the luster is made a ross all alorimeters (EM+HEC+FCal+TCal)- ET and �-� of the ells whi h form the TopoClusters are availableThey allows us to study of the size of the luster and the energy distribu-tion in the di�erent alorimeters. These hara terist s will hange whenTopoCluster thresholds related to the ele troni noise are swithed on inse tion 10.7.410.2 Samples of single parti leDC1 samples of single parti les (simulated by D. Froidevaux3) have beenused in the analysis. Pions and neutron (the main omponents of jets) havebeen generated at very low transverse energy4, in order to understand theshape of the shower, the amount of energy deposited in ell and the overlapbetween harged and neutral parti les.First, samples with only one type of parti les have been used to generatewith Geant3 ROOT-tuples of 1000 events of:3The samples are lo ated at CASTOR area in: = astor= ern: h=user=f=froid=di e03=4This is the best range of energy to apply Energy Flow Algorithm, be ause at verylow pT the momentum resolution of tra king is better than the energy resolution of the alorimeters.

10.2. Samples of single parti le 199� �0's with pT = 1, 3, 5, 10 and 30 GeV. To understand the behavior ofphotons inside the EM alorimeter.� �+'s and neutrons with pT = 1, 3, 5, 10 and 30 GeV. To know moreabout the hadroni shower.at �xed pseudorapidity � = 0.3 ( alorimeter barrel) and � = 1.6. Next, there onstru tion of these 1000 parti les from the lusters will be arried outusing di�erent releases of ATHENA: 7.8.0 and 8.2.0, omparing the resultswith and without ele troni noise applied.10.2.1 Composition of the showersThe omposition of the shower of these samples of parti les is analyzed,i.e., the type of se ondary parti les that are generated when these parti lesintera t with the dete tor material.For �0's, we an see in the �gure 10.1 that the shower has only ele tro-magneti omponents (photons, ele trons and positrons), be ause neutralpions usually de ay to photons: �0 ! and then, photons produ e e+e�pairs. They deposit all their energy in EM Calorimeter.

Figure 10.1: Composition of the shower for the neutral pions at 5 GeV.On the other hand, the de ays of harged pions and neutrons are mu hmore ompli ated, and a more extensive variety of \se ondary parti les"is obtained, as the �gure 10.2 shows. Next, the main ontributions areexplained:� There is an important amount of baryons (protons and neutrons), thebiggest ontribution to the \se ondary parti les".{ Neutron beta de ay: n! pe+�

200 10. Clustering for simulated parti les at Very Low Energy� There are also leptons (ele trons and quarks) and photons as result ofthe de ay of pions:{ �0 ! ,�0 ! e+e�.{ � ! e+ � + , � ! 3e+ �.{ Pion beta de ay: �+ ! �0 + e+ �, �+ ! e+ �.� The de ay ��! �� + � has been also analyzed but thereare only few of them, e.g. in the sample of 5 GeV neutronswe have only 12 �'s and 13 �'s5.{ KL ! �o , KL ! e+e�e+e�.{ KS ! �oe+e�, KS ! �+��e+e�.And these \se ondary parti les" deposit their energy in E.M. alorimeteras well as in the HAD alorimeter, due to their very low pT 6.

Figure 10.2: Composition of the shower for the harged pions at 5 GeV.5The �0 de ays to e+, e� and gamma ray by the e.m. intera tion on a time s ale� 1016 s. The �+'s have longer lifetimes � 2.6 x 10�8 s: may be Geant onsider them asstable parti les.6It is known that for high pT parti les, the energy of harged pions and neutrons isusually deposited only in the hadroni alorimeter

10.2. Samples of single parti le 201Total energy depositedFor the neutral pions, as there are only ele tromagneti parti les we expe thaving all the energy deposited in the E.M alorimeter. From the study ofthe energy resolution (PETopoEM=Egener), a Gaussian distribution entredin the value of energy for the generated parti les is obtained, but with a ertain width due to the u tuation of energy, as well as the resolution ofthe EM alorimeter (� 100%=pE).Nevertheless, for harged pions and neutrons the situation is di�er-ent. Although, as it's known for high pT parti les, the energy of hargedpions and neutrons is usually deposited only in the hadroni alorimeter,for the ase of very low energy, they also deposited their energy in the EM alorimeter (around 40-50%), as the table 10.1 shown. This deposited en-ergy in rease with the ET of the parti les. In this ase, the width of theGaussian of the PETopoEM=Egener distribution will be bigger be ause theresolution of the Hadroni alorimeter in ATLAS is worse (� 50%=pE).ET Charged pions Neutronsparti les ET in EM(%) ET in Tile (%) ET in EM (%) ET in Tile (%)1 GeV 84 16 66 343 GeV 70 30 57 435 GeV 62 38 56 4410 GeV 55 45 53 4730 GeV 47 53 49 51Table 10.1: Proportion of transverse energy deposited by harged pions and neutronsin EM and Tile Calorimeter inside TopoEM and TopoTile lusters using CaloNoiseTooland Seed ut=30 and Neighbor ut=3.So, in the ase of TopoClusters, for the study of the �0's only the energyfrom TopoCluster in EM will be sum, while for the study of the hargedpions and neutrons, we must add the energy from TopoCluster in EM andin Tile if we want to obtain the total energy.

202 10. Clustering for simulated parti les at Very Low Energy10.3 Thresholds for EM NoiseThe analysis is done using the 7.8.0 release of ATHENA and taking theusual thresholds for the Seed Cell and the Neighbor Cells inside the Calo-TopoCluster pa kage, it means that the values used by default for parti leswith normal energy are:� for Seed Cell: Seed ut = E=�noise = 30� for Neighbor ells: Neighbor ut = jE=�noisej =3In order to �nd the best energy resolution and the larger amount of energydeposited inside the lusters, di�erent thresholds for the EM Noise will be he ked for the re onstru tion of TopoClusters:� EM Noise = 10 MeV: Value of EM Noise lower than the realisti ase. This value is only useful for he king, be ause the study will bedone with very low energy (VLE) parti les.� EM Noise = 70 MeV: Fix value by default for EM alorimeter.� CaloNoiseTool=true: Pa kage with a model for the ele troni noise.10.3.1 Multipli ity of TopoClustersIn an important amount of events the multipli ity is zero for all parti lesdue to the high number of TopoClusters badly de�ned, so it seems to bene essaty to hange the Thresholds.Anyway, the table 10.2 shows the proportion (in %) of the existen eof 0, 1, 2 and more than 2 TopoClusters in ea h event. The multipli ityof TopoCluster for harged pions and neutrons is between 1 and 2. Themultipli ity equal to 2 indi ates when the parti le has deposited its energyin both LArEM and Tile Calorimeter giving rise to TopoEM and TopoTile lusters. The multipli ity tends to be over 2 as ET of parti les in reasebe ause in this ase the \se ondary parti les" of the hadroni shower extendfurther as more energeti they are.

10.3. Thresholds for EM Noise 203ET (TopoClusters �+'s) TopoClusters (neu)parti les 0 1 2 >2 0 1 2 >21 GeV 92 8 0 0 93 7 0 03 GeV 63 34 3 0 63 34 3 05 GeV 41 50 8 1 44 47 8 110 GeV 16 65 16 3 15 64 16 530 GeV 0.5 42 41 16.5 0.5 35 46 18.5Table 10.2: Multipli ity of TopoClusters for �+'s and neutrons from 1 to 30 GeV, usingEMNoise= 70 MeV and the default value for Seed ut (E=�noise = 30) and Neighbor- ut (jE=�noisej = 3). Proportion (in %) of the existen e of 0, 1, 2 and more than 2TopoClusters in ea h event.For neutral pions, the table 10.3 shows the multipli ity of TopoClusterand EGamma lusters from 1 to 30 GeV. It is possible to see how at 1 and3 GeV the TopoClusters algorithm does not work properly be ause it annot re onstru t any lusters. On the other hand, EGamma algorithm ismanaged to re onstru t the 60-70% of the lusters at 1-3 GeV. For longerenergies, the multipli ity of TopoClusters and EGamma lusters seems tobe around 1. This behavior will be orre t if the photons would be very lose one to ea h other, and the lustering algorithm onsiders them as onlyone luster7. ET TopoClusters (�0's) EGamma lustersparti les 0 1 2 >2 0 1 2 >21 GeV 100 0 0 0 2 62 35 13 GeV 100 0 0 0 0 74 20 65 GeV 96 4 0 0 0 78 14 810 GeV 0 82 14 4 0 82 14 530 GeV 0 92 6 2 0 90 8 2Table 10.3: Multipli ity of TopoCluster for �0's and EGamma lusters from 1 to 30GeV, using EMNoise= 70 MeV and the default value for Seed ut (E=�noise = 30) andNeighbor ut (jE=�noisej = 3). Proportion (in %) of the existen e of 0, 1, 2 and more than2 TopoClusters in ea h event.7This supposition will be analyzed in Appendix 1 in a deeper study of the angle betweenthe two photons of the �0 de ay ( �0 ! ).

204 10. Clustering for simulated parti les at Very Low Energy10.3.2 Number of TopoClusters with di�erent EM NoiseThe �gures 10.3 and 10.4 show the number of TopoClusters using thedi�erent values of EM Noise, for �+'s, neutrons and �0's respe tively.In general, there is a low eÆ ien y of TopoClusters mainly at 1, 3 and5 GeV. This eÆ ien y is even smaller in the ase of neutral pions, where,by ontrast, EGamma lusters are de�ned always for all the range of theparti le energy.

Figure 10.3: Number of TopoCluster for �+'s and neutrons, using EM Noise=10 MeV(red), EM Noise=70 MeV (green) and CaloNoiseTool (blue).For harged pions and neutrons, the best result is for EM Noise=10MeV, but this isn't a realisti ase. The multipli ity of TopoClusters issimilar for EM Noise=70 MeV and CaloNoiseTool, being slightly larger inthe last ase.

10.3. Thresholds for EM Noise 205

Figure 10.4: Number of TopoCluster for �0's, using EM Noise=10 MeV (red),EM Noise=70 MeV (green) and CaloNoiseTool (blue).For neutral pions, the multipli ity is mu h better applying CaloNoise-Tool:� with CaloNoiseTool, although at 1 GeV there is not TopoCluster de-�ned, around 50% are well-de�ned at 5 GeV� while using EM Noise=70 MeV, there are non-de�ned TopoCluster at1 and 3 GeV, and only around 40% at 5 GeVSo, the rest of the analysis with TopoClusters will be done using theCaloNoiseTool pa kage for the treatment of the Noise in the alorimeter forthe three types of parti les. And the next point to study will be to �nd othervalues for the thresholds of Seed ell and the Neighbor ells whi h shouldallow a better re onstru tion of very low energy lusters.

206 10. Clustering for simulated parti les at Very Low Energy10.3.3 ET resolution with di�erent EM NoiseThe �gures 10.5, 10.6 and 10.7 show the ET resolution for TopoClusterwhere di�erent EM Noise thresholds are applied (10 MeV, 70 MeV andCaloNoiseTool) for harged pions, neutrons and �0's, respe tively. They are ompared with the resolution of the ET deposited in all the alorimeter ells,the pT resolution of tra ks and the EGamma lusters resolution.For harged pions, the best energy resolution omes from the pT of thetra ks, but it gets worse as the energy of the parti le in reases, as we expe t.Respe t to the alorimeter energy, the best resolution omes from the energydeposited in all the ells of the alorimeters, it is the maximum resolutionthat an algorithms ould get. Around 30 GeV, the alorimeter energy res-olution gets better than the pT resolution of the tra ks, that indi ates thelimit for the appli ation of the Energy Flow.

Figure 10.5: ET resolution for 1-30 GeV �+'s for TopoCluster with di�erent EM Noisethresholds applied (10 MeV, 70 MeV and CaloNoiseTool), the pT resolution of tra ks andthe resolution of the ET deposited in all the alorimeter ells.In general, the neutral pions (see �g. 10.7) have better resolutionthan �+'s and neutrons, be ause they deposit all the energy in the EM alorimeter with a resolution � 50% while the �+'s and neutrons share theenergy deposits between the EM and Tile alorimeter, with worse resolutionthe last one (� 100%).

10.3. Thresholds for EM Noise 207

Figure 10.6: ET resolution for 1-30 GeV neutrons for TopoCluster with di�erentEM Noise thresholds applied (10 MeV, 70 MeV and CaloNoiseTool) and the resolution ofthe ET deposited in all the alorimeter ells.The worst result is from neutrons (see �g. 10.6) at 1 GeV, be ause thistransverse energy is very similar to the value of the mass of neutron (mn �940 MeV). This is an intrinsi problem and we must deal with it during allthe analysis.The analysis for Sliding Window algorithm has been done also, but thesame results as for EGamma lusters have been always obtained, maybebe ause for 7.8.0 release the more ompli ated alibration whi h must beapplied to EGamma luster have not been still implemented.Respe t to TopoClusters, for �+'s and neutrons at 1, 3, 5 and 10 GeV,results have non-sense, the resolution in rease instead of de reasing with theET of the parti les, and for �0's, even there are not TopoClusters de�ned at1 and 3 GeV. Anyway, the best resolution8 omes from CaloNoiseTool.

8Ex epting the non-realisti ase of EM Noise=10 MeV

208 10. Clustering for simulated parti les at Very Low Energy

Figure 10.7: ET resolution for �0's from 1 to 30 GeV, where di�erent EM Noise areapplied for the TopoClusters (10 MeV, 70 MeV and CaloNoiseTool). Therefore we have al ulated the EGamma lusters resolution and the resolution of the energy deposited byall the ells in the alorimeter.Finally, for the ase of neutral pions, the energy resolution from TopoClus-ters is worse than EGamma lusters at 1, 3 and 5 GeV.So, it will be needed to do hanges in the re onstru tion of the TopoClus-ter, i.e., apply more appropriated thresholds for parti les with very low en-ergy (VLE) instead of normal energy.

10.3. Thresholds for EM Noise 20910.3.4 Mean value of ET lusterETgenerated with di�erent EM NoiseThe relation ET lusterETgenerated gives us the amount of transverse energy depositedinside the lusters from the total generated energy, and it shows the lossin energy due to the dete tor hara teristi s as well as the eÆ ien y of the lustering algorithm.

Figure 10.8: Mean value of the ET lusterETgenerated ratio for �0's from 1 to 30 GeV, where dif-ferent EM Noise are applied for the TopoClusters (10 MeV, 70 MeV and CaloNoiseTool).Therefore we have al ulated the mean value of the EGamma luster energy and the meanvalue of the energy deposited by all the ells in the alorimeterThis ratio for all the alorimeter ells indi ates the maximum ET de-posited in all ells of the alorimeter for ea h type of parti les respe t tothe total energy deposited in the dete tor. This value is below 1, so thetransverse energy inside ells is smaller than the generated energy, as it isexpe ted:a) For �0's be ause the EM alorimeter is a sampling alorimeter, soonly a part of the energy is deposited in the a tive layers, whi h givesrise to the so- alled \intrinsi sampling u tuation" (negligible ontributions at high energies, where the onstant term dominates theET resolution).b) For harged pions and neutrons the mean value is even more far from1 than in the ase of �0's, be ause ATLAS has a non- ompensatedhadroni alorimeter and they deposit their energy between EM andHAD Calorimeter.

210 10. Clustering for simulated parti les at Very Low Energy

Figure 10.9: Mean value of the ET lusterETgenerated ratio for �+'s and neutrons from 1 to 30GeV, where di�erent EM Noise are applied for the TopoClusters (10 MeV, 70 MeV andCaloNoiseTool). Therefore we have al ulated the mean value of the tra k energy withxKalman for �+'s and the mean value of the energy deposited by all the ells in the alorimeterRespe t to TopoClusters, the best results for the mean value of ET lusterETgenerated(again ex epting the ase of 10 MeV) omes from CaloNoiseTool. Never-theless there is a loss in the deposited energy due to the low multipli ity ofthese lusters, mainly at very low energies (1 ,3 and sometime 5 GeV) andthe behavior at these low energies is di�erent to the expe ted (the meanvalue de reases with the energy instead of in reasing).

10.4. Lower thresholds for Seed and Neighbor ells 21110.4 Lower thresholds for Seed and Neighbor ellsFor the time being, the default values for the thresholds of Seed ell(E=�noise = 30) and Neighbor ells (jE=�noisej = 3) have been used in theanalysis of the TopoCluster. In view of the last results, it will be needed to hange these uts to lower threshold:a) Seed ut = E=�noise = 6 and Neighbor ut = jE=�noisej = 3b) Seed ut = E=�noise = 5 and Neighbor ut = jE=�noisej = 2.5a) Seed ut = E=�noise = 4 and Neighbor ut = jE=�noisej = 210.4.1 Multipli ity of TopoClustersWith the appli ation of these new thresholds in Seed ut and Neighbor ut,the problem with the non-de�nition of the TopoClusters at very low energieshas disappeared.As it shown in table 10.4 for harged pions and neutrons, the proportionof lusters with multipli ity zero is almost negligible9. In both ases, themultipli ity of the TopoClusters10 is between 1 and 2, and tends to be over2 as the energy of the parti les in reases.ET TopoClusters(�+'s) TopoClusters(neu)parti les 0 1 2 >2 0 1 2 >21 GeV 22 50 24 4 62 34 4 03 GeV 1 20 45 34 8 50 32 105 GeV 5 10 40 34 1 30 38 3110 GeV 0 5 40 55 0 19 28 5330 GeV 0 1 35 64 0 12 22 65Table 10.4: Multipli ity of TopoCluster for �+'s and neutrons from 1 to 30 GeV, usingCaloNoiseTool and Seed ut=4 and Neighbor ut=2. Per entage of the existen e of 0, 1, 2and more than 2 TopoClusters in ea h event.For the ase of neutral pions, when the default value for the SeedCutand NeighborCut were used, TopoClusters didn't work at 1 and 3 GeV. Butnow, using these lower thresholds, the per entage of multipli ity zero is verylow and the numbers are very similar to the EGamma ones, as the table10.5 shows.9Only there are some problems at 1 GeV for the ase of neutrons, be ause of thesimilarity between this range of energy and the mass of the neutrons.10The multipli ity 2 indi ates when the parti le has deposited its energy in both LArEMand Tile alorimeters giving rise to TopoEM and TopoTile lusters.

212 10. Clustering for simulated parti les at Very Low EnergyET TopoClusters (�0's) EGamma lustersparti les 0 1 2 >2 0 1 2 >21 GeV 7 66 26 1 2 62 35 13 GeV 0 30 63 7 0 74 20 65 GeV 0 62 30 8 0 78 14 810 GeV 0 82 14 4 0 82 14 530 GeV 0 92 6 2 0 90 8 2Table 10.5: Multipli ity of TopoCluster for neutral pions and EGamma lusters from 1to 30 GeV, using CaloNoiseTool and Seed ut=4 and Neighbor ut=2. Per entage of theexisten e of 0, 1, 2 and more than 2 TopoClusters in ea h event.10.4.2 Number of TopoClusters with lower thresholdsAs it is possible to see in 10.10, with Seed ut = 4 and Neigh ut = 2the TopoClusters for harged and neutral pions are almost ompletelyde�ned, even at 1 GeV:� 779 TopoClusters for �+'s� 934 TopoClusters for �0'sSo, using these thresholds the low eÆ ien y of TopoClusters for these singleparti les at 1, 3 and 5 GeV has been pra ti ally eliminated.

Figure 10.10: Number of TopoCluster for �+'s and �0's using EM Noise=10 MeV (red),EM Noise=70 MeV (green), CaloNoiseTool with SeedCut=30 (blue), with SeedCut=6(bla k), with SeedCut=5 (pink) and with SeedCut=4 (light blue).

10.4. Lower thresholds for Seed and Neighbor ells 213

Figure 10.11: Number of TopoCluster for neutrons using EM Noise=10 MeV (red),EM Noise=70 MeV (green), CaloNoiseTool with SeedCut=30 (blue), with SeedCut=6(bla k), with Seed ut=5 (pink) and with Seed ut=4 (light blue).The worst result is for neutrons at 1 GeV, but it improves with the hanged uts, as the �g. 10.11 shows:� SeedCut = 6: 299 TopoClusters for 1 GeV neutrons� SeedCut = 5: 376 TopoClusters for 1 GeV neutrons� SeedCut = 4: 468 TopoClusters for 1 GeV neutronsOnly the 50% of the TopoClusters are de�ned for neutrons at 1 GeV in thebest ase, but anyway the problem with the mass of neutron at 1 GeV willbe always present.

214 10. Clustering for simulated parti les at Very Low Energy10.4.3 Deposited EnergyFor �+'s and neutrons (see table 10.6), hanging the Seed ut value from30 to 4, a large in rease in the deposited energy is obtained, mainly at 1-5GeV (e.g. the ET deposited using Seed ut=4 is almost the double that usingSeed ut=30.)11. Charged pions (% of ET )ET TopoClusters All Calo(GeV) Seed ut=30 Seed ut=6 Seed ut=5 Seed ut=4 Cells1 5.1 26.1 32.5 41.1 65.73 21.7 49.3 53.5 57.4 72.95 35.6 59.5 62.2 65.1 76.110 59.5 72.7 74.4 76.1 83.430 77.1 79.7 80.5 81.3 84.6Neutrons (% of ET )ET TopoClusters All Calo(GeV) Seed ut=30 Seed ut=6 Seed ut=5 Seed ut=4 Cells1 4.2 11.8 14.0 16.7 28.43 17.2 33.5 36.3 39.3 51.35 25.5 44.1 46.7 49.8 60.410 46.8 60.6 62.5 64.2 72.230 72.2 75.2 76.0 77.0 81.1Table 10.6: Fra tion of energy deposited in alorimeter for Charged pions and Neutronsfrom 1 to 30 GeV, for TopoClusters with di�erent thresholds (E=�noise) for Seed Cell andNeighbor ells and for all the alorimeter ells.Neutral pions (% of ET )ET TopoClusters Egamma All Calo(GeV) Seed ut=30 Seed ut=6 Seed ut=5 Seed ut=4 lusters Cells1 0.0 52.8 59.8 67.8 76.8 87.13 36.4 83.7 85.2 86.6 81.1 95.25 76.2 90.4 91.0 91.8 91.0 96.810 93.4 94.6 95.0 95.4 95.3 98.430 97.5 97.7 97.8 97.9 97.8 99.5Table 10.7: Fra tion of energy deposited in alorimeter for Neutral pions from 1 to 30GeV, for TopoClusters with di�erent thresholds (E=�noise) for Seed Cell and Neighbor ells, for Egamma lusters and for all the alorimeter ells.11For neutrons this improvement is not so large at 1 GeV, be ause there are very few luster de�ned at this energy due to the fa t that ET is similar to the mn

10.4. Lower thresholds for Seed and Neighbor ells 215For �0's, using SeedCut=30 there are no TopoClusters at 1 GeV, butwith these new values for the threshold of SeedCell up to 67% of the energyis deposited inside the lusters at 1 GeV, as is shown in the table 10.6. Forthe rest of the ranges, the values for the deposited energy are very similarto the EGamma lusters and ompetitive respe t to the total energy in allthe alorimeter ells.In any ase, the use of these new values for the threshold in Seed andNeighbor ell re onstru ts better the lusters ome from VLE parti les andbe ause gives a larger value of the energy deposited inside the lusters.10.4.4 ET resolution results with lower thresholdsThe �gures 10.12 and 10.13 show the ET resolution for 1-30 GeV �+'s andneutrons respe tively, where di�erent thresholds (E=�noise) for Seed Cell andNeighbor ells of the TopoClusters are applied (Seed ut = 30, 6, 5 and 4 orrespond to Neighbor ut = 3, 3, 2.5 and 2). Therefore we have al ulatedthe momentum resolution of the tra ks with xKalman for �+'s and theresolution of the energy deposited in all the ells in the alorimeter (CELL).The best results for all parti les omes from Seed ut=4 and Neigh ut=2.

Figure 10.12: ET resolution for 1-30 GeV �+'s, whit di�erent thresholds for TopoClus-ters, the pT resolution of the tra ks and the resolution of the ET in all the ells.Using these new uts for Seed and Neighbor ells the behavior of TopoClus-ters ET resolution is more similar to the resolution of the ET deposited byall the ells in the alorimeter (CELL), it means loser to ideal ase.

216 10. Clustering for simulated parti les at Very Low Energy

Figure 10.13: ET resolution for 1-30 GeV neutrons, whit di�erent thresholds forTopoClusters and the resolution of the ET deposited in all the ells.On the other hand, the �gure 10.14 shows the ET resolution for �0's from1 to 30 GeV, where di�erent thresholds (jE=�noisej) for Seed Cell and Neigh-bor ells of the TopoClusters are applied. Therefore we have al ulated theEGamma lusters resolution and the resolution of the energy deposited byall the ells in the alorimeter. Using any of these new uts for TopoClus-ters, the energy resolution is even better than the resolution from EGamma lusters, so there is a huge gain in resolution.

Figure 10.14: ET resolution for 1-30 GeV �0's, with di�erent thresholds for TopoClus-ters, the EGamma lusters resolution and the resolution of the ET deposited in all the ells.

10.4. Lower thresholds for Seed and Neighbor ells 21710.4.5 Mean value of ET lusterETgenerated with lower thresholdsThe �gures 10.17, 10.15 and 10.16 show Mean value of the ET lusterETgenerated ra-tio for 1-30 GeV �0's, �+'s and neutrons respe tively. With the appli ationsof these new uts, there is a high in rease in the transverse energy depositedinside TopoClusters respe t to SeedCut = 30. Now the value of ET lusterETgeneratedis approa hing to 1 as the energy of the parti le in reases. The best resultfor all types of parti les omes form SeedCut = 4 and NeighCut = 2.

Figure 10.15: Mean value of the ET lusterETgenerated ratio for 1-30 GeV �+'s, whit di�erentthresholds for TopoClusters, pT resolution of the tra ks and ET resolution in all the ells.

Figure 10.16: Mean value of the ET lusterETgenerated ratio for 1-30 GeV neutrons, whit di�erentthresholds for TopoClusters and ET resolution in all the ells.

218 10. Clustering for simulated parti les at Very Low EnergyFor �0's, ex ept at 1 GeV, the energy deposited inside TopoClusters forall ases is larger than the deposited in EGamma lusters.

Figure 10.17: Mean value of the ET lusterETgenerated ratio for 1-30 GeV �0's, with di�erentthresholds for TopoClusters, the EGamma lusters resolution and the resolution of theET deposited in all the ells.These new uts are eÆ ient with the present samples without Ele troni Noise. When later (with 8.2.0 release) the noise will be applied, the utsmust be hanged in order to avoid olle t noise in the re onstru tion of the luster energy.

10.4. Lower thresholds for Seed and Neighbor ells 21910.4.6 Possible double ountingThe �gure 10.18 shows the lineal and logarithmi distributions of ET lusterET ellfor the TopoClusters, sliding window and EGamma luster. This ratio re-lates the ET deposited inside ea h type of luster (Topo, SW or EGamma)with the total ET deposited in the whole of the alorimeter ells, it means,the maximum value for the ET deposited. When this ratio is larger than1, it means that the ells are used more than on e in the re onstru tion ofthe luster energy. In TopoClusters this fa t does not happend, while thisseems to be pla e in the Sliding Window and EGamma luster ases12

Figure 10.18: Lineal and logarithmi distributions of ET lusterET ell for TopoClusters,EGamma or Sliding Window lusters.12This re e ts a failure in the development of the ell loop inside these algorithms: the ells must be removed from the list after they pass to form a luster.

220 10. Clustering for simulated parti les at Very Low Energy10.5 Cone algorithms for VLE parti lesThe ET of the lusters will be re onstru ted from the ET of the all ellsinside a one with a ertain value of its radius �R , where �R is de�nedas �R =q��2 +��2. Di�erent strategies to hoose the enter of the oneare followed for the di�erent type of parti les:a) Neutral pions:{ The enter is � � � of EGamma luster: EGamma- one{ The enter is � � � of TopoCluster in EM al: Topo- one{ The enter is � � � of TRUTH generated �0's: TRUTH- oneb) Charged pions:{ The enter is � � � of TRUTH generated �+'s: TRUTH- one{ The enter is � � � of TRACK at 2nd layer: TRACK- one ) Neutrons:{ The enter is ��� of TRUTH generated neutrons: TRUTH- oneIn prin iple, it is used a one with �R <1.0, be ause in this �rst onta tonly it is required to sele t the one algorithm with the best resolution.10.5.1 Rare behavior of Cone Algorithms for VLE parti lesFor �0's, there are tails in the left side of the E lusterEgenerated distribution at 1and 3 GeV for EGamma- one and Topo- one. The �gure 10.19 shows theE lusterEgenerated distribution at 1 GeV for EGamma- one and Topo- one.Figure 10.19: E lusterEgenerated ratio at 1 GeV for EGamma- one (left) and Topo- one (right).

10.5. Cone algorithms for VLE parti les 221Seeing the multipli ity of lusters for these ases, we an extra t thatthe tails ome from a missing photon, be ause the ones in these ases are entred at one photon and the other is outside the one (due to the fa t thatat VLE, photons from the de ay of �0's are emitted with a larger angle).On the other hand, for �+'s, as it an be seen in �gure 10.20, there is adeviation of �� at 1 and 3 GeV for the ase of the one entered in � � �of TRUTH generated �+'s (TRUTH- one):� at 1 GeV, �� distribution is entred at 0.5.� at 3 GeV, �� distribution is entred at 0.2.while that for the TRACK- one the �� distribution is always entred atzero. Nevertheless, over 5 GeV, the �� distribution is entred at zero inboth ases. So, it seems that THUTH variables are not well de�ned for verylow energies.

Figure 10.20: �� distributions in TRUTH- one and TRACK- one at 1 and 3 GeV.

222 10. Clustering for simulated parti les at Very Low Energy10.5.2 Preliminary on lusions about Cone AlgorithmThe �gures 10.21 and 10.22 show the ET resolution for 1-30 GeV �+'s and�0's, where di�erent one algorithm are applied (always with a radius �R =0:1). For �0's, the one is entered in the ��� of the tra ks (TRACK- one)and of the truth parti le (TRUTH- one). For �0's the one is entered in the��� of the EGAMMA luster, the TopoEM luster and the truth parti les.

Figure 10.21: ET resolution for 1-30 GeV �0's, where di�erent one algorithm areapplied (always with �R = 0:1).The best ET resolution for �+'s orresponds to the TRUTH- one, butthere are problems with the deviation of �� for VLE. Respe t to the �0's,theTRUTH- one gives the best re onstru tion to the luster energy, as well asthere are not tails in E lusterEgenerated distribution.

Figure 10.22: ET resolution for 1-30 GeV �+'s, where di�erent one algorithm areapplied (always with �R = 0:1).

10.5. Cone algorithms for VLE parti les 223Taking into a ount these results and the problems derivated to thebefore \rare behaviors", in the next analysis, it will be used as one algorithmfor the re onstru tion of luster from VLE parti les:� For �+'s: the TRACK- one� For �0's and neutrons: the TRUTH- one10.5.3 �R de�nitions for one algorithms for VLE parti lesUsing a one with a radius �R around 1, it is taken into a ount more thanone shower in the same luster. So it will be needed to de�ne a smallerradius, di�erent for ea h type of parti le depending on the nature of theshower.The radius for neutral pions are extra ted from the \Calorimeter Per-forman e" analysis where the luster, for parti les with low energies (E<100 GeV), are taken with sizes of the order of:� for un onverted photons: 5x3 ells (� �R < 0:073)� for onverted photons and ele trons: 7x3 ells (� �R < 0:095)Following these studies, in this analysis for the re onstru tion of the lustersfrom neutral pions, we will use:- �R < 0:1- ��= 0.0875 ��=0.0375 : 7x3 ells- ��= 0.0625 ��=0.0375 : 5x3 ells- �R < 0:0375: 3x3 ells (to study very on entrate ET deposit)For the ase of harged pions, the information has been found in LArTestBeam analysis, using there: 7x7 ells, 9x7 ells and 11x11 ells for there onstru tion of lusters. In this se tion, we apply the next value to theradius of the one:- �R < 0:1- �R < 0:2- �R < 0:4Finally, for neutrons, as their shower is as wide as the harged pions,the same values for �R will be he ked.

224 10. Clustering for simulated parti les at Very Low Energy10.5.4 ET resolution from one algorithms for VLE parti lesThe �gure 10.23 let us to ompare the energy resolution for the di�erentvalue of �R for harged hadrons. The best results ome from TRACK- one with �R < 0:4, but with �R < 0:2 also a good resolution is obtainedand it allows a better de�nition of the shower of only one pion.

Figure 10.23: ET resolution for 1-30 GeV �+'s, whith di�erent one algorithms:TRACK- one and TRUTH- one are al ulated with �R = 1.0, 0.4, 0.2 and 0.1.On the other hand, for neutrons (see �g.10.24), the best energy resolu-tion using TRUTH- one is with �R < 0:4, but applying the value �R < 0:2,the resolution is suÆ iently good. In both ases, the radius �R < 0:1 is tooestri t to de�ne hadroni parti les.

Figure 10.24: ET resolution for neutrons from 1 to 30 GeV, where the one algorithm(TRUTH- one) is al ulated with �R = 1.0, 0.4, 0.2 and 0.1.

10.5. Cone algorithms for VLE parti les 225In the �gure 10.25 the ET resolution and the Mean value of the ET lusterETgeneratedratio for neutral pions are plotted. The energy resolution using TRUTH- one with the radius �R < 0:1 is the best. The lusters re onstru ted with7x3 and 5x3 ells gives us a good resolution but not enough13. Finally, theresults of the energy resolution from 3x3 ells are very bad14.

Figure 10.25: ET resolution (top) and Mean value of the ET lusterETgenerated ratio (bottom) for�0's from 1 to 30 GeV, where the one algorithm (TRUTH- one) is al ulated with �R= 1.0 and 0.1, as well as de�ning lusters sizes of 7x3, 5x3 and 3x3 ells.In the next analysis, the values of �R whi h will be used in the one-algorithm for the re onstru tion of lusters from VLE parti les will be:- For harged pions, the TRACK- one with �R < 0:2- For neutrons, the TRUTH- one with �R < 0:2- For neutral pions, the TRUTH- one with �R < 0:113They ould be useful when ele troni noise will be applied.14So they won't be used in the next analysis, it only have been studied to he k thepossibility of a very on entrate deposit of energy for VLE parti les.

226 10. Clustering for simulated parti les at Very Low Energy10.6 Comparison of Cone-algorithms with TopoClus-ter and EGamma analysisThe �gures 10.26, 10.27 and 10.28 allow to ompare the best result of ETresolution using one algorithms with the TopoClusters of di�erents thresh-olds and with the ET resolution from the deposited energy in all the ells(pink line). In the ase of �0's EGamma luster is also in luded (yellowline).For harged hadrons, the best TopoCluster results is obtained usingthe thresholds SeedCut=4 and NeighCut=2 (dark blue line), as it is possibleto see in 10.26. Nevertheles, the TopoCluster algorithm gives worse energyresolution than any of the two one algorithms: TRACK- one with �R =0.2 (grey line) and TRUTH- one with �R = 0.4 (bla k line), very lose oneto ea h other, and with better energy resolution mainly at 1-5 GeV.

Figure 10.26: Comparison of ET resolution of the best one algorithms with the rest of lustering algorithms, for 1-30 GeV harged pions. The best algorithms are TRACK- onewith �R = 0.2 (dark blue line in the �gure) and TRUTH- one with �R = 0.4 (bla kline), very lose one to ea h other.On the other hand, the �gure 10.27 shows the di�erent result of ETresolution for neutrons. The TRUTH- one with radius �R < 0:2, is thebest algorithm in general15, but TopoCluster with Seed ut=4 and Neigh-bor ut=2 is very near and it is better at 1 and 3 GeV.Finally, for neutral pions (see �g. 10.28), the TRUTH- one with�R < 0:1 give the best energy resolution in general, but TopoCluster withSeed ut=4 and Neighbor ut=2 has again very lose results and even at 115At 1 GeV, it has a worse behaviour due to the �� deviation.

10.6. Comparison of Cone-algorithms with TopoCluster and EGamma analysis227

Figure 10.27: Comparison of ET resolution of the one algorithm with the rest of lus-tering algorithms for 1-30 GeV neutrons. The best algorithm is TRUTH- one (�R <0.2).GeV a better energy resolution is obtained using it. EGamma lusters giveworse results, in general, than TopoCluster and TRUTH- one, but it givesthe best resolution of all at 1 GeV.

Figure 10.28: Comparison of ET resolution of the one algorithm with the rest of lustering algorithms, for 1-30 GeV �0's. The best algorithms is TRUTH- one (�R <0.1).It is possible to extra t from these senten es that the results from TopoClus-ter algorithm are very ompetitive for neutrons and �0's, and for �+'sTopoCluster is a good algorithm but not enough, for the time being. Itwill be needed to test the next versions of the CaloTopoCluster pa kage inthe newer release of Athena: 8.2.0.

228 10. Clustering for simulated parti les at Very Low Energy10.7 TopoClusters in 8.2.0 ReleaseAs we have seen in Chapter 9, the 8.2.0 release have several new apli ationsfor the TopoClusters[6℄. In the next se tions, the ones used will be:- the luster is made a ross all alorimeters (EM+HEC+FCal+TCal)- ET and �-� of the ells whi h form the TopoClusters are availableTherefore, now the ele troni noise is in luded, in order to ompare withthe previous ase and study the in uen e of the noise in the size of theTopoClusters and the ET resolution.10.7.1 Size of the TopoCluster: Number of ellsThe tables 10.8 and 10.9 show that for both, harged pions and neutrons,the majority of the ells in the TopoClusters ome from EM alorimeter .This per entage de reases when the energy of the parti les in reases andmore and more energy is deposited in TILE, be ause the parti les be omeenough energeti to rea h this alorimeter.ET Total Cells in EM (�+)parti les Cells Total (%) Pres Front Mid Ba k1 GeV 182 170 93 10 82 57 203 GeV 257 233 91 13 111 74 345 GeV 311 276 89 14 131 86 4510 GeV 380 330 87 16 154 99 6030 GeV 513 432 84 20 196 122 94ET Total Cells in TILE (�+)parti les Cells Total (%) A BC D1 GeV 182 11 7 8 8 33 GeV 257 24 9 13 8 45 GeV 311 35 11 18 14 610 GeV 380 50 13 23 19 930 GeV 513 81 16 35 32 13Table 10.8: Mean value of ells in TopoCluster for 1-30 GeV harged pions, usingCaloNoiseTool, Seed ut=4 and Neighbor ut=2. The 2nd olumn shows the total numberof ells in all alorimeter. The 1st table shows the total number of ells in the EM alorimeter, next to the values for the di�erent layers of this alorimeter (Presampler,Front, Middle and Ba k). The 2nd table shows the total number of ells in TILE, next tothe values in its samples (A, BC, D).

10.7. TopoClusters in 8.2.0 Release 229A large per entage of the ells in EM omes from the se ond layer:- the se ond layer (Front): �48-46% of the ell in EM- the third layer: Middle (�34-30% of the ell in EMSo, respe t to the total number of ells, the most of them are lo ated betweenthese 2nd and 3th layer of EM: �83-75% of the total ells.In TILE the �rst sample (Sample A) has the large ammount of ells, butwith an amount mu h smaller: �4-6% of the total ellsThe behavior in the alorimeters of the very low energy harged pions andneutrons is very di�erent to the high energeti parti les, and they intera tmostly in the EM alorimeter.ET Total Cells in EM (neu)parti les Cells Total (%) Pres Front Mid Ba k1 GeV 153 141 92 9 67 48 173 GeV 221 198 90 11 53 64 305 GeV 282 248 87 13 116 77 4210 GeV 378 325 86 16 149 96 6330 GeV 549 463 84 21 209 130 103ET Total Cells in TILE (neu)parti les Cells Total (%) A BC D1 GeV 153 12 8 7 7 33 GeV 221 23 10 12 9 45 GeV 282 34 13 16 13 610 GeV 378 53 14 25 21 830 GeV 549 86 16 39 34 13Table 10.9: Mean value of ells in TopoCluster for 1-30 GeV neutrons, using CaloNoise-Tool and Seed ut=4. The 2nd olumn shows the total number of ells in all alorimeter.The 1st table shows the total number of ells in the EM alorimeter, next to the valuesfor the di�erent layers of this alorimeter (Presampler, Front, Middle and Ba k). The 2ndtable shows the total ells in TILE, next to the values in its samples (A, BC, D).

230 10. Clustering for simulated parti les at Very Low EnergyRespe t to the �0's, in prin iple, they only hit in EM, so the ells ofTopoCluster must be all of them in this alorimeter. Nevertheless, in thetable 10.10 there is a di�eren e of 10 ells between the total number of ellall alorimeter and the total number of ells in EM. They ome from TILEand it ould be really ele troni noise not signal16 .On the other hand, the number of ells in the last layer of the EM alorimeter if mu h smaller for �0's than for harged pions and neutrons,be ause the �0's shower is lo ated in the �rst samples of EM and they donot get the TILE alorimeter.Finally, we an see as the behavior in the EM alorimeter at very lowenergies (1-10 GeV) is very similar for �0's and neutrons17. As both areneutral parti les we only an start to distinguish them from energies above10 GeV, when the neutrons have a spread of the shower (460 ells) biggerthan the �0's one (338 ells).ET Total Cells in EM (�0)parti les Cells Total Pres Front Mid Ba k1 GeV 197 187 12 96 62 173 GeV 267 253 16 133 82 215 GeV 284 275 18 146 87 2410 GeV 305 295 19 158 92 2630 GeV 350 338 20 180 25 33Table 10.10: Mean value of ells in TopoCluster for 1-30 GeV �0's, using CaloNoiseTooland Seed ut=4. The 2nd olumn shows the total number of ells in all alorimeter. The3th olumn shows the total number of ells in the EM alorimeter, next to the values forthe di�erent layers (Presampler, Front, Middle and Ba k).

16The number of ells in TILE is the same from 1 to 30 GeV and the ET deposited insidethese ells is very low (almost negligible). Therefore, this level of noise (similar energydeposited and similar number of ells de�ned) is also found in FCal and HEC alorimeters,where we don't expe t to have any signal for these parti les samples (be ause they havebeen generated with a pseudorapidity �= 0.3 ( alorimeter barrel) and �=1.6). So it isde�nitively ele troni noise.17The behaviour of �0's from 1-10 GeV in EM is also similar to the harged pions one,but it will be possible to distinguish them, asking for a mat hing tra k- luster in the aseof harged parti les

10.7. TopoClusters in 8.2.0 Release 231Geometry of the TopoClusterThe �gures 10.29 and 10.30 show the energy deposit of the ells whi hform the TopoClusters in the �-� map of the whole alorimeter system for 5GeV harged pions and �0's respe tively. It is possible to see that the �0'senergy is more lo alized, while the harged hadrons have a wither showerdevelopment.

Figure 10.29: Energy deposit of the ells whi h form the TopoClusters in the �-� mapof the whole alorimeter system for harged pions at 5 GeV.

Figure 10.30: Energy deposit of the ells whi h form the TopoClusters in the �-� mapin the EM alorimeter for neutral pions at 5 GeV.

232 10. Clustering for simulated parti les at Very Low Energy10.7.2 Study of the TopoCluster with more energyIn order to see if the energy from the generated parti les an be studiedfrom the energy inside the TopoClusters, in the next se tion we will analyzethe behavior of the TopoCluster with the maximum energy deposit ( alledthe \1st TopoClusters", be ause they are ordered by ET in the ode). Thenext TopoCluster in energy will be the \2nd TopoCluster".For the TopoClusters from harged hadrons, the table 10.11 showsthat the main ontribution to the ET omes from the �rst TopoCluster .This proportion in reases with the energy of the parti les.ET Total TopoClusters 1st TopoCluster (�+) 2nd TopoCluster (�+)parti les ET (MeV) ET (MeV) ET (%) ET (MeV) ET (%)1 GeV 1259 560.9 44.5 274.7 20.03 GeV 2654 1407 53.1 504.3 19.05 GeV 4196 2517 59.9 707.7 16.810 GeV 8641 6082 70.3 1169 13.530 GeV 25530 20370 79.8 2711 10.6Table 10.11: Mean value of the ET deposited in TopoClusters and the proportion (in%) respe t to the total ET deposited for the TopoCluster with the maximum energy (1stTopoClusters) and the next in energy (2nd TopoCluster) for �+'s using Seed ut=4.Respe t to the behavior in ea h alorimeter, the table 10.12 allows tosee that at 1-3 GeV �80% of the ET is deposited in the EM alorimeter, inboth 1st and 2nd TopoClusters.ET 1st TopoCluster (�+) ET 2nd TopoCluster (�+) ETparti les Calo (MeV) EM (%) Tile (%) Calo (MeV) EM (%) Tile (%)1 GeV 560.9 84.1 10.2 274.7 87.9 6.73 GeV 1407 70.4 29.6 504.3 82.9 14.05 GeV 2517 61.8 39.1 707.7 77.4 22.710 GeV 6082 53.5 51.3 1169 76.2 24.130 GeV 20370 41.8 59.8 2711 69.7 30.3Table 10.12: Mean value of the energy deposited in TopoClusters in EM and Tile alorimeter and the proportion (in %) respe t to the total energy deposited in all for theTopoCluster with the maximum energy (1st TopoClusters) and the next in energy (2ndTopoCluster) for �+'s, using CaloNoiseTool and Seed ut=4.The energies in the EM alorimeter de rease with the energy of theparti les, at the same time in reases the energy in the Tile alorimeter.

10.7. TopoClusters in 8.2.0 Release 233The results of the TopoClusters from neutrons are very similar, as thetables 10.13 and 10.14 shown.ET Total TopoClusters 1st TopoCluster (neu) 2nd TopoCluster (neu)parti les ET (MeV) ET (MeV) ET (%) ET (MeV) ET (%)1 GeV 964 443.6 46.0 209.9 21.73 GeV 2059 1069 51.9 398.9 19.35 GeV 3437 1943 56.5 608.4 17.710 GeV 7493 5061 67.5 1074 14.330 GeV 24330 18470 75.9 3050 12.5Table 10.13: Mean value of the energy deposited in TopoClusters and the per entagewith respe t to the total energy deposited for the 1st and the 2nd TopoCluster for neutrons.ET 1st TopoCluster (neu) ET 2nd TopoCluster (neu) ETparti les Calo (MeV) EM (%) Tile (%) Calo (MeV) EM (%) Tile (%)1 GeV 443.6 75.8 12.6 209.9 84.5 6.13 GeV 1609 61.9 39.6 398.9 82.4 16.65 GeV 1943 56.1 45.2 608.4 76.8 21.710 GeV 5061 50.4 50.8 1074 73.3 27.530 GeV 18470 44.2 56.8 3050 68.3 32.9Table 10.14: Mean value of the ET deposited in TopoClusters in EM and Tile and theper entage with respe t to the total ET for the 1st and the 2nd TopoCluster for neutrons.Finally for neutral pions, the energy is deposited only in EM alorime-ter. The table 10.15 shows that the most important ontribution to theenergy omes from the �rst TopoCluster and this proportion in reases withthe energy of the parti les.ET Total TopoClusters 1st TopoCluster (�0) 2nd TopoCluster (�0)parti les ET (MeV) ET (MeV) ET (%) ET (MeV) ET (%)1 GeV 1436 659.8 45.9 282.5 19.63 GeV 3427 2133.1 62.2 688.2 20.15 GeV 5414 3712 68.5 1113.4 20.610 GeV 10380 8035 77.4 1959.6 18.830 GeV 30290 28170 93.0 2813 9.3Table 10.15: Mean value of the ET deposited in TopoClusters and the per entage withrespe t to the total ET deposited in EM for the 1st and the 2nd TopoCluster for �0's.Note that the re onstru ted energy from TopoCluster in this ase rea hesthe largest values with respe t to the energy of the generated parti les18.18Maybe the ele troni noise is in luded in the re onstru tion of the TopoClusters energy

234 10. Clustering for simulated parti les at Very Low Energy10.7.3 ET resolutions for TopoClusters in 8.2.0 ReleaseFor harged pions and neutrons the energy resolution of TopoCluster in8.2.0 release seems to improve (see tables 10.16 and 10.17). But we mustremember that in this ase, the ele troni noise is applied19, so the resolutionmay be worse due to the e�e t of the noise.ET ET Resolution Mean of ET lusterETgeneratedparti les 7.8.0 8.2.0 7.8.0 8.2.01 GeV 56.30 44.57 0.528 1.053 GeV 45.65 38.87 0.581 0.8715 GeV 33.82 30.65 0.652 0.84110 GeV 22.41 20.84 0.761 0.86430 GeV 13.91 13.36 0.813 0.851Table 10.16: Energy resolution and Mean value of ET lusterETgenerated in TopoClusters for 1-30GeV harged pions, using CaloNoiseTool and Seed ut=4 and Neighbor ut=2.ET ET Resolution Mean of ET lusterETgeneratedparti les 7.8.0 8.2.0 7.8.0 8.2.01 GeV 64.31 |- 0.357 |-3 GeV 57.54 46.19 0.406 0.6815 GeV 40.41 34.04 0.498 0.68710 GeV 23.98 22.43 0.643 0.74930 GeV 12.39 11.94 0.110 0.811Table 10.17: Energy resolution and Mean value of ET lusterETgenerated in TopoClusters for 1-30GeV neutrons, using CaloNoiseTool and Seed ut=4 and Neighbor ut=2.Seeing the results for neutral pions shown in the table 10.18, it is possibleto better understand what is happening. In the analysis, the thesholds of theTopoClusters related to the ele troni noise of the ells have been swi thedo� (the default a tion). It means that in the jobOption �le of the CaloReCpa kage related to CaloTopoCluster:- CellThresholdOnAbsEt = -1.0*MeV- NeighborThresholdOnAbsEt = -1.0*MeV- SeedThresholdOnEt = -1.0*MeVas well as the �0 signal19For this version CaloTopoCluster pa kage only worked putting doNoise=True.

10.7. TopoClusters in 8.2.0 Release 235It implies that all the energy deposited in the ells of the TopoCluster hasbeen take into a ount in the analysis: the energy omes from the generatedparti les, but also the energy of the ele troni noise ontributions.For this reason, the values of the ET lusterETgenerated are also larger in 8.2.0 thanin 7.8.0. And in the ase of �+'s some non-sense results are obtained:ET lusterETgenerated >1 means that the energy deposited in TopoCluster are evenbigger that the ET generated.ET ET Resolution Mean of ET lusterETgeneratedparti les 7.8.0 8.2.0 7.8.0 8.2.01 GeV 30.52 35.50 0.678 1.2173 GeV 12.66 20.72 0.866 1.1355 GeV 7.35 14.35 0.918 1.08410 GeV 4.02 7.77 0.954 1.03830 GeV 2.21 3.11 0.919 1.010Table 10.18: Energy resolution and Mean value of ET lusterETgenerated in TopoClusters for 1-30GeV neutral pions, using CaloNoiseTool and Seed ut=4.10.7.4 Topo lusters with the ele troni noise thresholdsSo, now the thesholds of the TopoClusters related to the ele troni noise20 of the ells are swithed on, with some values whi h taken into a ountthat we are working with very low energy parti les:- CellThresholdOnAbsEt = 10.0*MeV- NeighborThresholdOnAbsEt = 80.0*MeV21- SeedThresholdOnEt = 200.0*MeV2220The value of �noise per ell have been extra t from [7℄and [8℄.21The neighbor ells of the TopoClusters must be longer than the �noise per ell:- EM Presampler: �noise= 60-150 MeV- EM Front: �noise= 32-55 MeV- EM Middle: �noise= 60-130 MeV- EM Ba k: �noise= 70-100 MeV- Tile A: �noise= 25-70 MeV- Tile BC: �noise= 25-70 MeV- Tile D: �noise= 25-65 MeVas in this release of Athena is not possible to sele t a value of NeighborThresholdOnAbsEtfor ea h layer of the EM alorimeter and TileCal, and also putting NeighborOption ="super3D" is not possible to sele t ea h subdete tor options in a separated way, a \meanvalue" of the level of noise is hoosen.22The Seed ell of the TopoCluster is the ell with the bigest ET . As you an se later,the most energeti ells in the 2nd layer of the EM alorimeter has ET > 200MeV .

236 10. Clustering for simulated parti les at Very Low EnergySize of the TopoCluster: Number of ellsThe tables 10.19 and 10.20 show the mean value of the number of ellsfor �+ and �0's in TopoCluster with noise thesholds applied23. The majorityof the ells in the TopoClusters ome from EM alorimeter, as in the aseof tables 10.8. But now, this proportion de reases when the energy of theparti les in reases only for harged hadrons, for neutrons it seems to bein uen ed by the theshold in the ele troni noise.The majority of the ells in EM do not ome from the 2nd layer (Front),as in tables 10.8, but from the 3rd layer (Middle) and 4th layer (Ba k):- Middle: �28-31% of the ells in EM- Ba k: �34-39% of the ells in EMThey onstitute around 52-55% of the total ells. This is due to the fa t thatthe ele troni noise in Front is smaller than the NeighborThresholdOnAbsEtvalue hoosen and a loss in de�nition of Topo luster happens24.ET Total Cells in EM (�+)parti les Cells Total (%) Pres Front Mid Ba k1 GeV 12.8 11.4 88.6 2.4 2.3 2.6 3.93 GeV 38.7 32.0 82.7 2.9 7.5 9.8 11.75 GeV 62.6 50.5 80.7 3.3 13.1 15.5 18.710 GeV 97.0 77.3 79.6 3.9 20.5 24.0 28.830 GeV 168 130 77.2 5.6 37.3 36.3 51.3ET Total Cells in TILE (�+)parti les Cells Total (%) A BC D1 GeV 12.8 1.46 11.4 1.10 0.28 {3 GeV 38.7 6.67 17.2 4.16 2.07 0.235 GeV 62.6 12.08 19.3 7.01 4.32 0.5510 GeV 97.0 19.62 20.2 10.52 7.55 1.2830 GeV 168 38.10 22.5 18.1 15.8 4.15Table 10.19: Mean value of the ells in TopoCluster for �+ with noise thesholds usingSeed ut=4. The 2nd olumn is the ells in all alorimeter. The 1st table shows the total ells in the EM alo, next to the values in ea h layer (Pres, Front, Middle and Ba k). The2nd table shows the total ells in TILE, next to the values in its samples (A, BC, D).On the other hand, the sample with more ells in TILE is the �rst one(Sample A) and the proportion respe t to the total ell has in reased from�4-6% to �10-12%.23The results for neutrons are very similar, so they are not shown here.24It woul be better ould put the orre t �noise for ea h layer of the EM alorimeter,but it is not possible in this release of Athena

10.7. TopoClusters in 8.2.0 Release 237ET Cells in EM (�0)parti les Total Pres Front Mid Ba k1 GeV 9.82 2.49 2.81 2.41 2.123 GeV 45.64 5.83 19.0 15.64 5.165 GeV 63.6 7.21 27.62 21..56 7.2010 GeV 81.25 8.81 36.23 26.62 9.5830 GeV 107.3 10.29 46.67 36.37 13.94Table 10.20: Mean value of the ells in TopoCluster for �0's with noise thesholds usingSeed ut=4. The 2nd olumn shows the total ells in the EM alo, next to the values inea h layer (Presampler, Front, Middle and Ba k).The tables 10.21 and 10.22 show that the total size of the TopoCluster- when the noise thesholds are added - is from 3 to 19 times smaller. Thedi�eren e in size in reases when the ET of the parti les de reases. Thisdi�eren e is more important for the EM alo than for Tile, be ause in the�rst one the level of noise with respe t to the signal is bigger.Cells of �+'sET No Cut Cut Times No Cut Cut Times No Cut Cut Times(GeV) Total Total Size EM EM Size Tile Tile Size1 182 12.8 14.2 170 11.4 14.9 11 1.4 7.53 257 38.7 6.6 233 32.0 7.3 24 6.7 3.65 311 62.6 4.9 276 50.5 5.4 35 12.1 2.910 380 97.0 3.9 330 77.3 4.3 50 19.6 2.530 513 168 3.0 432 130 3.3 81 38.1 2.1Table 10.21: Comparison of the Mean value of the number of ells in ea h TopoClusterfor �+'s without (no ut) and with ( ut) noise thesholds, using Seed ut=4.ET No Cut Cut Times(GeV) EM EM Size1 187 9.8 19.03 253 45.6 5.55 275 63.6 4.310 295 81.2 3.630 338 107.3 3.1Table 10.22: Comparison of the Mean value of the number of ells in ea h TopoClusterfor �0's without (no ut) and with ( ut) noise thesholds, using Seed ut=4.Energy resolutionSo the type of parti le most a�e ted to the fa t that in lude the thesholdsof the ele troni noise will be the neutal pions - whi h deposited all theirenergy in EM alorimeter. As we an see in the new values of the energyresolution and the Mean value of ET lusterETgenerated .

238 10. Clustering for simulated parti les at Very Low EnergyET ET Resolution Mean of ET lusterETgeneratedparti les No Noise With Noise No Noise With Noise(GeV) 7.8.0 8.2.0 8.2.0 ( ut) 7.8.0 8.2.0 8.2.0 ( ut)1 56.30 44.57 60.71 0.528 1.05 0.4373 45.65 38.87 55.77 0.581 0.871 0.5585 33.82 30.65 41.39 0.652 0.841 0.64610 22.41 20.84 26.25 0.761 0.864 0.76130 13.91 13.36 13.09 0.813 0.851 0.817Table 10.23: Energy resolution and Mean value of ET lusterETgenerated in TopoClusters for harged pions , using CaloNoiseTool and Seed ut=4 and Neighbor ut=2.ET ET Resolution Mean of ET lusterETgeneratedparti les No Noise With Noise No Noise With Noise(GeV) 7.8.0 8.2.0 8.2.0 ( ut) 7.8.0 8.2.0 8.2.0 ( ut)1 64.31 |- 70.20 0.357 |- 0.4033 57.54 46.19 65.12 0.406 0.681 0.4245 40.41 34.04 51.07 0.498 0.687 0.49710 23.98 22.43 28.67 0.643 0.749 0.63630 12.39 11.94 12.60 0.110 0.811 0.771Table 10.24: Energy resolution and Mean value of ET lusterETgenerated in TopoClusters forneutrons, using CaloNoiseTool and Seed ut=4 and Neighbor ut=2.ET ET Resolution Mean of ET lusterETgeneratedparti les No Noise With Noise No Noise With Noise(GeV) 7.8.0 8.2.0 8.2.0 ( ut) 7.8.0 8.2.0 8.2.0 ( ut)1 30.52 35.50 | 0.678 1.217 0.5233 12.66 20.72 25.89 0.866 1.135 0.8415 7.35 14.35 15.19 0.918 1.084 0.92510 4.02 7.77 7.30 0.954 1.038 0.96830 2.21 3.11 2.89 0.919 1.010 0.986Table 10.25: Energy resolution and Mean value of ET lusterETgenerated in TopoClusters forneutral pions, using CaloNoiseTool and Seed ut=4 and Neighbor ut=2.The ET resolution gets worse when the ele troni noise is in luded in allparti les, but applying the noise ut we obtain a ET lusterETgenerated ratio similar tothe ase without noise, it means a more realisti method to olle t the ETdeposited in ells.

10.8. Con lusions 23910.8 Con lusionsTopoClusters is a very useful tool in the study of the lusters and itprovides a very good re onstru tion of the lusters, even in the ase ofparti les at very low energy. From the �rst part of this hapter, we an on lude that using TopoClusters with CaloNoiseTool pa kage and applyingSeed ut = 4 and NeighborCut= 2:- The best values of energy resolution are obtained for �+'s, �0's andneutrons.- The low eÆ ien y of TopoClusters for single parti les at 1, 3, and 5GeV is eliminated.- The largest amount of ET is deposited inside the TopoClustersTopoCluster results are even better than the obtained from EGamma lus-ters for the ase of neutral pions.Comparing with another lustering algorithms, TopoCluster algorithmis very ompetitive for neutrons, �+'s and �0's at very low energies with thebest algorithm in these ases:- the TRUTH- one, i.e. the one algorithm entred in the ��� of Truthgenerated parti les, for neutrons and �0's- the TRACK- one, for harged pionsWhen the ele troni noise is in luded, the ET resolution from TopoClus-ters get worse, but applying these noise uts:- CellThresholdOnAbsEt = 10.0*MeV- NeighborThresholdOnAbsEt = 80.0*MeV- SeedThresholdOnEt = 200.0*MeVwe get a ET lusterETgenerated similar to the ase without noise, it means a more realisti method to olle t the ET deposited in ells.So, TopoClusters algorithm (with the hanges performed before) ouldbe used as \standard" tool in the study of lusters from parti les at verylow energies25.25In fa t, it will be used as basi algorithm in the Signal Chara terization of ele tro-magneti and hadroni shower and the next alibration level, see ATLAS CalorimetryCalibration Workshop presentations, De 2004

240 10. Clustering for simulated parti les at Very Low Energy10.9 Next Step in Clustering of VLE parti lesCluster formation and Cluster alibration of very low energy parti les mustbe validated with real data. During 2004, a Combined TestBeam of thedi�erent sub-dete tor of ATLAS have been done. Single parti le beam ofpions and ele tron at very low energy (from 1 to 9 GeV) have been sent tothe ombined- alorimeter set-up, so they will be a useful tool to understandthe lustering formation[7℄[9℄[10℄.On the other hand, samples based on DC2 events are simulated usingGeant4[11℄, in luding the geometry of the Combined TestBeam (a la AT-LAS) and we an used them to get more easily the orre t sele tion uts inthe beam parti les to extra t the harged pions or ele trons in ea h ase.

10.10. Appendix 1: Analysis of the de ay �0 ! 24110.10 Appendix 1: Analysis of the de ay �0 ! The more frequent multipli ity of TopoClusters for �0's is 1. This be-havior would be orre t if the photons would be very lose to ea h other,and the lustering algorithm onsiders them as only one luster.In order to see if this hypothesis is orre t and there is not any problemwith the re onstru tion of the neutral pions at VLE inside the lusteringalgorithm, next we study the angle between the photons of the �0 de ay(�0 ! ) and relate it with the multipli ity of TopoClusters.10.10.1 Proximity �0- First, using a sample of neutral pions at 5 GeV, it has been veri�ed thatthe whole of the 1000 generated �0's de ay into two photons.Then, de�ning �� = ��0 � � and �� = ��0 � � it possible to he kthat the �� � oordinates of the �0's are very lose to the �� � oordinatesof the two photons, see �g. 10.31.Figure 10.31: �� = ��0 � � and �� = ��0 � � distribution from �� � oordinatesof the �0's and the two de ayed photons.Finally, the radius is de�ned as � R = q��2 +��2. The majority ofthe photons are inside a one with �R < 0:01 from the � � � oordinatesof the �0, as it is shown in the �g. 10.32. So it an be said that the �0'sare very lose to the de ayed photons and it's orre t to use their � � � oordinates in the analysis to re onstru t the energy deposited.Figure 10.32: �R distribution from �� � oordinates of the �0's and the two de ayedphotons.

242 10. Clustering for simulated parti les at Very Low Energy10.10.2 Proximity - Now the angle between the photons of the �0 de ay ( �0 ! ) is studied,in order to understand the multipli ity of TopoClusters. The majority ofthe multipli ity of TopoClusters for �0's is 1, this would be orre t if thephotons would be very lose ea h other.Then, de�ning �� = � 1 � � 2 and �� = � 1 � � 2 it possible to he kas the �� � oordinates of the photons are very lose to ea h other, as the�g. 10.33 shown.Figure 10.33: �� = � 1 �� 2 and �� = � 1 � � 2 distributions from �� � oordinatesof the two de ayed photons.Again, using the above given de�nition of the radius, it an be seen thatthe majority of the photons are inside a one of �R < 0:01 from the �� � oordinates of either photon. So, their lusters are very lose and they anbe onsidered only one luster.Figure 10.34: �R distribution from �� � oordinates of the two de ayed photons.RMS of the �� and �� distributionComparing the di�erent results for the RMS of the �� and �� distri-bution of the two de ayed photons, it an be seen that the RMS hangeswith the transverse energy of the generated �0's. As the energy of the �0'sin reases the de ayed photons are loser.

10.10. Appendix 1: Analysis of the de ay �0 ! 243

Figure 10.35: RMS of the �� and �� distribution of the two de ayed photons.MEAN value and the RMS of the �RIn the same way, the MEAN value and the RMS of the �R from the� � � oordinates of both photons gets smaller as the ET of the generated�0's in reases.Figure 10.36: The MEAN value and the RMS of the �R from the �� � oordinates ofthe one photon to the other.Case of �0's at 1 and 3 GeVThe �� and �� distributions of the photon from the generated �0's at1 and 3 GeV, see �g. 10.37 are wider than at higher energies.

Figure 10.37: �� and �� distribution of the de ayed photons from 1 and 3 GeV �0's.

244 10. Clustering for simulated parti les at Very Low EnergyTherefore, the �R at 1-3 GeV present a strange distribution (see �g.10.38). At 1 GeV, the de ayed photons are separated at a value for theradius near to �R � 0:3, instead of being the majority of them inside a one of �R < 0:1. In a similar way, at 3 GeV the photons are separated at�R � 0:1, why appears this strange behavior?The best explanation an be the next: The MINIMUM separation of thetwo gammas from �0 de ay o urs when the de ay angle is perpendi ular tothe dire tion of motion, and in that ase the tangent of the half-angle is mE .- For E�0=1000 MeV (and m=140), this is 0.140 so the separation �0.280 rad- For E�0=3000 MeV (and m=140), this is 0.046 so the separation �0.092 radThe separation in reases monotoni ally as the de ay angle moves away fromperpendi ular, rea hing 180Æ for the de ay when one gamma is forward andthe other is ba kward26.

Figure 10.38: �R distribution of the two de ayed photons from 1 and 3 GeV �0's.26Be ause for massive de ay produ ts we expe t the parti les to have max separationat 90Æ.

10.11. Appendix 2: Study of the overlap 24510.11 Appendix 2: Study of the overlapThe eÆ ien y of the Energy Flow Algorithm will be limited by the overlapbetween neutral and harged parti les in the ells of the alorimeter. So,to try to estimate the presen e of a neutral hadron inside a luster de�nedfrom the tra k of the harged pion and its in uen e in the energy resolution,we pass to use multiparti le samples instead of single parti le samples.These samples are a mixing of neutral and harged pions as well as neu-trons, all of them at very low energy (5, 7 or 10 GeV). These multiparti lessamples are based on DC1 events simulated by D. Froidevaux27 with ele -troni noise (but without pileup) in the barrel region (j�j <1.5).To study the grade of overlapping, we use di�erent multiparti les sampleswith the parti les generated at di�erent distan es (�R) between them:� Parti les far away in �R spa e- pi0pimneu10hfar: �0 = 10 GeV, �� = 10 GeV, neu = 10 GeV- pi0pimneu5hfar: �0 = 5 GeV, �� = 5 GeV, neu = 5 GeV� Parti les loser in �R spa e (�R = 0.1)- pi0pimneu10d1010: �0 = 10 GeV, �� = 10 GeV, neu = 10 GeV- pi0pimneu555d1010: �0 = 5 GeV, �� = 5 GeV, neu = 5 GeV� Parti les loser in �R spa e bellow 0.1- pi0pim77d05: �0 = 7 GeV, �� = 7 GeV in a distan e �R = 0.05- pi0pimneu555d0505: �0 = 5 GeV, �� = 5 GeV, neu = 5 GeVin a distan e �R = 0.05- pi0pip1010d05: �0 = 10 GeV, �� = 10 GeV in �R = 0.05- pi0pip55d07: �0 = 5 GeV, �� = 5 GeV in a distan e �R = 0.07Event Display of TopoClusters[11℄ shows us the di�eren e between thesesamples. This tool permits us to see the same �� x �� region of the di�erent alorimeter se tions. The olor boxes denote the energy per ell in MeV ona log-s ale with di�erent s ale for ea h plot.27The samples are lo ated at CASTOR area in: = astor= ern: h=user=f=froid=di e03=

246 10. Clustering for simulated parti les at Very Low EnergyFor the example of parti les far away in �R spa e (see �g. 10.39), it'spossible to distinguish the three luster orresponding to ea h parti les fromECAL Middle layer, while for parti les loser in �R (bellow 0.1) the lustersare very lose and they are diÆ ult to be distinguished (see �g. 10.40).

Figure 10.39: Event display for a multiparti le sample with �0 = 10 GeV, �� = 10GeV and neu = 10 GeV generated far away between them. It's possible to distinguish 3 lusters from ECAL Middle layer up to Tile2.

Figure 10.40: Event display for a multiparti le sample with �0=10 GeV and ��=10GeV generated to be very lose (�R=0.05). It's diÆ ult to distinguish the lusters inTile.

10.11. Appendix 2: Study of the overlap 24710.11.1 Energy Resolution with and without SplitterNext table shows the energy resolution values for the di�erent multipar-ti les samples with and without the Splitter[12℄ applied.ET Resolution Mean of ET lusterETgeneratedNo Splitter Splitter No Splitter Splitterpi0pimneu10d10hfar 10.26 10.21 0.8171 0.8185pi0pimneu5hfar 14.97 14.70 0.7535 0.7543pi0pimneu10d1010 9.34 9.32 0.8282 0.8287pi0pimneu555d1010 13.96 14.17 0.7715 0.7717pi0pim77d05 11.87 11.89 0.8969 0.8975pi0pimneu555d0505 14.51 14.55 0.7786 0.7801pi0pip1010d05 9.04 9.00 0.9093 0.91pi0pim55d07 14.77 14.74 0.8926 0.8944The Energy resolution results with and without Splitter are very similar,even in the ase of parti les generated to be very lose (�R = 0.05 and �R= 0.07)!!28.The tool used, CaloTopoClusterSplitter a epts three parameters:� NeighborOption (default = "super3D")� NumberOfCellsCut (default = 4)� EtDensityCut (default = 500 MeV/600000 mm3)As we have seen, all maximum andidates must pass EtDensityCut to bea epted as lo al maxima, but the very low energeti parti les don't produ ebig lo al maxima, so it needed to hange the value of the EtDensityCutinvestigating the deposited energy in a LarEM ell in the 2nd layer by VLEparti les.

28The total energy of all lusters must be the same at the end of the re onstru tion withand without Splitter by de�nition, so it's expe ted that the results for ET lusterETgenerated will besimilar but not for the energy resolution.

248 10. Clustering for simulated parti les at Very Low Energy10.11.2 Energy deposited in LArEM ell of 2nd layerThe energy deposited in LArEM ell of 2nd layer by harged and neutralpions of very low energy (3, 5 and 10 GeV) is shown in �g. 10.41 in or-der to �nd the orre t value for the EtDensityCut and apply orre tly theClusterSplitter to TopoCluster oming from VLE parti les.

Figure 10.41: The energy deposited in LArEM ell of 2nd layer by harged and neutralpions of very low energy (3, 5 and 10 GeV). The mean value of the energy depositedis around 280 GeV, so the orre t value for the EtDensityCut and apply orre tly theClusterSplitter to TopoCluster oming from VLE parti les ould be 250 MeV/600000mm3.The mean value of the energy deposited in LArEM ell of the 2nd layer is�280 GeV, so the EtDensityCut will be hanged to 250*MeV/600000*mm3.10.11.3 Final on lusion about Splitter in VLE parti lesNevertheless, the value of energy resolution using the default EtDensityCutand using the new value of 250 MeV/600000 mm3 are identi al in the 3 asesof multiparti les samples. Even the Root plots from the event display arethe same. So it's only possible to on lude that the CaloTopoSplitterClusterin 8.2.0 release29 an not be used to study the overlap of parti les at verylow energy (only useful for energeti parti les30.)29No sharing of ells between lusters is introdu ed in CaloTopo pa kage in these releaseof Athena, maybe with this tool, the shape of the luster ould be studied more a urately.30As Sven Menke show in O tober 2004 during the ATLAS Overview Week for jet at70 GeV in the presentation \Hadroni Energy Calibration: from TestBeam to ATLAS"on behalf of the Hadroni Calibration Group.

Referen es: 249Referen es:[1℄ Athena User and Developer Guide v.2.0 & Releaseshttp://atlas.web. ern. h/Atlas/GROUPS/SOFTWARE/OO/ar hite -ture/General/[2℄ ATLAS Collaboration, ATLAS Dete tor and Physi s Performan eTe hni al Design Report CERN/LHCC/99-14, ATLAS TDR 14 (1999).[3℄ C.Iglesias talks: TiCal-IFIC Weekly Meetings (Valen ia, SPAIN), atmy personal web page: http://i� .uv.es/�iglesias[4℄ C.Iglesias, Clustering of very low ET parti les, Software Workshop, Re- onstru tion Working Group: Calorimetry, Sep,2004, CERN[5℄ S.Menke talks: Status of Topologi al Clustering, presented at Software& Performan e Meeting, LAr Week (CERN), 28. Jan 2004[6℄ S.Menke Status of Topologi al Clustering & re ent Re o-SoftwareChanges, Hadroni Calibration meeting, 13. May 2004, CERN (Calo-EventDisplay.tar.gz), 06. June 2004. S. Menke Personal web page:http://www.mppmu.mpg.de/ menke/[7℄ C.Iglesias, Clustering of very low ET parti les in Combined TB, ATLASCalorimetry Calibration Workshop, Hadroni Calibration Session, De 2004, Trata, SlokaviaC.Iglesias, More about very low energy parti le, TileCal CommissioningMeeting 2 Feb., 2005[8℄ C.Iglesias, Pedestal analysis, personal web page:http://i� .uv.es/�iglesias/C.Iglesias, Clustering for VLE parti les in CBT, TileCal Analysis andCombined Test Beam, 14 Feb, 2005, TileCal Week, CERN[9℄ C.Iglesias, V. Giangiobbe. Analysis with VLE runs in Combined TB,Final Combined Test Beam Workshop, 16 Feb, 2005, CERN[10℄ C.Iglesias, Clustering of very low ET parti les with 2004 Combined Test-Beam data of ATLAS, ATLAS ommuni ation in preparation.[11℄ Geant4 Users do uments:http://wwwasd.web. ern. h/wwwasd/geant4/G4UsersDo uments//Overview/html/index.html

250 Referen es:[12℄ ROOT ma ro pa kage for ATLAS Calorimeter Event Displays,[13℄ S.Menke Topologi al Cluster Maker & Splitter - HOWTO for Athena8.2.0, JetRe Phone Meeting, 02. June 2004, CERN

Chapter 11Combined TestBeam 200411.1 Introdu tionIn the year 2004, ATLAS ommunity has been involved in a huge Com-bined Test Beam (CTB )[1℄[2℄ e�ort in H8. A omplete sli e of the barreldete tor and of the Muon End- ap has been tested (see Fig.11.1) in a run-ning period from 17 May to 15 November.In this hapter a general des ription of the 2004 Combined Test Beamis done. In the se tion 11.2 the motivations and the main goals of CBTare explained. The CBT s hedule, hara terized by di�erent phases withan in remental presen e of subdete tors, is treated in se tion 11.3. Then,in se tion 11.4 the setup is des ribed, next to the di�erent measurementswhi h were done with sele ted parts of the setup (se tion 11.5) and theamount of information that was possible to obtain on the di�erent sub-dete tors (se tion 11.6). In se tion 11.7 and 11.8 the Simulation and theO�ine Re onstru tion in CBT are des ribed, respe tively.Finally, the last se tion is dedi ated to the runs of very low energy (VLE)parti les taken in the CBT and the des ription of the spe ial setup neededto re ord them. These will be the data used in our analysis with lusteringalgorithms[3℄[4℄[5℄ shown in the next hapter.11.2 The motivationThe Combined Test Beam operation is seen by the ATLAS ommunity asa unique o asion for exploiting the pre- ommissioning strategy that willallow a better understanding of the barrel sub-dete tors for a qui ker startup of the ommissioning in the pit. The same argument is valid for the other251

252 11. Combined TestBeam 2004

Figure 11.1: Setup for Combined TestBeam of the EM alorimeter (LArEM) andHadroni alorimetervery important test to be arried out next year by the End Cap Calorimetryon the H6 line.It is a very important o asion for young people to have the feeling ofthe issues related to the run of a small s ale experiment. Thanks to thisexperien e, a lot of expertise in the operations has been a quired studingthe dete tor performan e in a realisti ombined data taking1. Therefore,many data (�4.6 TB of data, �90 millions of events on CASTOR[6℄) havebeen olle ted and are already under analysis.The physi s goals of the CTB have been de�ned in onsultation withthe physi s oordinator, all the sub-dete tor and the ombined performan egroup representatives. With all these indi ations, a detailed run plan day-by-day s hedule[7℄ has been de�ned before the CTB start and followed duringthe period of data taking[8℄. The program has been re-adjusted and modi-�ed a ording to the needs and priorities rising during the pro ess, via dailymeetings and dedi ated dis ussions with all groups involved[10℄,[11℄,[12℄.Flexibility for swapping and res heduling studies was provided where possi-ble by identifying pre isely the beam onditions and the availability of otherelements (i.e. magnets).1In the past, short periods of test beam ombining di�erent ATLAS sub-dete tors havebeen used. However, with the 2004 ombined test, for the �rst time ATLAS elements havebeen integrated in realisti onditions.

11.3. S hedule 25311.3 S heduleThe CTB has been hara terized by di�erent phases with an in rementalpresen e of subdete tors modules and asso iated DAQ infrastru ture, as wellas in remental improvement of analysis tools for prompt data erti� ation.As a result a full sli e of the ATLAS experiment (see Fig. 11.1) has beentested with beams of di�erent parti les (pions, ele trons, protons, muons andphotons) at di�erent energies and polarities, ranging from 1 GeV up to 350GeV, providing a unique opportunity to evaluate the individual sub-dete torperforman es, but also to exploit the full power of the ATLAS dete tor fordetailed parti le identi� ation and measurement and to understand betterthe dete tor before the ommissioning phase.A s hedule of about 22 weeks in total was foreseen for the SPS protonrun, growing in omplexity. Two periods in June and in O tober (see �gure11.2) have been dedi ated to the test with a 25 ns bun hed beam. Duringthe se ond period a full test of the alo and muon Level 1 trigger hain hasbeen performed.With the data whi h have been olle ted it will be possible to performa ombined re onstru tion of muons and ele trons[9℄ using the informationfrom the Inner Dete tor, the Calorimetry and the Muon system, to studythe muon atastrophi energy losses, their identi� ation and the �/� sep-aration, to look at the energy losses in ra ks, and to see how well we anre over these losses. There will also be studies of ele trons and pions iden-ti� ation, separation and shower shapes in di�erent onditions (i.e: varyingthe material in front, or the magneti �eld). Photon runs, to study onver-sion events have also been performed. The data will be used for detailedG4/FLUKA validation studies and tuning.Respe t to the alorimeter, testbeam data will yield the lue informationin the evaluation of the approa h hosen in the hadroni alibration. There-fore the CBT allows to optimize methods and algorithms as the following:- get \intrinsi em s ales";- 3D lustering algorithms[13℄[14℄[4℄[5℄, luster level orre tions, lusteridenti� ation studies;- try weighting approa h and ompare with MC;- lustering a ross dete tor boundaries- lustering a ross ra ks/transition regions, dead material orre tions

254 11. Combined TestBeam 2004

Figure 11.2: S hedule of the studies arried out.

11.4. The setup 255In addition, the testbeam data will give a �rst estimate of the systemati errors in the hadroni energy alibration due to the need to use MC derivedparameters in ATLAS.11.4 The setupStarting from May 2004, a full sli e of the ATLAS experiment was proto-typed and tested with beams of di�erent parti les at di�erent energies. Theset-up in luded (see Fig.11.1):� Inner dete tor: three layers of the Pixel sub-dete tor followed byfour layers of the SCT sub-dete tor and by a two modules-barrel sli eof the TRT sub-dete tor (see �g. 11.3).� Barrel e.m. and hadroni alorimetry: barrel modules of thee.m. LAr alorimeter and three barrel modules of the hadroni Tile al alorimeter. The setup also in ludes for a limited period of time threeextended barrel modules of the hadroni alorimeter extending the eta overage up to 1.2.� Muon spe trometer: three stations of barrel MDT, two additionalbarrel MDT hambers, three stations of the end ap MDT for a total of14 hambers; three end- ap TGC hambers, two barrel RPC hambersand an end- ap CSC hamber.

Figure 11.3: Left: the Pixel setup. Center: the SCT setup. Right: the TRT setup.The setup has to be seen as evolutive .The ombined alorimetry startedto take data in isolation from the rest for the basi measurements and toreprodu e the results obtained in 1994 and 1996. The Inner Dete tor om-bined setup started later to work independently from the other dete tors.

256 11. Combined TestBeam 2004

Figure 11.4: The Combined test beam setup (top view) in H8A.The Muons setup spanned a large part of the H8 line, therefore a stand alonesetting up had to be foreseen. A top view of the setup is in �gure 11.4.The CTB lead also to proje t and set a ommon trigger and busy aswell as a ommon data a quisition hain for all the sub-dete tors, whi h are hara terized by di�erent readout systems. This has been a fundamentalpre ommissioning whi h allowed to test in a realisti environment the read-out ar hite ture, the fun tioning of all its omponents, the Central TriggerPro essor whi h will have to manage all the �rst level triggers through dedi- ated interfa es, the sub-dete tors busy and hen eforth the omplete timingof the whole dete tor through the TTC ele troni .Besides the ar hite ture of the �rst level, almost the entire ar hite tureof the DAQ, in luding the High Level Trigger (Level 2 and Event Filter) havebeen implemented. This quite omplete test of the DAQ and the trigger will ertainly shorten the dete tor ommissioning in 2005-2007.Another important exer ise was the use of the olle ted data to developand ontrol the fun tioning of the entire o�ine software hain, from the on-dition database to the re onstru tion program (in the Athena framework),to the graphi s and to the Geant 4 simulation.For example, it has been already possible to verify the data in the \raw"format and in their de�nition \in obje ts", their de oding and the onversionfrom one format to the other, their use and the a ess s heme, both in thetrigger algorithms and in the re onstru tion programs, and �nally their use\online" for the monitoring and the alibration.

11.5. First measurements: debugging 25711.5 First measurements: debuggingMany measurements were done with sele ted parts of the setup:- Inner Dete tor + Calorimetry: They allow the identi� ation ofele trons and photons. Also it was possible the low energy pions iden-ti� ation using TRT and many others.- Inner Dete tor + Muons: This setup permits the ombined tra k-ing of muons.- Inner Dete tor + Calorimeters + Muons: With this on�gu-ration the ombined tra king of low energy muons (< 20 GeV) ouldbe obtained to study the resolution worsening when the muons areintera ting in the Calorimeters. Also it would be possible to study thee�e t of muons identi� ation in the third sampling of Tile al on theresolution and at the level of triggering enhan ement.- Calorimeters + Muons: Using these sub-de te tor, we an get asimilar study as above with the absen e of the Inner Dete tor infor-mation- Calorimeters + LVL1 Calo: In luding the Level 1 of trigger aswell as the EM and TileCal Calorimeter, the study of the timing and omparison of the orre tness of the trigger information is done.- Muons + LVL1 Muons: as above for Calorimeters11.6 The MeasurementsThe amount of information that was possible to obtain by this setup is huge.Few examples of the main goals are given here.11.6.1 CalorimetryIt will be a real advantage for ATLAS to have a well de�ned strategyof the alorimetry alibration[15℄. The importan e of the knowledge of theenergy sharing is learly needed for being ready to measure the �rst physi savailable at LHC.The weighting te hniques, that an be used o�ine to ompensate and orre t the energy re onstru tion in the alorimeters, have an important testduring the CBT2.2For weighting te hniques that would need a low number of parameters and a fast�tting one an also imagine an implementation of them at the level of the Event Filter(more details later).

258 11. Combined TestBeam 2004The showers ontainment an be a limit to these studies, therefore theoptimal onditions for the positioning of the alorimetry setup and the en-ergy of the parti les were studied.11.6.2 Inner Dete torThe Inner Dete tor exploited the ombined setup to study the ombinedresolution and pattern re ognition algorithms. These were also implementedat the level of the Event Filter. Further studies an be arried out with theMuons, as des ribed in the next subse tion.11.6.3 Muon Spe trometerThe Muon spe trometer is a large system that an pro�t of the Combinedrun to ontinue the already started experien e of internal integration beforegoing for the integration with the other dete tors. As said before an impor-tant study with low energy muons was done. The studies of tra k orrelationwith the Inner Dete tor are important as well and one ould imagine an im-plementation of an algorithm at the Event Filter level, to perform an onlinestudy.11.6.4 The LVL1 TriggerAt the beginning the trigger was based on the lassi set of s intillators witha pre ise de�nition of the beam.On e the LVL1 was ommissioned, the trigger de�ned by the s intillatorswas swit h o� and onlly the LVL1 trigger was used in the proper way. Ithad many advantages, the main advantage is that this is the only way tofully exploit the pipelined readout of all the subdete tors. The a quisitionof the slow information from s intillator and beam hambers does not allowthat mode of operation and for e an event-by-event readout.11.6.5 The DAQThe exploitation of the prototype software available at the time of the Com-bined Test Beam an be a powerful debugging tool. The experien e ofrunning the entral DAQ prototypes from 2000 onwards has proved to bevery produ tive.The possibility of using protoypes or pre-produ tion of the hardware forre eiving the data from the various RODs and ROD emulators, an be ofreal interest.

11.7. Simulation in CombinedTB 25911.7 Simulation in CombinedTBBeam tests are an ideal proving ground for a dete tor simulation programas they provide a dire t omparison with experimental data in a simpli�eddete tor setup. Simulating the ATLAS Combined Test Beam Fa ility per-mits to test the reliability of the simulation suite and to validate the physi smodels employed while at the same time providing a useful tool to be usedby the dete tor ommunity.Simulation studies were performed for all sub-dete tors (in various om-binations and separately) and a detailed omparison was run against avail-able experimental data sets, the agreement between data and simulationbeing remarkable in all ases.In the last years an extensive program of tests, in a beam line, of allthe omponents of a true and omplete se tor of ATLAS was performed.A detailed simulation of the setup was developed, reprodu ing a ompletese tor of ATLAS dete tor. All an illary dete tors, magnets and dead ma-terial along the beam line were added in the simulation, and a broad setof omparisons with data were performed for all the te hnologies, giving us on�den e in the simulation of both the dete tor des ription and the physi sof the omplete tool.Testbeam simulation uses the same software as the full experiment. A3D view of the implemented geometry is shown in Fig. 11.5.

Figure 11.5: Geant4 Layout if the Combined Test Beam setup.

260 11. Combined TestBeam 200411.8 O�ine Re onstru tion and Software toolsThe Combined Test Beam was a hallenging exer ise sin e, for the �rst time,the omplete software[16℄ suite developed for the full ATLAS experiment hasbeen extended for use with real dete tor data. It was a powerful instrumentto get the people exploit the software tools.Exploiting the o�ine omputing model and the re onstru tion programis a very important experien e that an help the debugging of the appli a-tions and the dis overy of any possible improvement.The use of the o�ine tools will be a on rete advantage for people thatwants to be ready in advan e to use them in the �nal experiment. Thise�ort an be seen as a powerful data hallenge.Important integration issues like ombined simulation, ombined re on-stru tion, onne tion with the online servi es and management of many dif-ferent types of onditions data are being addressed for the �rst time, withthe goal of both a hieving experien e on su h integration aspe ts and ofperforming physi s studies requiring the ombined analysis of simultaneousdata oming from di�erent sub-dete tors.

Figure 11.6: Conditions Database infrastru tureA key part of this e�ort is the storage of onditions data (i.e. alibrationand alignment onstants or bookkeeping information) in a oordinated way.The main omponent of the Conditions Database Infrastru ture (see Fig.11.6) is the Interval of Validity Database (IoVDB), whi h holds not only thedata obje ts that are a tually stored in IoVDB but also referen es to obje tsthat have been stored in other two types of Database, NOVA and POOL.Important feedba k on the performan e of su h infrastru ture is awaitedfrom the test beam operation.

11.9. Where the real ombination is taking pla e 261From the software development point of view, the ATLAS CombinedTest Beam is a unique opportunity to test, with real data, new algorithmsfor pattern re ognition, parti le tra king and identi� ation and High LevelTrigger strategies.11.9 Where the real ombination is taking pla eThe full setup is ombined at several levels. The most elementary one is atthe level of the ommon triggering and busy infrastru ture and at the levelof the Data Adquisition System (DAQ).Nevertheless an evolution of the basi triggering s hema has to be fore-seen even before exploiting the LVL1 infrastru ture. A de�nition of theele trons, muons and pions an be easily a omplished by using Cherenkovdete tors available on the beam line[17℄ (see �g.11.7) and oin iden e ofs intillator properly positioned. A simple logi an handle similar fun tionas an elementary Central Trigger Pro essor (CTP).

Figure 11.7: A drawing of the beam line element layout. The dimensions are not ins ale and the elements are represented by blo ks.But the real ombination at the online level happens at the Event Filter.Every sub-dete tor implements their online alibration and event sele tionas an online pro essing task that an run on the Event Filter farm CPUs.Starting with simple algorithms one an start agging as good tra ks in theMDT hambers the ones that have more than a ertain number of hits, forexample. On the same line it's possible to do a similar sele tion at the InnerDete tor level. Or use the energy deposition in the various layers of the alorimeters to ag events as ele trons or hadrons.Many e�orts should go in this dire tion. These elementary tools willbe very useful on e in the pit, the avern 100 m underground where the

262 11. Combined TestBeam 2004experiment will be housed. There will be the possibility of getting osmi rays and later with the �rst ollisions. Pro essing tasks implemented usingthe ATHENA framework should be exploited already in 2003 during theMDT test beam runs and during the ombined run.11.10 Other important subje tsThe Combined Test Beam an also be a powerful tool for the exploitationand the debugging of a large s ale Dete tor Control System (DCS) infras-tru ture (high-low voltage ontrol, ooling system... ). How to ombine the ontrols of the various sub-dete tors, how to manage the information om-ing from the a elerator, et . are important real life examples for the DCSsystem.In ATLAS the on ept of Condition Database is still not ompletelyde�ned. In su h a setup the �lling of a database by the DCS and from thesub-dete tors to store the alibration outputs would be a very importanto asion of a better omprehesion of this on ept. The a ess of it for theO�ine analysis may ontribute enourmously to the development of toolsthat will turn out to be very useful during the ommisioning and during theexperiment.11.11 VLE parti les in Combined Test BeamDuring the last period of CBT 2004 (Period 8: sep. 24th to nov. 15th3.)runs with very low energy (VLE) were taken with a fully ombined setup:Pixel + TRT + Calo's + Muons4.The data used in our analysis will be runs of ele trons and pions with:- pT = 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 GeV- � = 0.20, 0.25, 0.35, 0.45, 0.55 and 0.653See the Run lists and o�ine status for the H8 Combined Test Beam-2004 with theList of data taken per subje t and per periode:http://atlas.web. ern. h/Atlas/GROUPS/LIQARGON/Comb TB/CBT Barrel/RunLists/index.htmland the List data per subje t per Period 8:http://atlas.web. ern. h/Atlas/GROUPS/LIQARGON/Comb TB/CBT Barrel/RunLists/liste-per-type.txt4Although the Pixel does not work properly and only the TRT information for tra kswill be used in the later analyisis. The use of Muons hamber is under analysis.

11.11. VLE parti les in Combined Test Beam 263Other studies with VLE parti les in this period were:- Muons at very low energies- Material study: at 1, 5, 9 GeV di�erent material thi knesses dire tlyin front of the LAr ryostat (Al plates of 2.5 m thi kness) � = 0.0;0.3; 0.6; 0.911.11.1 Produ tion of parti les with low pTFor the produ tion of parti les with low pT (with pT < 10 GeV) a new setupis needed due to the de ay time of low energy pions and the low momentumtransport limited by urrent instabilities of beam elements. This VLE setup onsist in:- Additional produ tion target- Momentum sele tion: 4 dipoles + ollimator- Beam dump- Spe trometer: Beam instrumentation (Cherenkov + trigger + beam hambers) (see �g.11.8)

Figure 11.8: Setup for VLE beam.

264 Referen es:Referen es:[1℄ The ATLAS CTB Team, The 2004 ATLAS Combined Test Beam ATL-ENEWS-2004-021[2℄ Aleksa, M; (CERN) Coelli, S (INFN Milano) ; Di Girolamo, B (CERN); Ferrari, C (CERN) ; Giugni, D (CERN) ; Santoni, C (LPC ClermontFerrand) ; Wingerter, I (LAPP Anne y) ; TEST BEAM COORDINA-TION: The 2004 Test Beam Calorimetry set-up in H8 ATL-ENEWS-2004-001[3℄ C.Iglesias, Clustering of very low ET parti les in Combined TB, ATLASCalorimetry Calibration Workshop, Hadroni Calibration Session, De 2004, Trata, SlokaviaC.Iglesias, More about very low energy parti le TileCal CommissioningMeeting 02/02/2005C.Iglesias, Clustering for VLE parti les in CBT, TileCal Analysis andCombined Test Beam, 14 Feb, TileCal Week, CERN[4℄ C.Iglesias, V. Giangiobbe. Analysis with VLE runs in Combined TB,Final Combined Test Beam Workshop, 16 Feb, CERN[5℄ C.Iglesias, Clustering of very low ET parti les with 2004 CombinedTestBeam data of ATLAS, ATLAS ommuni ation in preparation.[6℄ J.P. Baud et al., CASTOR status amd evolution, presented at CHEP03,La Jolla California, Mar h 2003CERN Web page How to use CASTOR?, http://lh b-help.web. ern. h/lh b-help/html/ astor.htmCASTOR User's guide: http://ait.web.psi. h/servi es/ astor/ astor-info.html[7℄ B. Di Girolamo, M. Gallas, T, Ko�as 2004 ATLAS Barrel CombinedTest Beam Layout EDMS: Note: ATC-TT-IN-0001. EDMS ID: 406880.[8℄ M. Cobal, B. Di Girolamo, ATLAS Barrel Combined Run in 2004 Day-by-day EDMS Note: ATC-TT-ON-0001 EDMS ID: 450811.[9℄ Aleksa, M. et al, Studies of upstream material e e ts on e�= re on-stru tion and alibration in 2004 ATLAS Combined Test-Beam. Notenot published yet.

Referen es: 265[10℄ First Workshop on 2004 ATLAS Combined Test Beamhttp://atlas.web. ern. h/Atlas/GROUPS/GENERAL/TESTBEAM/TBWorkshop/�rstworkshop.html[11℄ Se ond Workshop on 2004 ATLAS H8 Combined Test Beam.http://atlas.web. ern. h/Atlas/GROUPS/GENERAL/TESTBEAM/TBWorkshop/se ondworkshop.html[12℄ Final Workshop on 2004 ATLAS H8 Combined Test Beamhttp://atlas.web. ern. h/Atlas/GROUPS/GENERAL/TESTBEAM/TBWorkshop/[13℄ C.Iglesias, Clustering of very low ET parti les, Software Workshop, Re- onstru tion Working Group: Calorimetry, Sep,2004, CERN[14℄ C.Iglesias, Clustering of very low ET parti les, sent as ATLAS ommu-ni ation in April 2005[15℄ ATLAS Calorimeter Performan e, CERN/LHCC/96-40, ATLAS TDR1, (1996).[16℄ Barberis, D; Software and Computing News ATL-ENEWS-2004-020[17℄ Di Girolamo, B; Dotti, A; Giangiobbe, V; Johansson, P; Pribyl, L;Volpi, M; Beamline instrumentation in the 2004 ombined ATLAS test-beam. CERN-ATL-COM-TECH-2005-001. Geneva : CERN, 07 Apr2005

266 Referen es:

Chapter 12Clustering for VLE parti lesfrom Combined Test Beam12.1 Basi Idea of the analysisThis hapter shows a omparison among the di�erent lustering algorithmspresented in the Combined Testbeam ontext: the sliding window algo-rithms (EM lusters, TBEM lusters and CMB lusters) and the TopoCluster(Topo EM and Topo Tile).12.2 Physi s Samples from Combined TB 2004Very low energy runs from the CombinedTB 2004 have been used. Thenumber of runs an be seen in the table 12.1. Events from 1 to 9 GeV at �= 0.35, with alorimeter information (LAr+Tile) and the tra ks informationfrom the TRT system only (Pixels had problems at that time) are used.Table 12.1: Number of the runs of very low energy parti les taken during the Com-binedTB 2004 that will be used in this analysis.A set of 100.000 events have been generated for ea h point, being amixture of ele tron, pions and muons.267

268 12. Clustering for VLE parti les from Combined Test BeamThe re onstru tion have been done �rstly with 9.1.1 and then with 10.0.2releases of the ATLAS o�ine software. The ntuples where generated in ol-laboration with V. Giangiobbe (LPC Clermont-Ferrand), using the defaultvalues of the Re ExTB (the re onstru tion pa kage inside Athena for theCombinedTB data). They are stored in:/ astor/ ern. h/atlas/ tb/test/real data/re onstru tion/Combined.12.3 Energy re onstru tionThe total energy is obtained from the sum of the ell energy when it hasa value larger than the level of noise (pedestal) per ell, de�ning di�erent�pedestal depending on the part of the sub-dete tors, as it is shown in thetable 12.2:

Table 12.2: Level of noise per ell for ea h part of the LAr alorimeter (Presemapler,Front, Middle and Ba k) and ea h sample of TileCal (A, BC and D).Only the ells inside a small volume around the beam are studied:- For LAr: 0.25 < � < 0.45 and -0.15 < � < 0.15- For TileCal: 0.20 � � � 0.50 and -0.1 < � < 0.1 , whi h ontains the ells: A3, A4, A5, BC3, BC4, BC5, D1 and D2, (see �g. 12.1).

Figure 12.1: S hema of the volume of TileCal used for the energy re onstru tion.

12.4. Sele tion Cuts for parti les at VLE 26912.4 Sele tion Cuts for parti les at VLEBe ause the samples with Very Low Energy (VLE) parti les are a mixingof pions, muons and ele trons, it will be ne essary to apply several uts inorder to sele t the desired parti les. Next, the di�erent uts developpedmainly by V. Giangiobbe and C Santoni (LPC Clermont-Ferrand) will besummarize.12.4.1 Sele tion of well-de�ned tra k in TRTWe study the quality of the tra k using information only from TRT system,be ause Pixels did not work properly during these runs. Spe ial jobOptions�le have been used to enable the tra king with TRT1. In the ase of goodtra ks, the average number of hits asso iated is 36. In the ntuples exists theinteger variable trk nTrtHits [itra k ℄ that orresponds to the number of hitsasso iated to the tra k itra k.In our ase, for leaning the beam, �rst, we sele t the event with only asingle tra k:� trk nTra ks == 1and then apply a ondition under the number of hits to sele t a well-de�nedtra k in TRT:� trk nTrHits[0℄ � 2012.4.2 Separate ele trons from �=�In the �g.12.2 (left side), one an see how to separate ele tron from �=� sig-nal applying a ut in the number of ADC ounts in the se ond Cherenkov hamber:� for ele trons: sADC C2 < 650� for pions/muons: sADC C2 > 6501We have applied the hanges suggested by Tuan Vu Anh (from TRT system). ThejobOptions �le is availabe in /afs/ ern. h/user/v/vgiangio/publi , with the hanges in:� InnerDete tor/InDetExample/InDetTBRe Example/*/InDetTBRe JobOptions.py� some ags in Re ExTB Combined 2004 jobOptions.pya) InDetTBFlags.xKalman = Trueb) InDetTBFlags.SiTBLineFitter = False

270 12. Clustering for VLE parti les from Combined Test BeamTo improve the herenkov eÆ ien y, the low-level and high-level trig-ger ould be used (see right side of the �g.12.2). A pion tra k, in general,has less than 5 high level hits while the ele tron tra ks have more than 2high-level hits. To ea h hit itrhit of a tra k itra k, it is asso iated an integervariable trk TrtHL [itra k℄[itrhit℄, in this way, hits of the kind high-level aretrk TrtHL [itra k℄[itrhit℄ =1, otherwhise it is equal 0.In our ase, we have a single tra k and we will usethe variable nHL2(number of High Level hits) to separate ele tron from pions:� for ele trons: nHL > 5� for pions/muons: nHL � 2

Figure 12.2: Left: number of ACD ount in the 2nd Cherenkov hamber for 9 GeVparti les: it will be possible to separate ele trons from pions/muons with a ut in �650.Right: number of high level hits per tra k for 9 GeV parti les: with a ondition in thisvariable an improvement in the eÆ ien y of the sele tion will be a hieved.

2Tuan Vu Anh suggested to de�ned the variable nHL (number of High Level hits) inthe following way:nHL = 0for ( itrhit = 0; itrhit < trk nTrtHits [0℄; itrhit++) fif ( trk TrtHL [0℄[itrhit℄ ==1) nHL++;g

12.4. Sele tion Cuts for parti les at VLE 27112.4.3 Separate pions from muonsIn a �rst stage, it should be possible to remove the muons from the pionsample using only the Tile alorimeter information.First method: using sample D as a muon vetoAssuming that only muons an rea h sample D and the pions signal is only oming from pedestal in this region, we put the ut: ESampleD < 0.15 GeV(see �g. 12.3).

Figure 12.3: Energy in the sample D of TileCal for 9 GeV parti les. With the onditionESampleD < 0.15 GeV it should be possible to remove the muons from the pion sample.This method has the advantange that it is very eÆ ient and easy toreprodu e with MC, but it has also an important disadvantage: we anreje t pions that rea h the sample D, getting a bias. In order to avoid it,di�erent strategies are followed depending on the energy of the parti les:- bellow 6 GeV, the TileCal last sample (D ells) is used as a muon vetoa) for pions: it is supossed that there is no energy in TileCal SampleD. So, we ask for less than 0.1 GeV (only pedestal)b) for muons: more than 0.1 GeV in Sample D (above pedestal).- at larger energies, a fra tion of pions an rea h the sample D in TileCal,so it is no more a good muon veto, and we will use the longitudinalpro�le in TileCal

272 12. Clustering for VLE parti les from Combined Test BeamSe ond method: Using the longitudinal pro�leWe an use the fa t that the muons leave their energy unformly (E / pathin matter) to distinguish pions from muons. always normalizing by the pathlenght as it is shown in the table 12.3.

Table 12.3: Values of the path lenght of ea h sample of the Tile alorimeter.For energies above 6 GeV, di�erent onditions are applied to the relationbetween the energy in ea h sample of TileCal (ESampleA, ESampleBC andESampleD) with the total energy in TileCal. They are shown in the table12.4. The values of the limits have been extra ted from the distribution ofESampleA=ET ile, ESampleBC=ET ile and ESampleD=ET ile for parti les at 7, 8and 9 GeV. In the �gure 12.4, it is possible to see these distributions forpions/muons samples at 7 GeV.ET ESampleAETile � xA ESampleBCETile � xBC ESampleDETile � xD7 GeV 0.0 < xA < 0.1 0.15 < xBC < 0.45 jxDj > 0.058 GeV 0.0 < xA < 0.1 0.20 < xBC < 0.40 jxDj > 0.059 GeV 0.0 < xA < 0.1 0.22 < xBC < 0.37 jxDj > 0.05Table 12.4: Conditions under the energy in ea h sample of TileCal respe t to the totalenergy in TileCal. The limits have been extra ted from the distribution of ESampleA=ETile,ESampleBC=ETile and ESampleD=ETile for parti les at 7, 8 and 9 GeV.Figure 12.4: Ratio of the energy in ea h sample of TileCal respe t to the total energyin TileCal for pions/muons samples at 7 GeV with the limit used in red.

12.5. Number of Parti les 27312.5 Number of Parti lesFor ele trons, the onditions under the 2nd Cherenkov ounter and thehigh-level hits, as well as the TRT information, seem to be good to sele tthem properly from the mixed sample3. Whi hever minor is the energy, thereare less and less ele tron, as the same time that in rease the ontaminationof muons.In the same way, the number of pions in LAr also de reasex at smallerenergies, (see the table 12.5 to ompare the di�erent number of parti les at1-9 Gev). In TileCal, it is more diÆ ult to sele t the pions due to the large ontamination of high energy muons, oming from the high energy line4.ET Total Ele trons Pions Muonsparti les parti les # in LAr (%) # in LAr (%) # in LAr (%)9 GeV 50599 31618 62.48 2687 5.31 779 1.548 GeV 49948 30521 61.10 1983 3.97 1404 2.817 GeV 51150 27318 53.40 1459 2.85 3279 6.416 GeV 53440 26988 50.50 1098 2.05 5878 11.005 GeV 55173 22475 40.73 651 1.18 8914 16.164 GeV 58233 58233 23.70 176 0.30 14668 25.183 GeV 59870 12131 20.26 227 0.38 15902 26.562 GeV 62625 6753 10.50 96 0.15 19581 31.271 GeV 65711 1918 2.92 71 0.11 23614 35.94Table 12.5: Number of ele trons, pions and muons at 1-9 GeV deposited in LAr andtheir per entages with respe t to the total number of parti les.

3When the e� ontamination in a pion sample was evaluated by V. Giangiobbe (Pysi sMeeting, Mar h, 2003):- e� ontamination was very small between 9-6 GeV (<2%)- SigniÆ ant e�e t appear bellow 5 GeV- It is very diÆ ult to separate e� from pions bellow 3 GeV4There are also problems with the low energy muons (�2 GeV) whi h does not deposittheir energy in the last Tile sampling and therefore they are taken as pions, but this ontribution is negligible

274 12. Clustering for VLE parti les from Combined Test BeamThe �gure 12.5 shows as the number of ele trons and pions in LAr alorimeter de rease at smaller energies, while there are more and moremuons.

Figure 12.5: Distribution of the ET deposited by ele trons (green), pions (blue) andmuons (red) in the LAr alorimeter at 2-9 GeV.

12.6. Clustering information in CBT ntuples 27512.6 Clustering information in CBT ntuplesAfter running Athena with the re onstru tion pa kage for the CombinedTestBeam2004 alled Re ExTB, (see Appendix 1 for more information aboutRe ExTB pa kage), we obtain a CBNT ntuple where the information about lusters is the next:� EM lusters: lusters from the sliding window algorithm.� TB EM lusters: lusters from an algorithm used in previous testbeam. It has been added to allow omparison. It is a window of 3 x 3 ells.EM lusters and TB EM lusters use only ells from the LAr alorime-ter.� CMB lusters: sliding window luster but they are done on towers( ombining LAr and Tile information) and not anymore ells. It wasnot working for the moment be ause of a oordinate problem betweenLAr and TileCal: LAr is shifthed just 3 modules to Tile by \halfmodule"5:- TileCal has just 3 modules -0.15 < � < +0.15- LAr has -0.2 < � < 0.2� Topo EM luster and Topo Tile luster: The TopoCluster algo-rithm is de�ned in a separated way for LAr and TileCal. The defaultvalues are:- seed threshold is E=�noise > 6- neighbor threshold is jE=�noisej > 3

5There are 3 sli es with �� = 0.1 in Tile and 4 sli es in LAr, shifted by half of thesli e.

276 12. Clustering for VLE parti les from Combined Test Beam12.7 Clustering results for ele trons12.7.1 Number of Clusters for ele tronsThe table 12.6 shows the number of lusters for ele trons using the slidingwindow algorithms (SW luster and SW TB luster) and the Topo EM luster algorithm. There are very similar results for the number of parti lesand the number of lusters, so the re onstru tion seems to work well forele trons.ET # parti les # Clustersparti les ele trons SW luster SW TB luster Topo EM luster9 GeV 31618 31585 31607 316148 GeV 30521 30475 30506 305147 GeV 27318 27252 27303 272926 GeV 26988 26878 26969 269615 GeV 22475 21689 22446 224644 GeV 58233 10994 13751 136703 GeV 12131 2292 11869 114722 GeV 6753 | 5853 45741 GeV 1918 | 1093 482Table 12.6: Number of lusters using the sliding window algorithms (SW luster andSW TB luster) and the Topo EM luster algorithm, respe t to the total number of ele -trons re onstru ted at 1-9 GeV.As it is possible to see in the �gure 12.6, the number of lusters is verysimilar in the three lustering algorithms, mainly from energies above 4 GeV.All of them show how the number of lusters in reases with the energy.Figure 12.6: Number of lusters using the sliding window algorithms (SW luster andSW TB luster) and the Topo EM luster algorithm, for ele trons at 1-9 GeV.

12.7. Clustering results for ele trons 277At 1-3 GeV, the number of lusters de reases a lot in the three algo-rithms:- For the ase of SW lusters this fa t is due to a ut (ET >2 GeV)de�ned by default in the re onstru tion hain of the algorithm. Thisis the reason why there are not results for SW lusters at 1 and 2 GeV.- For Topo EM luster the number of lusters is around the half thatwe expe ted.- For SW TB luster we obtain the best results, but the number of lusters obtained is less than the number of re onstru ted parti les.In any ase, it seems that it will be ne essary to hange the energy thresholdsin these lustering algorithms to will be managed of a good re onstru tionof the very low energy parti les.12.7.2 Energy resolution of Clusters for ele tronsThe table 12.7 shows the values of the energy resolution of SW luster,SW TB luster and Topo EM luster algorithm, for ele trons at 1-9 GeV.ET Energy resolutionparti les SW luster SW TB luster Topo EM luster9 GeV 7.57 8.92 10.488 GeV 8.51 10.04 11.647 GeV 7.85 6.93 8.516 GeV 8.83 7.81 9.625 GeV 13.07 15.47 17.344 GeV 11.04 11.47 14.783 GeV | 14.38 20.392 GeV | 20.52 34.991 GeV | 80.75 48.38Table 12.7: Energy resolution of SW luster, SW TB luster and Topo EM luster algo-rithm, for ele trons at 1-9 GeV.These values are preliminary, they are only usefull to ompare betweenalgorithms:- In the 9.1.1 release of the ATLAS software, there were problems inthe alibration of the energy in Lar and mistakes in the re onstru tion hain. These problems were solved in next releases of Athena.

278 12. Clustering for VLE parti les from Combined Test Beam- The results of energy resolution are worse than we expe ted, e.g. forele trons at 9 GeV, it is expe ted an ET resolution around 4%, insteadof 7-10%. So, it means that there is still noise in LAr (May be be ausethe Optimal �ltering is not applied in LAr, only in TileCal)- On the other hand, at 6 and 7 GeV, we obtain a resolution whi h isbetter than the one expe ted from the behaviour at the rest energies.It may be due to the beam onditions during the data taking.

Figure 12.7: Energy resolution of SW luster, SW TB luster and Topo EM luster al-gorithm, for ele trons at 9 GeV.

12.8. Improvement in the resolution of ele trons 27912.8 Improvement in the resolution of ele tronsThe samples of very low energy parti les are generated using a newrelease of the ATTLAS software, where the Oftimal Filtering is applied inLAr signal and the problems in the re onstru tion hain have been solved.Unfortunately, only samples with 9, 7, 5 and 3 GeV have been possible togenerate for the moment of this thesis.On the other hand, now the Topo luster is the global luster for LAr+Tile alorimeter, be ause from the release it is de�ned in the Re onstru tionpa kage of CBT in mode \super3D" instead of mode \all3D", (see hapter9 for more information), as well as new value are used for the TopoClusterthresholds as parameters:- seed threshold is E=�noise > 4- neighbor threshold is jE=�noisej > 312.8.1 Number of Clusters for ele tronsThe table 12.8 shows the number of lusters for ele trons using the slidingwindow algorithms (SW luster and SW TB luster) and the Topo EM luster algorithm. There are very similar results for the number of parti lesand the number of lusters, so the re onstru tion seems to work well forthem.ET # parti les # Clustersparti les ele trons SW luster SW TB luster Topo luster9 GeV 38319 38285 38314 383167 GeV 29588 29517 29578 295785 GeV 21704 21214 21690 217003 GeV 10262 21214 21690 10.258Table 12.8: Number of lusters using the sliding window algorithms (SW luster andSW TB luster) and the Topo luster algorithm, respe t to the total number of ele tronsre onstru ted at 9, 7, 5 and 3 GeV.At 3 GeV, the best results are from the spe ial SW algorithm for Test-Beam (SW TB), be ause again for SW lusters we have problem with the ut (ET >2 GeV) de�ned by default in the re onstru tion hain of the al-gorithm.

280 12. Clustering for VLE parti les from Combined Test Beam12.8.2 Energy resolution of Clusters for ele tronsThe table 12.9 shows the values of the energy resolution of SW luster, thespe ial Sliding Window algorithm for TestBeam (SW TB luster) and theTopo luster algorithm, for ele trons at 9, 7, 5 and 3 GeV.ET Energy resolutionparti les SW luster SW TB luster Topo luster9 GeV 4.81 4.41 5.047 GeV 5.32 4.62 5.465 GeV 6.61 5.97 6.903 GeV | 8.67 10.15Table 12.9: Energy resolution of SW luster, SW TB luster and Topo luster algorithm,for ele trons at 9, 7, 5 and 3 GeV.There is an important improvement of the resolution respe t to the re-sults shown in the se tion 12.7.2. Therefore the values obtained are of theorder that are expe ted for very low energy parti les.

12.9. Results for pions and muons 28112.9 Results for pions and muonsThe tables 12.10 and 12.11 show the number of Topo lusters(LAr+Tile)respe t to the total number of pions and muons re onstru ted, and theirenergy resolutions at 9, 7, 5 and 3 GeV, respe tively.ET # parti les # TopoClustersparti les Pions Muons Pions Muons9 GeV 5089 2551 5019 24817 GeV 3194 5170 3109 51205 GeV 1077 8723 1018 86733 GeV 344 13562 291 13546Table 12.10: Number of Topo lusters (LAr+Tile) respe t to the total number of pionsand muons re onstru ted at 9, 7, 5 and 3 GeV.ET ET resolution TopoClustersparti les Pions Muons9 GeV 21.05 |7 GeV 21.55 10.195 GeV 23.78 12.023 GeV 27.86 16.65Table 12.11: Energy resolution of Topo luster (LAr+Tile) for pions and muons at 9, 7,5 and 3 GeV, applying the ut E<0.1GeV as veto for muons.For now, the results from pions and muons are very diÆ ult to interpret,be ause there is still a mixing of the two types of parti les at energies above7 GeV, as one an see in the �g. 12.8 for muon and pions at 9 GeV.Figure 12.8: Transverse energy por pions (left) and muons (right) at 9 GeV in bothLAr and Tile alorimeter, after applying the ut E<0.1GeV as veto for muons.

282 12. Clustering for VLE parti les from Combined Test Beam12.10 Improvement in the sele tion of parti les:�/� separationIn order to separate better the pions from the muons, and mainly try toremove the ontamination oming from the high energy muons, an improve-ment in the se ond method (using the longitudinal pro�le in TileCal) as wellas a new (third) method using the MDT information have been developpedby V. Giangiobbe and C. Santoni.12.10.1 Se ond method: Using the longitudinal pro�leAnother way to use the longitudinal pro�le to separate pions from muons isupplied in this ase:- Fit the muon response in ea h TileCal sample in 2 parts (see �g. 12.9):{ Peak: p0�exp(-p2(x-p1-exp(-p2(x-p1)){ Tail: exp(p3�x2 + p4�x + p5)The set of parameters for the �t of the muon response in TileCal isshown in table 12.12.- Muons are sele ted asking E > 0.15 GeV in the whole sampleD.p0 p1 p2 p3 p4 p5Sample A 292 0.42 4.35 0.658 -3.37 5.86Sample BC 247 1.03 3.13 0.154 -1.77 5.97Sample D 4.18 0.42 4.86 1.25 -6.29 8.14Table 12.12: Set of parameters for the �t of the muon response in TileCal in 2 parts:peak (p0�exp(-p2(x-p1-exp(-p2(x-p1))) and tail (exp(p3�x2 + p4�x + p5)).Figure 12.9: Fits in ea h TileCal sample in two part (peak and tail), using the longitu-dinal pro�le to sele t muons.

12.10. Improvement in the sele tion of parti les: �/� separation 28312.10.2 Third method: using MDT informationIt is possible to separate and reje t muons from the pion sample putting uts onthe signal of the Monitored Drift Tube (MDT) hambers of the Muonspe trometer system in the Combined TB.Ussing the variable nMDTdig of the ntuple, one an ount the numberof hits in the di�erent MDT stations6 : BIL, BML, BOL, EI, EM, EO (see�g. 12.10), whi h have several eta regions.

Figure 12.10: Layout of the di�erent MDT stations: BIL, BML, BOL, EI, EM, EO.Ea h MDT station has several eta regions.One we know the number of digits for ea h event, we an assum thatevents with more than 8 digits in a MDT stations are muons (be ause wehave 8 plans of tubes per station).6The H8 Muon stand onsists of two parts: a barrel stand and an end- ap stand. Thebarrel setup is reprodu ing one ATLAS barrel se tor with its MDT and RPC stations. It onsists of six MDT hambers (two of ea h type: inner, middle and outer hambers) fullyinstrumented with Front End ele troni s (FE) read with a Muon Readout Driver (MROD)and fully equipped with an alignment system. There are six RPC doublets: four middle hambers (BML) and two outer hambers (BOL) in the barrel set-up. Two additionalbarrel stations where used in the test stand: one inner hamber (BIL) on a rotatingsupport for alibration studies and one outer (BOS) station (MDT+RPC) upstream ofthe muon wall for noise and ombined studies.In the end- ap stand whi h reprodu es a muon spe trometer end- ap se tor there are11 MDT hambers: two inner (EI), two middle (EM) and two outer (EO). As in the barrelthey are fully instrumented with FE and read out through one MROD.

284 12. Clustering for VLE parti les from Combined Test BeamLooking at the �gure12.11, one an see as the muons signal in ea h MDTstation has the peak position around number of digits = 8.

Figure 12.11: Number of digits in ea h MDT stations.So omparing the ele trons and muons signal in ea h eta region of ea hMDT station one an de�ne a set of uts to remove muons, as it is shownin table 12.13

12.10. Improvement in the sele tion of parti les: �/� separation 285

Table 12.13: Set of uts in ea h eta region of ea h MDT station to remove muons.After applying these uts in the number of hits in ea h MDT station,the orre t separation of pions from muons above 7 GeV it is possible, asone an see in the �g. 12.12

Figure 12.12: Transverse energy por pions (left) and muons (right) at 7 and 9 GeV inboth LAr and Tile alorimeter, after applying the ut in MDT stations.12.10.3 Number of Clusters for pions and muonsThe table 12.14 shows the number of Topo lusters for pions and muonsat 9, 7, 5 and 3 GeV afters appling the MDT uts. The number of lustersis very similar to the number of re onstu ted parti les, so the lusteringmethod seems to works well.

286 12. Clustering for VLE parti les from Combined Test BeamET # parti les # TopoClustersparti les Pions Muons Pions Muons9 GeV 2663 700 2638 6977 GeV 1661 3226 1636 32045 GeV 572 7822 548 77963 GeV 278 12671 249 12857Table 12.14: Number of TopoClusters respe t to the number of parti les for pions andmuons at 9, 7, 5 and 3 GeV after appling the MDT uts.12.10.4 Energy resolution of Clusters for pions and muonsThe table 12.15 shows the values of the energy resolution of the TopoClus-ter algorithms, for pions and muons at 9, 7, 5 and 3 GeV. There resolutionsfrom pions are rather similar, nevertheless the most important result is theimprovement in resolution from muons.ET ET resolution (Topo)parti les Pions Muons9 GeV 21.15 6.547 GeV 22.42 7.135 GeV 23.08 9.453 GeV 30.30 15.05Table 12.15: Energy resolution of Topo luster (LAr+Tile) at 9, 7, 5 and 3 GeV, afterapplying the MDT uts.12.10.5 Con lusions about pion/muon separation� For Ebeam > 7 GeV, the use of MDT uts to reje t muons is moresatisfa tory than using a ut on TileCal last sample (No bias).� For energies bellow 7 GeV, there are too mu h muons, and the ut onthe 3rd TileCal sample is justi�ed here (negligible energy expe ted forpions)7

7See several presentation of V. Giangiobbe's in CBT meetings at CERN about that.

12.11. Con lusions 28712.11 Con lusionsThe re onstru tion of very low energy parti les it is possible with thetools available in the re onstru tion pa kage for the Combined TestBeaminside the software of ATLAS (see Appendix 2).For the re onstru tion of ele tron from 1 to 9 GeV, the two sliding win-dow algorithm (SW and SW TB) are usefull. The values of the energyresolution obtained for VLE ele trons are of the order that it is expe ted forthis range of energy. On the other hand, the results from TopoClusters arevery ompetitive with the others.Nevertheless, it will be ne essary to apply some hanges in the energythreshold of the SW algorithm, in order to an apply it for 1-3 GeV ele tro-magneti parti les.The re onstru tion of pions and muons, �rst nedeed of a very a ura ysele tion of these parti les. Di�erent methods have been used in this wayto separate pions from muons: using the longitudinal pro�le of the muonsalong the alorimter or the MDT information in the muon spe trometer. We on lude to use the muon veto (ESampleD <0.15 GeV) for energies bellow7 GeV, and the MDT uts for larger energies. The values of the energyresolutions obtained with the TopoCluster algorithm are inside the expe tedones.However, it will be interesting a tunning work to adapt the energy thresh-old more properly to VLE parti les, and try to understand, per example,how to a�e t their hanges in the resolutions values and the way we anremoved the greater ammount of noise.

288 12. Clustering for VLE parti les from Combined Test Beam12.12 Farther Analysis: Threshold hanges for lus-tering algorithms12.12.1 Sliding Window algorithmWe will hange the energy threshold in the re onstru tion of the luster8,from the default value of 3000 MeV to:- energy threshold = 1000 MeV (for parti les at 4-9 GeV)- energy threshold = 500 MeV (for parti les at 1-3 GeV)12.12.2 Spe ial SW algorithm for TestbeamWe will hange the energy threshold in the re onstru tion of the luster9 ,from the default value to:- energy threshold = 1000 MeV (for parti les at 4-9 GeV)- energy threshold = 500 MeV (for parti les at 1-3 GeV)12.12.3 TopoCluster algorithmA set of ntuples with di�erent energy threshold have been generated (onlywith 1000 events in this ase)10:- Seed ut = E=�noise = 6.0, 5.5, 5.0, 4.5 and 4.0.- Neighbor ut = jE=�noisej = 3.0, 2.5 and 2.0Therefore, the ut under the ele troni noise has been hanged (in view ofthe pedestal results shown in Appendix1).� CaloTopoClusterEMMaker.TopoCluster.NoiseSigma is hanged from70 MeV to 100 MeV� CaloTopoClusterTileMaker.TopoCluster.NoiseSigma is hanged from25 MeV to 70 MeVFinally, in order to remove the ele troni noise (and taking into a ountthe previous analysis with simulated parti les at VLE in hapter 10), thede�ned thresholds of TopoCluster related with them will be \swit hed on"(before they are not applied).8To hange the energy threshold of SW lustering in the 10.0.2 release we use\LArClusterRe /LArCluster jobOptions.py".9To hange the energy threshold of spe ial SW lustering for TB in the 10.0.2 releasewe use \LArClusterRe /LArTBCluster jobOptions.py".10To hange the threshold of TopoClusters in the 10.0.2 release we use\CaloRe /CaloTopoCluster jobOptions.py".

12.12. Farther Analysis: Threshold hanges for lustering algorithms 289So their new values will be:a) For the EM alorimeter:- CellThresholdOnAbsEt = 10.0 MeV- NeighborThresholdOnAbsEt = 100.0 MeV- SeedThresholdOnEt = 100.0 MeVb) For Tile alorimeter:- CellThresholdOnAbsEt = 10.0 MeV- NeighborThresholdOnAbsEt = 70.0 MeV- SeedThresholdOnEt = 100.0 MeVwhere:� NeighborThresholdOnAbsEt must be of the order of the noise inEM and Tile Calorimeter11.� SeedThresholdOnEt must be of the order of the most energeti ellin the TopoCluster12.� CellThresholdOnAbsEt will be enough to be a non-zero value, tobe fast the re onstru tion.

11It will be better to put the value of the noise in ea h layer of EM and TileCal (seeAppendix 1), but it is not possible in this release of Athena.12These values in the EM alorimeter and in TileCal, ould be better tuned in the futureanalysing the ET deposited in ells of the TopoClusters (when this information will beavailable in the CBNT ntuple). For now, we will he k with the shown values.

290 12. Clustering for VLE parti les from Combined Test Beam12.13 Apendix 1: Pedestal analysisFrom the analysis of the energy distributions for very low energy parti leswe an extra t:- There are ele trons in the TileCal- The energy deposited by ele trons it bigger than the expe ted one.This two fa ts indi ate that the noise has not been properly removed bysumming only the ell energy with a value larger than the level of noise per ell shown in the table 12.2.We have studied the ele troni noise value (from pedestal) orrespondingto the di�erent runs of VLE parti les used in this analysis. The pedestalvalues13 an be seen in the table 12.16.ET �noise in LAr �noise in Tileparti les Presampler Front Middle Ba k A BC D9 GeV 150 60 120 100 70 70 608 GeV 150 50 130 100 70 60 507 GeV 140 50 140 100 70 70 606 GeV 150 60 120 100 70 70 605 GeV 140 70 140 110 70 70 604 GeV 180 50 130 100 60 60 603 GeV 140 50 130 100 65 65 652 GeV 150 50 120 100 65 65 601 GeV 140 50 140 100 65 65 60new �noise 150 50 130 100 70 70 60default �noise 60 32 60 70 25 25 25Table 12.16: Ele troni noise per ell (from pedestal) orresponding to the di�erentruns of VLE parti les used in this analysis. Comparison of the new proposed �noise valueand the old one.In view of the results we must hange the energy threshold for E ell.13The values of the pedestal does not depend on the energy of the beam, but we put thisvalue in the table, be ause we have extra t them from ea h run of VLE energy parti lesused in the analysis, in order to be sure that they have the same onditions as the datataken.

12.14. Apendix 2: Re ExTB, the Combined TB re onstru tion pa kage29112.14 Apendix 2: Re ExTB, the Combined TBre onstru tion pa kage12.14.1 To get the Combined Testbeam ntupleThe data �les are in / astor/ ern. h/atlas/testbeam/ ombined/2004.You have to he k out Re ExTB pa kage and to exe ute the jobOptions�le Re ExTB Combined 2004 jobOptions.py: jobOptions to run theCTB 2004 re onstru tion for real and simulated data. The following agsneed to be set:- doSim: False (real data) True (simulated data)- doInDet: Run Inner Dete tor re onstru tion- doTile: Run Tile re onstru tion- doLAr: Run LAr re onstru tion- doBeamDete tors: Run Beam dete tors re ontru tion- doDetailedNtuple: Write a detailed ntuple for LAr and Tile (at thelevel of raw data)You may also to hange the default run number to what you want andthe default number of events whatever you want.For ea h individual dete tor one an also �ll its individual ags set injobOptions:- InDetTBRe Example/InDetTBFlags jobOptions.py- LArTBRe /LArTBFlags jobOptions.py- CaloTBRe /CaloTBFlags jobOptions.py12.14.2 Di�erent trees in the Root-tuple� TileRe /h1000:Data from beam line dete tors (non Atlas dete tors) and TileCal de-tailed information.� TB /Tree:Gives publi information about the whole energy and lustering inboth alorimeters.� CALO /168 (Liquid Argon Calorimeter)CALO /169 (Tile Calorimeter)Data for ea h ell of TileCal and LAr (energy, eta position...)

292 12. Clustering for VLE parti les from Combined Test Beam12.14.3 TileRe /h1000Beam-line dete torsBeam s intillators, beam hambers, trigger pattern...- ryostat s intillator SC1 (whi h is not yet on TB/tree)- phantom alorimeter- Muon wallTileCal detailed informationsSignal in ea h PMTs, ADC samples, CIS parameters...All informations about those variables are on :http//atlas.web. ern. h/Atlas/SUB DETECTORS/TILE/testbeam/tb2004/analysis/online ntuple.des r12.14.4 TB/treeBeam line information� sADC[Ns int℄ : ad ounts in beam-line s intillators

� bp X[NBCP℄ : X position in beam hambers� bp Y[NBCP℄ : Y position in beam hambers

12.14. Apendix 2: Re ExTB, the Combined TB re onstru tion pa kage293TriggerTrigger pattern (1=physi s, 2=LEDs, 4=pedestals, 8= harge inje tion)More informations at :http://atlas.web. ern. h/Atlas/GROUPS/LIQARGSOFF/Re onstru tion/Code/Various text �les/ntup beaminstrumentation.html12.14.5 Calorimeters information� Eh Calo: total energy in TileCal + Lar� Eh EM: total energy in Lar� Eh HAD: total energy in TileCal� Eh PresB: total energy in Lar barrel presampler� Eh EMB[3℄: total energy in Lar front, middle, ba k� Eh Tile[3℄: total energy in TileCal samples A, BC, D� Eh TileGap: total energy in Gap (E ells, D4 and C10)12.14.6 Clustering variables : pre�x and suÆxPre�xes:� l n : number of re onstru ted lusters� l et: ET of luster� l eta: eta of luster� l phi: phi of luster� eemb0: energy deposited in barrel presampler� l eemb1: " " in 1st EM barrel sampling� l eemb2: " " in 2nd EM barrel sampling� l eemb3: " " in 3rd EM barrel sampling� l etileb0: energy deposited in Tile barrel A sampling� l etileb1: " " in Tile barrel BC sampling� l etileb2: " " in Tile barrel D sampling� l etilee0: " " in Tile ext. barrel A sampling� l etilee1: " " in Tile ext. barrel B sampling� l etilee2: " " in Tile ext. barrel D sampling

294 12. Clustering for VLE parti les from Combined Test BeamSuÆxes :� em: sliding window� topo em: topologi al lustering in LAr� topo tile: topologi al lustering in Tile� mb: ombined topologi al algorythm12.14.7 CALO/169 : TileCal� nhit: total number of ells� e ells: total energy ( = Eh HAD)� E ells[0-134℄: Energy in ell i ( in MeV, alibrated! )� EtaCells[0-134℄: Eta position of ell i� PhiCells[0-134℄ : Phi position� DetCells[0-134℄ : ode whi h gives the radial position for ell i65544 = sample A 131080 = sample A ext barrel 811016 = E ells73736 = sample BC 139272 = sample B ext barrel 270344 = C10 ell81928 = sample D 147464 = sample D ext barrel 278536 = D4 ellRelation between numbering in CALO/169 and ells positiona) Barrel on�guration

Example : E ells[112℄ is the energy in ell A-1 of the upper module

12.14. Apendix 2: Re ExTB, the Combined TB re onstru tion pa kage295b) Barrel + Extended barrel on�guration ( C side + E side)

12.14.8 CALO/168 : Liquid Argon CalorimeterThis part has the same variables as the TileCal one with the same meaning.� DetCells[0-2031℄ : 65=presamp, 81=front, 97=middle, 113=ba k12.14.9 Clustering algorithm ode for CombinedTBIn the release 10.0.2 (the a tual release of Athena for the re onstru tionprodu tion) the CaloTBRe H8 Cluster jobOptions.py, show the di�erent�les needed to hange in the lustering pro ess:- For sliding window (doEMCluster):\LArClusterRe /LArCluster jobOptions.py"- For spe ial TB lustering (doEMTBCluster):\LArClusterRe /LArTBCluster jobOptions.py"

296 12. Clustering for VLE parti les from Combined Test Beam- For TopoCluster (doCaloTopoCluster):\CaloRe /CaloTopoCluster jobOptions.py"More information about the TopoCluster algorithm and its new vari-ables in 10.0.2 release is provided by S. Menke in the Twiki web page14and his personal web15.

14https://uimon. ern. h/twiki/bin/view/Atlas/Topologi alClusteringhttps://uimon. ern. h/twiki/bin/view/Atlas/ClusterMoments.15http://www.mppmu.mpg.de/�menke

Referen es: 297Referen es:ATLAS Referen es:- ATLAS Collaboration: ATLAS Dete tor and Physi s Performan eTe hni al Design Report Vol 1, CERN/LHCC/99- 14, 25 May 1999- ATLAS Collaboration: ATLAS Calorimeter Performan e,CERN/LHCC/96-40, ATLAS TDR 1, (1996).C. Iglesias's presentations and analysis about lustering of VLEparti les:- C.Iglesias talks: TiCal-IFIC Weekly Meetings (Valen ia, SPAIN), atmy personal web page: http://i� .uv.es/�iglesias- C.Iglesias, Clustering of very low ET parti les, Software Workshop,Re onstru tion Working Group: Calorimetry, Sep,2004, CERN- C.Iglesias, Clustering of very low ET parti les, ATLAS ommuni ation(ATL-INT-SOFT-2005-001)C. Iglesias's presentations and analysis about Combined TBVLE parti les:- C.Iglesias, Clustering of very low ET parti les in Combined TB, AT-LAS Calorimetry Calibration Workshop, Hadroni Calibration Ses-sion, De 2004, Trata, Slokavia- C.Iglesias, Information about Combined TB. How to...?, personal webpage: http://i� .uv.es/�iglesias/- C.Iglesias,More about very low energy parti le, TileCal CommissioningMeeting 02/02/2005- C.Iglesias, Clustering for VLE parti les in CBT, TileCal Analysis andCombined Test Beam, 14 Feb, TileCal Week, CERN- C.Iglesias, V. Giangiobbe, Analysis with VLE runs in Combined TB,Final Combined Test Beam Workshop, 16 Feb, CERN- C.Iglesias, Pedestal analysis, personal web page: http://i� .uv.es/�iglesias/- C.Iglesias, Clustering of very low ET parti les with 2004 CombinedTestBeam data of ATLAS, ATLAS ommuni ation in preparation.

298 Referen es:V. Giangiobbe's presentations and analysis about CombinedTB VLE parti les:- V. Giangiobbe, C. Santoni, Analysis with VLE parti les, ATLAS Calorime-try Calibration Workshop, Hadroni Calibration Session, De 2004,Trata, Slokavia- V. Giangiobbe,Few things on erning low energy runs, 12/01/2005- V. Giangiobbe,Combined Testbeam analysis: Parti les separation inVLE runs, TileCal Analysis and Combined Test Beam, 14 Feb, TileCalWeek, CERN- V. Giangiobbe, C. Santoni, Separation between pions and ele trons inVLE runs, Physi s meeting, 05/03/2005- V. Giangiobbe, C. Santoni, Status of the VLE data analysis, CBTLAr-Tile pions analysis, 15/03/2005- V. Giangiobbe, C. Santoni, Muon and ele tron ontamination in thepion sample for VLE runs, 19/04/2005- V. Giangiobbe,Using MDT information to separate pions and muons,12/05/2005 and 17/05/2005Internal omuni ations- Tuan Vu Anh (from TRT), Tra ks information from TRT- C. Iglesias, V. Giangiobbe, Next Steps in the analysis with VLE runs- C. Iglesias, V. Giangiobbe, Task to do for VLE data in CombTB- C. Iglesias, V. Giangiobbe, List of orre t runs with at VLE in Com-binedTB 2004- C. Iglesias, V. Giangiobbe, Threshold Changes in Clustering algo-rithmsOther interesting results with VLE parti les:- A. Dotti (from INFN, Pisa), Results from ATLAS Tile Calorimeter:a omparison between data and Geant4 simulation, 24/05/2004, Siena(This study ontains resolutions for ele trons and pions taken in aspe ial VLE session of Testbeam arried out in 2003).

Referen es: 299- A. Fabri h, VLE muon ontamination, CERN, AB-ATB, 19 April2005.Other interesting results with TopoClusters in Combined TB:- M. Hurwitz, Summary of TopoCluster in TileCal, Commissioningmeet-ing, 2/2/2005.- N. Kers hen (CEA Sa lay), Linearity studies with the topologi al lus-tering on the Combined TB, LAr H8 analysis meeting, 31/05/2005.Usefull links:- TestBeam web page :http://atlas.web. ern. h/Atlas/SUB DETECTORS/TILE/testbeam/tb2004/TestBeam run.html- CBTN web page :http: //atlas.web. ern. h/Atlas/GROUPS/SOFTWARE/OO/domains/Re onstru tion/pa kages/CBNT Athena/CBNT Athena.htm- ATLAS Twiki web page:https://uimon. ern. h/twiki/bin/view/Atlas/

300 Referen es:

Con lusionsWe have wanted to show the importan e of the alorimeter analysis insidethe global studies of the high energy physi s in the ATLAS experiment. In on rete, the de isive role that the re onstru tion algorithms play to obtain abetter understanding of the behaviour of the parti les inside the alorimetersas well as the in uen e of the physi s e�e ts, su h as the Underlying Eventsor Minimum Bias, and the dete tor e�e sts, su h as the ele troni noise.From the �rst part of this thesis, we an extra t that the appli ationof the Energy Flow algorithm at parti le level in ATLAS an potentiallyimprove the jet energy resolution. This improvement is better at lowerpT rea hing values up to �40% of relative improvement in the resolution.Nevertheless, around 100 GeV the overlap between parti les is higher andthe gain in resolution of the energy for jets is marginal. Respe t to the softpro esses, the in uen e of the Underlying Events and the Pile-Up events atlow luminosity an be negligible for Energy Flow resolutions.However, one should keep in mind that this analysis has been done usinga fast simulation pa kage but also a very \simplisti " one, where the e�e tof the dete tor and also a lot of ir umstan es have not been onsidered.Atlfast supposes that ea h parti le deposited all its energy in one ell, whenin reality parti les deposit their energy in a set of ells forming a luster,whose shape and size depend on multiple fa tors as the type of parti le(EM or HAD shower), the energy, the e�e t of the magneti �eld and theamount of material in front of the alorimeter. Taking into a ount all thesefa tors requires the use of advan ed lustering algorithms apable of eÆ ientisolation of the individual shower together with an energy deposition model.For this reason, we have deeped in the se ond part of this thesis inthe analysis of the lustering algorithm using the full simulation and re on-stru tion tools, where the dete tor is modelled in a very a urate way byGeant. The main idea of this analysis is to ompare the di�erent lusteringalgorithms inside the ATHENA framework of ATLAS: TopoCluster, SlidingWindow luster, EGamma luster and di�erent one algorithms. We haveseen how these lustering algorithms an be tuned to obtain the best energyresolution when re onstru ting very low energy parti les.The results obtained from TopoCluster algorithm in the three samples(�0�s, ���s and neutrons) are very promising. They show that TopoClustersis a very useful tool in the study of the lusters and it provides a very goodre onstru tion of the lusters, even in the ase of parti les at very low energy.With the appropiate hanges in the energy thresholds of the Seed Cell andthe neighbord ells, we have removed the low eÆ ien y of TopoClusters at1-5 GeV and the largest amount of ET is deposited inside them. The energy301

302 Con lusionsresolutions obtained with TopoCluster are very similar to the obtained bythe one algorithms for ���s and neutrons and even better than Egamma(Sliding Window) lustering for �0�s.We have also used the TopoCluster algorithm to study the e�e t of theele troni noise in the size of the luster and the worsening of the resolution.So, TopoCluster is a usefull tool to study the lusters and it allows us a morerealisti method to olle t the ET deposited in ells, that a window with adeterminated size or a one with a �xed radius.Finally, luster formation must be validated with real data. In this sense,we have used the very low energy data (1-9 GeV) of ele trons and pionstaken during the Combined Testbeam 2004. The last part of this thesisshows a omparison among the di�erent lustering algorithms presented inthe Combined Testbeam ontext: the sliding window algorithms (EM lus-ters, TB EM lusters and CMB lusters) and the TopoCluster. Be ause thesesamples were a mixing of pions, muons and ele trons, it was ne essary toapply several uts in order to sele t the desired parti les.At the end, we an on lude that the re onstru tion of VLE it is possiblewith the tools available in the re onstru tion pa kage for the Combined TB.The values of the energy resolution obtained by the two sliding windowalgorithm (SW and SW TB) for VLE ele trons are of the order that it isexpe ted for this range of energy, and the TopoClusters results are very ompetitive with the others.On the other hand, di�erent methods must be used to separate pionsfrom muons. We on lude to use the muon veto (ESampleD <0.15 GeV) forenergies bellow 7 GeV, and the MDT uts for larger energies. The values ofthe energy resolutions obtained with the TopoCluster algorithm are insidethe expe ted ones.These results are even better than the obtained in the se ond part ofthe thesis, due to the improvement in the analysis tools of the softwareand the greater knowledge of their fun tionalities. Nevertheless, it will beinteresting a tunning work to adapt the energy thresholds more suitably toVLE parti les for SW algorithm and TopoCluster, as we have mentioned inthe \further analysis" se tion, and try to understand, per example, how toa�e t their hanges in the resolutions values and the way we an remove thegreater ammount of noise.

Agrade imientosMirando ha ia atr�as, en los 6 a~nos que llevo en F��si a de Altas Energ��as, veoque ha er un do torado no signi� a solo aprender de part�� ulas o de ModeloEst�andar, ompilar orre tamente en Athena o mejorar la e� ien ia de unalgoritmo. Signi� a mu ho m�as.Signi� a admira i�on, pues ono es a gente a quien admiras y respetas,por su dedi a i�on al trabajo, por ser exigentes pero justos, por su integri-dad y sobretodo por el ari~no que muestran desde sus posi iones de \rela-tivo poder", omo ser��an Toni Ferrer y Emilio Hig�on en Valen ia, MartineBosman y Enrique Fern�andez en Bar elona y Mar os Cerrada y Juan Al- araz en Madrid. Guardo un hue o espe ial en mi oraz�on para Mar os, porser mi primer jefe en este mundillo, y quien me dio mi primera oportunidadjunto on Lu ila.Signi� a amistad, pues tengo la suerte de ontar on muy buenos amigosentre mis ompaeros. Nun a olvidar�e omo me re ibieron Carmen, Angelay Carlitos, mi primer d��a en el CIEMAT, y on que pa ien ia resolv��an misnumerosas dudas on Linux...Sobretodo, quiero agrade er lo mu ho que meayud�o Carmen durante mi tesina a pesar de estar ella en los ltimos mesesde su tesis. Ahora que he pasado por lo mismo, y se lo \ apri hoso" que esel LaTeX, lo valoro a�un m�as.As�� mismo, re uerdo on a~noranza mis \ harretas" on mi \ ompi" enBar elona: Olga, que a�un estando al otro lado del planeta (en Chi ago) sigollam�andola as��. De Eva, no puedo de ir otra osa m�as que es la persona m�asbondadosa que onoz o (aunque me matar�a uando lea esto;-) ). Mi amis-tad on Os ar aunque empez�o tirante por ser ambos de ara teres fuertes,se fundament�o en una gran d�osis de omprensi�on y apoyo en los peores mo-mentos. As�� mismo guardo muy gratos re uerdos de nuestras omidas engrupo: Ana, Ester Aliu, Ester Segura, Lluis...Signi� a ompa~nerismo, por el buen \rollo" que hab��a siempre entretodos los be arios del IFAE, siempre dispuestos a ayudarte en ualquier osa:resolverte aquella duda de Athena (Mireia, mil gra ias), los problemas quesurgian durante el QC en el taller (Pepe, siempre tan r�apido), esos papelesde be a que faltan por ha er (Javi), esas harlas �los�o� as on Fran es(siempre on sus le hugas), y a los dem�as: Xavi Portell, Xavi Espinal, Oriol,Carolina...tambien os tengo un enorme ari~no.Signi� a ompli idad, que es lo que siento uando veo a Jes�us y aHugo, aunque hayan pasado 4 meses desde la �ultima vez que nos vimos, ompartimos on�den ias y mil historias juntos.Signi� a una segunda oportunidad, que es lo que me dieron en Va-len ia. Siempre les agrade er�e a Toni y Emilio el re ibirme on los brazos303

304 A knowledgementsabiertos y darme su apoyo y soporte ient��� o, trat�andome omo una m�asen el grupo. Tambi�en a Vi toria por su inter�es en mi trabajo y por ser tan on ienzuda en su orre iones, riti as pero siempre onstru tivas.Por su parte, Belen, Cristbal y Esteban me lo pusieron muy f�a il, tantoen Valen ia, omo en nuestras \estan ias" en el CERN. A�un estando lejosde asa intentamos ha er del SUITE HOME o del Foyer nuestro hogar par-ti ular.Adem�as, en el IFIC ont�e on la ayuda y amistad de Jose-Enrique, nosolo para osas de Athena, sino tambi�en para desahogos en momentos deestr�es... llev�andome a tomar un af�e asi a rastras.Signi� a distan ia, tener lejos a la fam��lia: perderme la gradua i�on demi hermano, la imposi i�on de banda de mi hermana, la boda de mis primoso el bautizo de los sobrinos. Soy siempre la que falta porque no se sabe enque pais o en que uidad ando ( omo dir��a mi abuela), por eso se agrade eque uando vuelvas te lo hayan grabado en video y te lo uenten todo aldetalle.Tambi�en agradez o lo mu ho y muy bi�en que me uidaron mis t��os yprimos uando estuve en Madrid, y el apoyo re ibido de mi familia, espe- ialmente de mi t��a Manolita y mis abuelos, que ha en que la distan iaparez a menor, pues on una llamada y sus onsejos te dejan omo nuevo.Finalmente, y no por ello menos importante, me gustar��a agrade er aXose el estar siempre a mi lado, que el brillo de sus ojos me arranque unasonrisa aunque est�e triste, que su on�anza en m�� me haga superar todoslos obst�a ulos, que su ari~no no entienda de distan ias ni de horarios, quesu amor sea por en ima de todo y para siempre, hoy omo novio, ma~nana omo marido.