Muon Reconstruction Muon Reconstruction with Moore and with Moore and

MuonIdentificationMuonIdentification

Muon Reconstruction Muon Reconstruction with Moore and with Moore and

MuonIdentificationMuonIdentification

The Moore/MUID group

Atlas Physics Workshop

Athens, May 2003

OutlineOutline Reconstruction method and architecture Muon spectrometer inert material treatment Single performances H→4 Z→2 Test beam data reconstruction Moore and Muid as Event Filter algorithms Conclusions

TasksTasks Moore Moore (Muon Object Oriented REconstruction)

reconstruction in the MuonSpectrometer MuonIdentificationMuonIdentification

Muon reconstruction and identification Divided in two parts :

MuidStandAlone:MuidStandAlone: Back tracking of the MOORE tracks to the interaction point

Muid Comb:Muid Comb: Combination of the muon and the inner detector tracks

Both work in ATHENA (= the ATLAS reconstruction framework)

MOORE MOORE Reconstruction Reconstruction Strategy (I)Strategy (I)

MOORE MOORE Reconstruction Reconstruction Strategy (I)Strategy (I)

rpc

rpc

rpc

MDT

barrelbarrel projectionprojection

barrelbarrelRZ projectionRZ projection

Search for region Search for region of activity in the of activity in the

projectionprojectionand and RZ projection RZ projection

rpcrpc

rpcrpc

rpcrpc

MOORE Reconstruction Strategy(II)MOORE Reconstruction Strategy(II)

Pattern recognition in the Pattern recognition in the MDTsMDTs the drift distance is calculated the drift distance is calculated

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

Track segment combinationTrack segment combination. .

Track fitTrack fittrack parameters (a0, z0, track parameters (a0, z0, , cot, cot, 1./pt ) expressed , 1./pt ) expressed at the first measured pointat the first measured point

MDT mutilayer

MDT patternMDT patternrecognitionrecognition

MuonIdentification Method MuonIdentification Method

MS track parameters are propagated to beam-axis

multiple scattering parameterised as scattering planes in calorimeters

energy loss from truth or from Calo Reconstruction or from parametrization as function of (,p)

Refit muon track parameters expressed at vertex

Muon/ID tracks matching with a 2 cut-off 2 based on track covariance matrices

and the difference in the track parameters Combined track fit

calorimeterscalorimeters

Muonspectrometer inner layer

Beam spot

Energy loss and multiple scattering

Architecture (I)Architecture (I) C++ and OO technology High modularisation and flexibility

Easier to develop alternative recostruction approaches Successfully adapted for the test beam data reconstructionSuccessfully integration in the HLT frameworkPart of Moore will be used by Calib (MDT calibration)

Track class and Fitter class in common with the inner detector reconstruction (iPat)

MooAlgs MooEvent

• Separation of the algorithmic classes Separation of the algorithmic classes from data objectsfrom data objects

Architecture (II)Architecture (II)Pattern recognition is divided Pattern recognition is divided

in several steps.in several steps.

Each step is driven by an Each step is driven by an Athena top-algorithmAthena top-algorithm

Algorithms indepent, imply Algorithms indepent, imply less dependencies, code more less dependencies, code more maintainable, modular, easier maintainable, modular, easier to develop new reconstruction to develop new reconstruction approaches approaches

Separation of the algorithmic classes from data objects

Parameterization of the Inert Material (I)Parameterization of the Inert Material (I)

NO material

in the fit

1/PT Pull

Single Pt=20 GeV

Chamber

Material in the fit

The treatment of the inert material The treatment of the inert material

until Marchuntil March

No services available yet in Athena for the description of the inert materials

The ATHENA geometry service allowsThe ATHENA geometry service allows to take into account in the fit multiple scattering and energy loss in the material of the chambers.

Work in progress (waiting for a Material Service from GeoModel):

Parameterization of the material effects: Data driven approach: define a map of materials; tune

materials with the pull distributions (available) Geant4 based approach: describe all inert materials;

propagate geantinos; define a fine map of materials in the Spectrometer (in progress)

March 2003

A

BB C

Parameterization of the Inert Material (II)Parameterization of the Inert Material (II)

Main steps

•Define a segmentation of the Muon Spectrometer:

Binning in //L

•Estimate X0 and Energy Loss

in each //L bin

•Refit the track with 2 scattering centers per station

•Tune X0 and energy loss of the “scatterers” against the pull distributions

(L = trajectory path length)

1.2

1.8

3.13.6

5.47.8

Overall performances 1st

iteration

Overall performances 1st

iteration1/pt pull distributions with Parameterization of Inert Material and with Detector Material only

For fixed transverse momentum single muon

samples

Pt = 6 GeVPt = 6 GeV Pt = 20 GeVPt = 20 GeV

||| < 1| < 1

||| > 1| > 1

Single muons DC1 data

PT (GeV)

Efficiency vs pT Efficiency vs pT

Rather good agreement with

Physics TDR results

Moore/MuonID performances shown here are obtained with

• Release 6.0.3• A private improved version of MuonIdentification

•Tracking in the magnetic fields, bug fixes

• Moore with the full material description

MooAlgs-00-00-41

MooEvent-00-00-42

Single performancesSingle performances

Efficiency vs Efficiency vs

Stepping in the fit procedure needs to be optimized in the region |Stepping in the fit procedure needs to be optimized in the region ||>1|>1

Uniform efficiency vs phi

1/Pt Resolution vs Pt1/Pt Resolution vs Pt

Rather good agreement

with Physics TDR results

Pt (GeV)

1/Pt resolution vs 1/Pt resolution vs

Critical reconstruction in the transition region at low momenta

1/Pt resolution vs 1/Pt resolution vs

Worsening of resolution in the MuonSpectrometer in the feet region at low momenta

(1/pt pulls) vs (1/pt pulls) vs

Without Z constraintWithout Z constraintWithout Z constraintWithout Z constraint

Reconstruction with Muon Spectrometer Standalone (Moore + MUID Standalone)

Reconstruction with Muon Spectrometer Standalone (Moore + MUID Standalone)

With Z constraintWith Z constraintWith Z constraintWith Z constraint

HH44(I)(I)Evelin MeoniEvelin Meoni•DC1 sample (prod. in July 2002):DC1 sample (prod. in July 2002): HH44 (with mH=130 GeV) (with mH=130 GeV) ~ 10 K evt.~ 10 K evt.• ATHENA 6.0.3 (Moore-00-00-42)ATHENA 6.0.3 (Moore-00-00-42)

•DC1 sample (prod. in July 2002):DC1 sample (prod. in July 2002): HH44 (with mH=130 GeV) (with mH=130 GeV) ~ 10 K evt.~ 10 K evt.• ATHENA 6.0.3 (Moore-00-00-42)ATHENA 6.0.3 (Moore-00-00-42)

= (3.15±0.09) GeV

Phy TDR = 2.7 GeV

= (2.33±0.07) GeV

Phy TDR = 2.1 GeV

= (1.49±0.05) GeV

With Z constraintWith Z constraintWith Z constraintWith Z constraint

= (1.85±0.06) GeV

Without Z constraintWithout Z constraintWithout Z constraintWithout Z constraint

Phy TDR = 1.6 GeV Phy TDR = (1.42 ±0.06) GeV

Combined Reconstruction (Moore + MUID + iPat)Combined Reconstruction (Moore + MUID + iPat)

HH44(II)(II)Evelin MeoniEvelin Meoni

Z0→ Z0→ DC1 Data DC1 Data Moore/MUID in 6.0.2Moore/MUID in 6.0.2 Total Number of Events: Total Number of Events:

~10000~10000

Phy TDR:Standalone Muon Spectrometer : = 3.0 GeVCombined MS + ID : = 2.5 GeV

Test Beam Reconstruction (I)Test Beam Reconstruction (I) MuonTestBeam: ATHENA package designed to read and decode

DAQ data from the Muon Test Beam in H8 and prepare the reconstruction with Moore algorithms

Status (in ATHENA release 6.2.0): Converter to access to the H8-DAQ data in bytestream format

construct digits in the TDS using the new Muon Event Data Model H8 detector description through the ATHENA MuonDetDescrMgr

initialised from H8 Amdb Segments and tracks reconstructed via Moore algorithms Ntuples for the analysis Access to digits from H8 Geant4 simulation also implemented

First tests performed on data collected during 2002 (only MDT) Also RPC and TGC at this year’s test beam

Test Beam Reconstruction (II)Test Beam Reconstruction (II)DAQ DAQ filefile Test Beam ConverterTest Beam Converter

MuonDigitContainerMuonDigitContainer Moore Algs.Moore Algs. NtupleNtuple

Conditions DB Conditions DB serviceserviceTDC TDC

countscountsTracks Tracks angleangle

First test on First test on 2002 data 2002 data

• Straight line fit of track segments and full tracks implemented Straight line fit of track segments and full tracks implemented • Integration withIntegration with MDT calibration, chambers alignmentMDT calibration, chambers alignment

• The access to conditions DB through the Athena Interval Of Validity The access to conditions DB through the Athena Interval Of Validity Service is under developmentService is under development

In the Athena In the Athena frameworkframework

Moore and MUID in HLTMoore and MUID in HLTAt the hearth of the philosopy of the

Pesa design is the concept of

seeding.

Algorithms functioning in the context

of the High Level Trigger do not

operate in a general-purpose sense;

rather they must validate or reject

Trigger Element hypotheses formed

at a previous stage in the triggering

process.

Reminder geometry

Strategy for the Seeding

Strategy for the Seeding

RecoMuonRoI

( ±±)RegionSelector Hash offline IDs

DigitsContainerseeded

(RPCs and MDTs)

RPCDigitContainerMDTDigitContainer

TDS(ZEBRA)

MooMakePhiSegmentSeededMooMakeRZSegmentSeeded

PhiSegmentContainerRZSegmentContainer

MooMakeRoadsMooMakeTracksMuId standalone

Reconstructed Tracks

The HLT RegionSelector translates geometrical regions within the fiducial volume of the detector into a set of corresponding elements of appropriate granularity in each sub-detector

The RecoMuonRoI gives

eta & phi position of RoI.

From the event store (ZEBRA) it is possible to access the full event and to build the RPC and MDT digitcontainers.

Using boths it is possible to build the seeded DigitsContainers

And to follow the reconstruction chain

Moore/MuId – First time-performance testMoore/MuId – First time-performance test

20GeV TDR 20GeV DC1 300GeV TDR

200GeV DC1

H 4 DC1

142 msec 155 msec 368 msec 279 msec 572 msec(t -1)(t -1)

• t-1 t-1 Average execution time per event calculated for the 500 events sample. Average execution time per event calculated for the 500 events sample.The 1The 1stst event has not been included in the calculation since in this event several event has not been included in the calculation since in this event several services are initialized (magnetic field map,… ). services are initialized (magnetic field map,… ).

PTPT

Pt (GeV) Time (ms)

20 5.1

100 6.3

300 4.9

H->4mu

mH= 130 GeV

25.2

ConclusionsConclusionsConclusionsConclusions

A lot of improvements have been made to MOORE/MUIDA lot of improvements have been made to MOORE/MUID

in the last two months: in the last two months: it can now be used for Physics Studies

The code has proved to be robust on high statistics DC1 samplesThe code has proved to be robust on high statistics DC1 samples (~10(~1066 events processed – No Crash) events processed – No Crash)

A big (and successful!!) effort has been done for having A big (and successful!!) effort has been done for having MOORE/MUID as Event Filter in the HLT framework: results will MOORE/MUID as Event Filter in the HLT framework: results will appear in the HLT TDRappear in the HLT TDR

Alternative tracking methods to be inserted in MOORE (e.g. KalmanAlternative tracking methods to be inserted in MOORE (e.g. Kalman Filter) are under developmentsFilter) are under developments We are aiming at keep going with the developments but alwaysWe are aiming at keep going with the developments but always

having a having a referencereference versionversion to be used for Physics Studies to be used for Physics Studies