1 muon reconstruction in the atlas experiment michela biglietti dottorato in fisica fondamentale e...

41
1 Muon Reconstruction in Muon Reconstruction in the ATLAS experiment the ATLAS experiment Michela Biglietti Dottorato in Fisica Fondamentale e Applicata, XVI ciclo Università di Napoli “Federico II”

Upload: deirdre-cori-white

Post on 04-Jan-2016

217 views

Category:

Documents


0 download

TRANSCRIPT

1

Muon Reconstruction in the Muon Reconstruction in the ATLAS experiment ATLAS experiment

Michela Biglietti Dottorato in Fisica Fondamentale e Applicata, XVI ciclo

Università di Napoli “Federico II”

2

The The LLarge arge HHadron adron CColliderollider Proton - proton collider Centre of mass energy of 14 Tev

(7+7) previous accelerations in the,

linac (50 MeV), PS (25 GeV) and SPS (450 GeV)

Circumference of 27 km 23 collision per crossing, 109

events/s (most soft hadronic interactions)

Energy per proton 7 TeV

Bunch spacing 25 ns

Bunch size 15 m 12 cm

Protons per bunch 1011

Bunches per ring 2835

Beam lifetime 10 hours

Design luminosity 1034 cm-2 s-1

Currently under construction in the LEP tunnel scheduled to start in the 20074 experiments : Atlas, CMS, LHCb, Alice

W (E/m)4R-1

3

Physics @ LHCPhysics @ LHC

Total p-p cross-section 80 mb 109 events/s Most are large distance, soft collisions

QCD background S/B very low

(exe: (Hm=150Gev)/(jetpt=700Gev) ~10-5 ) Pile up

Hard interactions overlapped with ~ 25 soft collisions

Need of good trigger system and fast detector response

4

The LHC physics programmeThe LHC physics programme Factory of all SM and new particles with masses in the TeV

range SM Higgs boson search

Exp limit (LEP): mH>113.5 Gev/c2 LHC will be able to observe a SM Higgs up 1 TeV and to measure his

mass and couplings with high precision SUSY particles search Precision measurements

huge production of W, Z, b and t particles• exe: tt cross section ~ 1 nb (0.8 event/s)

B physics low luminosity running (L = 1033 cm-2 sec-1)

• b quark identification is not hidden by pile-up LHCb

New physics

5

SM Higgs boson searchSM Higgs boson search

Low mass region (mH<130 GeV)

H , H bb

Intermediate mass region (130 GeV < mH< 2 mZ)

H WW(*), H ZZ*

High mass region (mH > 2 mZ )

H WW, H ZZ, H tt

The channels experimentally most promising are those with leptons in final state.

H ZZ 4l “golden channel”H ZZ is one of the most promising

Production cross sec.

Decay BR

Higgs boson signal needs to be extracted from a background of several orders of magnitude larger.

g

gt H

H

q

q

W,Z

6

The Atlas Apparatus The Atlas Apparatus General purpose

apparatus Lenght of 46 m,

diameter of 22 m Onion shell structure,

two endcaps ad one barrel

Inner tracker, calorimeters, muon spectrometer

Inner tracker cointained in a solenoid (max 2 T), muon spectrometer in a toroid (air core, max 3.9 T for barrel, 4.1 T for endcap)

108 electronic channels

7

Atlas design criteriaAtlas design criteria

Large acceptance Very good e.m. calorimetry for detection of e and

and energy measurements, hermeticity. High precision muon momentum measurements

(accurate tracking in the inner detector for low pt muons and large level arm of the muon spectrometer), low PT trigger capability

Efficient tracking at high luminosity for lepton-momentum measurements, for b quark tagging, reconstruction of B decay at lower luminosity

8

Conventions Conventions z direction along the beam

pipe x-y define the plane

transverse to the beam direction

Positive x-axis points from the interaction point to the centre of the LHC ring, positive y-axis points from the interaction point upward

Cylindrical coordinates useful : , , R

Pseudorapidity : = -ln(tan(/2))

cot

X

YZ

9

The MuonThe Muon Spectrometer Spectrometer

16 sectors in (small and large) Instrumented with trigger and

precision chambers Muon binding

|| < 0.7 from barrel toroid 1.4<||<2.7 from two endcap

magnet 0.7<||<1.4 transition region

Open structure of magnets minimizes the effect of multiple scattering and energy loss

Design performances pt/pt 10% for pt = 1Tev Momentum and mass

resolution of 1% for reconstructed 4-muons final state

view

RZ view

10

The Muon Precision Chambers The Muon Precision Chambers

MDTs (Monitored Drift Chambers) Basic element is a tube with a diameter of 3 cm and a variable

lenght, from 70 cm to 630 cm Tubes arranged in multilayer of 3 (4 for the inner stations) Single wire resolution 80 m

CSCs (Catod Strip Chambers) MWPC with segmented cathode strips read-out both orthogonal

(precision measurements) and parallel to the anode wires In the innermost ring of the endcap region, 2 < || < 2.7 (faster, for

high multiplicity) Spatial resolution 60 m, small drift time (30 ns), time

resolution 7 ns

Precise measurements in the bending direction

11

The Muon Trigger Chambers The Muon Trigger Chambers

Barrel RPCs (Restistive Plate

Chambers): on both sides of middle MDT stations and above or below the outer MDT station.

For bunch crossing identification and second coordinate ()

measurements. Trigger system covers the region with ||<2.4

Endcap TGCs (Thin Gap Chambers) : 3 stations close the MDT middle station. Consists of MWPC (wires for trigger signal, parallel to those of MDTs ) with read-out strips orthogonal to the wires for the second coordinate measurement

Time resolution 1 ns

Spatial resolution 1 cm

12

HEP Computing HEP Computing

In the past elementary particle experiments the dominant programming language was Fortran Introduced when experiment were small

• Small detectors, small number of workers

Today experiments are HUGE Stringent demands not only on the detector’s hardware but

also on software needed to simulate, reconstruct and analyse physic events

Need to change from procedural to object-oriented programming

… but sometimes Fortran is hard to kill … Strong links with the past We have inherited too many useful and working tools

13

The Atlas CollaborationThe Atlas Collaboration1700 members from 144 institutions and 33 countries

14

Offline Software in ATLASOffline Software in ATLAS Goals

Detector response simulation and geometry description Reconstruction of physically interpretable objects from raw data Storage ( 100 Mbyte/s ) Analysis Visualization …

Features High complexity Long lifetime (20 years!) Large data volumes Many developers, most of them are not expert in programming

Needs of Flexibility , mantainaibility, uniformity, modularity, reusability,

distribuited development mechanisms … Choice to use OO/C++ techologyChoice to use OO/C++ techology

15

Object Oriented Programming Object Oriented Programming FeaturesFeatures An OO application is a collection of collaborating objects that interact

to each other by exchanges messages Encapsulation

Implementation details are hidden Clients only see object’s interface, i.e. his behaviour

Polymorphism and Inheritance Different kinds of objects can belong to a abstract common class and

have similar features and a common interface The “shared operation” behavior depends on the type of the object

Abstraction Real objects are abstracted into classes, similarities among objects are

implemented in terms of interface, using polymorphism and inheritance Reduction of complexity, increase of modularity, flexibility, robustness

and code reuse Object Orientation is the widest used technology for large

software projects C++ is a mature, standard and widely used OO language

16

Offline Reconstruction in AtlasOffline Reconstruction in Atlas

Data flow

Tracking

Calorimetry

Muon

Tracks

Em cluster

Muon

Calo Jets

Combined Muon

Analysis

Raw digits

Detector element E/

identificationEvent

MC truth & simulation

Atlas Sim. and rec. algorithms

dataObject

Detector descriptor

17

Offline Reconstruction in AtlasOffline Reconstruction in Atlas

Converter

Algorithm

Event DataService

PersistencyService

DataFiles

AlgorithmAlgorithm

Transient Event Store

Detec. DataService

PersistencyService

DataFiles

Transient Detector

Store

MessageService

JobOptionsService

Particle Prop.Service

OtherServices

HistogramService

PersistencyService

DataFiles

TransientHistogram

Store

ApplicationManager

ConverterConverter

Necessity of a framework: a template application into which developers plug in their code, using mechanisms defined by the framework, collections of functionality, common vocabulary …

Athena

18

Offline Reconstruction in AtlasOffline Reconstruction in Atlas

Packages should be made of many indipendent Athena top-algorithms

Transient objects are passed via the Transient Data Store

Algorithms are only coupled through the data

Algorithm1

Algorithm2

Algorithm3

DataObj

DataObj

DataObj

DataObj

DataObj

DataObj

T

D

S

Algs2Event

Algs1

Algs3

Algorithms and data objects should be placed in different packages

Algorithmic packages depend on data, not

viceversa

Software organization inside Athena

The detector description, the even structure and the implementation of recostruction algorithms are separated

19

Muon ReconstructionMuon Reconstruction At every interaction the signals from each sub-detector

that pass the trigger selection are recorded for processing by the offline reconstruction software

A charged particle moving in the detectors leaves a trace of hits

The goal of the reconstruction is to find a track associated to the hits and and perform a fit to obtain the best estimates of the set of parameters that describes the particle trajectories To define a 3D curve we need of 5 parameters: usually a0, z0, ,

cot, ±1/PT

The result of the fit is the best estimate of th track parameters and their covariace matrix at every position along the track

Track can be traced to the beam line to searches for matching to the vertex

20

Muon Reconstruction in AtlasMuon Reconstruction in Atlas

Old package Muonbox in F90 Still working but hard to integrate with all the Atlas

software Lacks of flexibility and maintainaibility Potentially dangerous to use for the standard Atlas

muon reconstruction

Necessity to have a new C++ package MOORE (Muon OO REconstruction)

21

Software for Muon Software for Muon Reconstruction and MeReconstruction and Me

My present work consists of contribute in developing the C++ stand alone

package for muon reconstruction (Moore)• Integration with Atlas offline software/reconstruction

framework• Architecture and design• Test

develop a package for combined muon reconstruction, Inner Detector + MuonSpectrometer (MuonIdentification)

This is finalised to physics studies (together with validation of software, check of the quality of simulated data producted, detector studies)

22

Atlas Data Challenges Atlas Data Challenges Massive production of simulated physics events Needed for

software validation• Check of the full chain generation-simulation-offline reconstruction• Data storage

high level trigger studies detector performances studies physics studies

DC1 (July/August, October/November 2002 ) We are involved in muons-final states events production

Single ’s for several energies (in total ~107 events) cavern “background events” 105 H 4, A/H 2 106 Z for calibration ~107 events Productions to be done in Roma, Napoli, Lecce

23

MOOREMOORE Reconstruction Reconstruction StrategyStrategy

Searches for regions of activity From the RPC/TGC measurements “-

Segments” are created

Searches for R-Z regions of activity For each “-Segment”, the associated MDTs is

found and a “crude” RZ Segments is built (essentially collections of z hits) .

rpc

rpcrpc

MDT

24

MOOREMOORE Reconstruction Strategy Reconstruction Strategy Pattern recognition

and outer Roads– Inside MDTs the drift distance is

calculated from the drift time, by applying various corrections on it (TOF, second coordinate, propagation along the wire, Lorenz effect). From the 4 tangential lines the best one is found.

– All the “MDT segments” of the O station are combined with those of the M layer. The MDT hits of each combination are added to the phi-hits of the “Phi Segment”, forming “outer” track candidates. All the successfully fitted candidates are kept for further processing. Final tracks

The successful “outer” track is subsequently used to associate inner station MDT hits. A “final” track is defined as a successfully fitted collection of trigger hits and of MDT hits from at least two layers.

MDT mutilayer

25

Architecture and Design Architecture and Design

MooMakePhiSegments

RPC/TGC digits

PhiSegments

MooMakeRZSegmentsMDT digits

MooMakeRoads CrudeRZSegments

MooMakeiPatTracks MooRoads

MooiPatTracks

MooMakeNtuples

Ntuples

MooAlgsMooAlgs

MooStatisticsMooStatistics

Each step is driven by an Athena top-algorithm

Transient objects are passed via TDS

Independent algorithms, the only coupling is through the transient objects

Results : Results : less dependencies, code less dependencies, code is more maintainable, modular, is more maintainable, modular, easier to develop new easier to develop new reconstruction approaches reconstruction approaches

26

Architecture and Design (2)Architecture and Design (2)

MooEventPackages organization

27

Efficiency vs PEfficiency vs PTT

Single muon studies

PT (GeV)

(%)

A Muon track consists ofhits from at least 2 stationsand is successfully fitted.

28

Efficiency vs Efficiency vs , cot, cot

PT = 20 GeV

(rad)

N e

ven

t

N e

ven

t

cot

29

PPTT resolution resolution

Pt resolut ion 20 gev Pt resolution 100 gev

PT = 20 GeV PT = 100 GeV

N e

ven

t

N e

ven

t

30

Effect of dead materialEffect of dead material

No material

Including in the fit the material crossed by the track (chambers + toroids) .

Get full information from AMDB (via “trmusc” from MUONBOX)

1./PT Pull

20 GeV

NO Material Effects in the fit Material included in the fit

1./PT Pull

20 GeV

pull = (Xgen – Xrec)/rec

= 1.0

N e

ven

t

N e

ven

t

31

Combined Muon ReconstructionCombined Muon Reconstruction Improve muons identification efficiency

Discrimination of muons from rays in the muon spectrometer Reconstruction of low energy muons that do not reach the middle and

outer stations of the muon spectrometer Rejection of decay muons (from k and ) by requiring tracks originate

close the interaction point Discrimination of muons in hadronic jets from hadrons. An efficient muon

b-tagging requires a good muon identification for non isolated muons Improve track parameters

Achieve the best possible momentum resolution Reduce tails in the momentm resolution of the muon spectrometer,

resulted from fluctuation in energy loss in the calorimeter Improve charge determination for high energy muons

Understand the detector Check the calibration of calorimeter. Cross check the results from the inner detector and muon spectrometer

(for muons with momenta from 20 GeV to 70 GeV)

32

Combined MuonsCombined Muons

pT > ~100 GeV: profit from greatly superior Muon Spectrometer momentum precision

~20 < pT < ~100 GeV: combination more

precise than Inner Detector or Muon Spectrometer alone

pT < ~ 20 GeV: purpose is purely identification => no parameter improvement over indet measurement Reduce decay-in-flight

background.

33

Combined Combined Reconstruction/Reconstruction/MuonIdentificatonMuonIdentificaton Purpose: associate tracks found by Moore in Muon

Spectrometer with inner detector tracks and calorimeter information to identify muons at their production vertex with optimum parameter resolution

2 principle methods: Stand-alone muons – MS track and track-segment

parameters propagated to beam-axis Combined muons – match MS to ID tracks and fit

combined parameters

Input – results of Inner Detector, Calorimetry and Muon Spectrometer (Moore) reconstruction (as C++ objects through Athena framework interface)

34

MuonIdentification Method MuonIdentification Method MS track and inner station

segment parameters propagated to beam-axis Angle resolutions dominated

by Coulomb scattering in calo Parametrise calorimeter

effects – function of p and (i.e. thickness)

or measure energy loss from calibration of observed energy deposition

MS track is express at vertex

2 fit for matching of inner detector and muon spectrometer tracks parameters

Final fit

calorimeter

Muonspectrometer inner layer

Beam spot

Energy loss and multiple scattering

35

Track Combination and Final Fit Track Combination and Final Fit

From the point of view of interfaces, the track combination and final fit easy to perfom Muid and Moore track

both ihnerit from the base class Track

Inner Detector track is a (instance of) Track

The same happens to the Fitter objects

36

A First approach A First approach

Association of the reconstructed muon Track (from Moore) with the Truth Event track(from MC/simulation). Calculation of the difference between the energy atthe vertex and the energy at the entrance of the Muon Spectrometer

Energy loss from truth

GeV

Single Pt = 20 Gev

N e

ven

t

Need to parametrise calorimeter effects

37

MuonIdentificationMuonIdentification: First Look : First Look

Single Pt = 20 Gev

cot pull at vertex

N e

ven

t

GeV

Correction on PT

Muidtrack at vertex

Moore track atMS entrance

Single Pt = 20 Gev

38

MuonIdentificationMuonIdentification First Look First Look

Single + Pt = 20 Gev

- pull at vertex

N e

ven

t

N e

ven

t

Single - Pt = 20 Gev

39

MuonIdentificationMuonIdentificationFirst LookFirst Look

Moore PMoore PTT pull at the pull at theentrance of muon entrance of muon spectrometerspectrometer

MuID PMuID PTT pull at vertex pull at vertex

Single Pt = 20 Gev

Single Pt = 20 Gev

N e

ven

t

N e

ven

t

40

Plans for futurePlans for future

Continue software developing Completation of Muid method

• Get calorimeter information for energy loss• Get inner detector track from framework• Implement a fit method for track matching at vertex

Improve MuonIdentification design, need to modularize of the code eliminate superfluos dependeces exploit the new Atlas software (event structure, detector

description, framework facilities, event display … ) separate framework interface object/algorithms/events

Physic studies based on DC1 data produced in our site

41

Following Moore design … Following Moore design …

MuidStandAlone

Moore Tracks

CaloObjects

MuidComb

Stand alone MuidTracks

MuidNtuples

Ntuples

In.Det.Tracks

Combined MuidTracks