physics analysis with aliroot
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16-Sep-05 1
Physics Analysis With AliRoot
Peter HristovALICE CollaborationNEC2005, September 16, Varna
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OutlineThe framework: AliRootAnalysis examplesDistributed analysis and parallel analysis facilitySummary of the analysis tools in AliRootConclusions
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The framework:AliRootUp-to-date description of Alice detectors (geometry, physics processes, detector response, etc.)Rich set of event generators, easily extensiblePossibility to use different transport packagesRobust IO schemeUser friendly steering classes for simulation and reconstruction
Efficient tracking in the barrel detectors and in the MUON armElaborated reconstruction of the neutral particlesReconstruction of V0’sCombined PID based on the Bayesian approachESD classes suitable for further analysis Detailed analysis examplesPossibility to explore wide spectrum of heavy-ion and pp physics
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AliRoot Layout
ROOT
CINT HIST GRAPH TREES CONT IO MATH …
EG
EE
+A
liEn
GR
ID
ITS TPC TRD TOF PHOS EMCAL RICH MUON
FMD
PMD
START
VZERO
ZDC
CRT STRUCT
STEERAliSimulation
AliReconstructionESD classes
G3 G4 Fluka
Virtual MC
HIJING
PYTHIA6
DPMJET
ISAJET
EVGEN
Analysis
HLT
RAW Monit
HBTAN JETAN
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AliRoot: Execution Flow
InitializationEvent
GenerationParticle
TransportHits
SummableDigits
Event merging
Digits/Raw digits
Clusters
Tracking PID ESD Analysis
AliSimulationAliReconstruction
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Event ModelRAW data; Written once, read up to 3 times.
Size: 1(pp)- 50(PbPb) MB per event.Event Summary Data (ESD); Written up to 3 times, read many times. Contains all the information needed for analysis, fine-tune calibration and further processing into AOD. Single version for everybody.
Size: ~ 1/10 of raw per event.Analysis Object Data (AOD); Written many times, read many times. Specific for a set of analysis tasks.
Size: ~ 1/10 of ESD per event.Tag; Written few times, read many times.
Size: 100 B – 1 kb per event, exist many per event.Done for fast event data selection: global experiment tags, physics working group tags, user defined tags.
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Existing Analysis Examples in AliRoot
ESD analysis:V0 & cascade reconstruction/analysisOpen charm
Specific AOD-based analysis:HBTJetV0
MUONAny user can contribute with additional examples and extending the functionalities
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PT Distributions of ,K,pExperimental PT distributions.
Selection of tracks from the primary vertex: cuts on impact parametersPID: using probabilities as weights, taking the most probable type, taking type above a probability threshold,…
Corrections:Contamination: comparison of the PID and true MC particle type. Depends on the way one obtains the exp. PT spectra.Combined acceptance ~ Geometrical acc. x Decays x Reconstruction efficiency x PID efficiency. Depends on the primary vertex position, momentum, and occupancy => Comparison between MC kinematics tree and reconstructed particles.Resolution: comparison between the MC and reconstructed momenta.
=> The framework provides easy access to the kinematics tree.
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Example Histograms: PbPb events
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Meson Mass, Width, PT Distribution, Yield
Selection of tracks from the vertex, PID of kaons.Cuts to increase the significance (5 parameters for each pair: PT, azimuthal and polar angles, azimuthal and polar angles in the rest frame).Effective mass distribution for all pairs of kaon candidates (global and for different PT intervals).Effective mass distribution for the (combinatorial) background.
Event mixing: positive particles from the same event, negative from a different, but “similar” one. Similarity: close event impact parameters and number of negative particles. Event plane? One might rotate all the negative tracks accordingly.
Mass resolution, combined acceptance from MC.=> The framework provides easy access to events for mixing.
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Meson Mass in pp Events
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V0s and Cascades: PT Spectra, YieldsV0: pair of tracks with opposite charge, selected according to the following criteria:
Min. Allowed impact parameter(in XY) for each track.Max. Allowed DCA between the two tracks.Max. Allowed cosine of the V0 pointing angle.Min. And max. Radius of fiducial volume.Max. 2 => needs covariance matrices of the track parameters.
Cascades: V0 and “bachelor” track selected according the cuts above and in addition.
Mass window for V0.Effective mass distribution in different PT intervals -> fit (or background subtraction from mixed events) -> experimental PT.Corrections => Need for MC for combined acceptance, resolutions,…
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D* D0 Search for D0 candidate with some “loose” cuts. (See the D0 analysis classes.) combined with pion from the primary vertex -> Distribution of m(D0) - m(D0)
Secondary vertex close to the primary one. Need for precise secondary vertex finding/fitting, especially in the case of proton-proton events.
Estimation of the background distributions => event mixingCombined acceptance, resolutions, etc. => from MC=> Classes for precise secondary vertex finding/fitting are available within the framework
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Example: JetsLeading hadrons correlationsJet reconstruction algorithm: UA1 cone algorithm modified for HI
Cone size: R < 1pt cut
Background subtractionEvent by event jet identification
Jet parameters: multiplicity, kt, f(z), -jet
Jet spectrum
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Jets
Pythia
Hijing
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Tag eventInformation (meta-data) to select and analyze events of interest only via user-selected conditionsThe framework (inspired from STAR)
Collects the file identifiers where to find the eventsLocalizes the filesPasses the events to the analysis program
Metadata (> 70 parameters)Run specific informationInformation concerning the state of LHC per ALICE runDetector information per runInformation about each event being collected from PWGPopulated during and after ESD creation
Architecture defined, partially implemented, analysis cuts tested
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Distributed analysisPrototype demonstrated to workUsed routinely by one single userNot yet released to general users because of major middleware reorganization (Alien2/gLite) end 2005For most of the analyses the files have been “moved” to a single location to be analysedProposal for a Parallel Analysis Facility
Fast on line processing of data (calibration, tuning of algorithms, online physics results)Few users (detectors and PWG experts), many x a few events, short latencyLow cost farm of dual core processors
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Analysis Job StructureFile Catalogue
query
CE and SE
processing
User job (many events)
Data set (ESDs, other)
Job Optimizer
Sub-job 1
Sub-job 2 Sub-job n
CE and SEprocessin
g
CE and SE
processing
Job Broker
Grouped by SE files location
Submit to CE with closest SE
Output file 1
Output file 2
Output file n
File merging job
Job output
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AliEn2 Development
User Interface (gShell)Universal: only one for accessing all the GridsComplete: Provides all the functionality a user might needRobust: Does not crash or hang up in case of misuseSimple: Does not require expert knowledge to run it
New catalog:FastReliable
Secure data managment: encrypted access envelopes
Job agents:Response to analysis requestsPrioritiesQuotas
Transport protocol: xrootd
Uniformity with Root and PROOF
API: under active development, available now in RootInstallation: new installation utility for easy installation
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Parallel Analysis Facility
Interactive prompt analysisData recorded at CERN T0After first reconstruction pass analyze results using PROOF on CERN T1Check detector functioning and hot channels, calibration, alignment, physics
Prototyping in progressRedesign of the existing analysis classes using Root selectors
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Interactive Analysis with PROOF on a Large Cluster
PROOFPROOF
USER SESSIONUSER SESSION
PROOF PROOF SLAVE SLAVE SERVERSSERVERS
PROOF MASTERPROOF MASTER SERVERSERVER
PROOF PROOF SLAVE SLAVE SERVERSSERVERS
PROOF PROOF SLAVE SLAVE SERVERSSERVERS
Guaranteed site access throughPROOF Sub-Masters calling outto Master (agent technology)
PROOF SUB-PROOF SUB-MASTERMASTER SERVER SERVER
PROOFPROOF
PROOFPROOF
PROOFPROOF
Grid/Root Authentication
Grid Access Control Service
TGrid UI/Queue UI
Proofd Startup
Grid Service Interfaces
Grid File/Metadata Catalogue
Client retrieves listof logical files (LFN + MSN)
Slave servers access data via xrootd from local disk pools
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Summary of Analysis Tools
The tools work on ESD/AOD.Basic kinematics from Root: 3-vectors, 4-vectors, rotations, boosts, eff. masses, PT calculations
Geometrical tools: propagation of tracks, DCA, primary and secondary vertexes.
Specific: V0s, cascades -> AliV0vertexer, AliCascadeVertexer.General: AliITSVertexerTracks.
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Summary of Analysis ToolsImpact parameter of the interaction: based on ZDC energies and number of participants from ESD.Event plane: AliFlowAnalysis.Typical tasks:
Comparison with MC and access to the kinematics tree. Creation of “MC AOD”;Calculation of combined acceptance (“physics efficiency”);Background studies using the event mixing technique.
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(Trivial) Practical AdvisesInstantiate the objects outside the analysis loops and use setters inside. Use references instead of new objects.Do the pre-selection of tracks and particles in single loop before the main analysis. Use indexes to access the original objects.Use standard tools for sorting, minimization, etc. Do not rewrite the existing ROOT tools!Load to memory when possible (example: tree->LoadBaskets())Foresee checks for the data consistency
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ConclusionsThe main tools for data analysis are available in Root and AliRootThe analysis code based on ESD / AOD’s seems adequate, and is evolving according to feedbackThe infrastructure tools for distributed analysis are under active developmentSeveral detailed analysis examples are availableAnalysis infrastructure for distributed data will be offered to test users 1Q06
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