OO Muon Reconstruction in ATLAS Atlas offline software

OO Muon Reconstruction in ATLAS • Atlas offline software • Muon. Spectrometer reconstruction (Moore) • Atlas combined reconstruction (Muon. Identification) Michela Biglietti Univ. of Naples INFN/Naples 1

Offline software in Atlas 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 … Converter Application Manager Message Service Job. Options Service Particle Prop. Service Other Services Athena Event Data Service Persistency Service Data Files Transient Event Store Algorithm Detec. Data Service Transient Detector Store Persistency Service Data Files Histogram Service Transient Histogram Store Persistency Service Data Files 2

Offline Reconstruction in Atlas Algorithm Alg 1 Event Algorithm Alg 2 Algorithm Alg 3 Raw digits Atlas MC & simulation Event Detector Descriptio n Calorimetry Muon Tracks Em cluster Calo Jets Muon D Event S Event Data flow … Tracking T E/g identification Combined Muon … Event, Identified particles 3 Analysis

Moore in Athena Before: Moore RPC/TGC/MDT digits Moo. Algs Tracks RPC/TGC digits Moo. Make. Phi. Segments Moo. LVL 2 Phi. Segment. Maker n Phi. Segments Moo. Make. RZSegments Moo. LVL 2 RZSegment. Maker n MDT digits Moo. Make. Roads Crude. RZSegments Moo. Makei. Pat. Tracks Moo. Statistics Ntuples Moo. Roads n Each step is driven by an Athena topalgorithm Transient objects are passed via TDS/Store. Gate Independent algorithms, the only coupling is through the transient objects Mooi. Pat. Tracks Moo. Make. Ntuples Easier integration with other code ATHENA Results : less dependencies, is more packages to get services and for combined maintainable, modular, easier to develop reconstruction, test-beam software, 4 new reconstruction approaches calibration, online/EF sw …

Athena algorithms with different features/goals Moore Packages Moo. Algs_2 Moo. Algs. LVL 2 Moo. Algs Moo. Statistics Moo. Algs_n Moo. Code Shared code used by Athena Algos Moo. Events for reconstruction 5

Performance (%) Single muon studies Efficiency vs Pt A Muon track consists of hits from at least 2 stations and is successfully fitted. PT = 20 Ge. V PT (Ge. V) PT = 100 Ge. V = 3. 4 = 3. 3 Pt resolution 6

Speed MOORE: • Pentium III 850 MHz - 256 Mbytes Pt(Ge v) Time( ms) 20 90 100 300 570 1000 1500 MUONBOX 7

Combined Muon Reconstruction l Improve muons identification efficiency – Discrimination of muons from rays in the muon – – – l 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 – – – l spectrometer Reconstruction of low energy muons that do not reach the middle and outer stations of the muon spectrometer 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 Ge. V to 70 Ge. V) 8

Muon Identification Pre-existing work: Muon Identification (MUID) package used for physic TDR Ø Atrecon implementation: Ø Input – results of ID, Calo and Muon reconstruction (Muonbox) (as C++ objects through interface packages) Ø Output – class structure => zebra banks => combined ntuple l Purpose: associate tracks found in Muon Spectrometer with inner l 2 principle methods: detector (ID) tracks and calorimeter information to identify muons at their production vertex with optimum parameter resolution Stand-alone muons – Muon Spectrometer track and track-segment 1. parameters propagated to beam-axis • 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 h (i. e. thickness) or measure energy loss from calibration of observed energy deposition • MS track is express at vertex Combined muons – match Muon Spectrometer to ID tracks and fit combined parameters • 2. l l 2 cut for matching of inner detector and muon spectrometer tracks parameters combined fit 9

Muonidentification – Athena Implementation Muid. Init Moore Tracks Truth. Event Tracks Muid. Stand. Alone Muid. Tracks status muon Calo. Clusters Muid. Comb Muid. Tracks status standalone Muid. Ntuple ID Tracks Muid. IDNtuple Muid. Comb. Ntuple Muid. Tracks status combined Ntuples 10

Energy loss in the Calorimeters reconstructed (Ge. V) Pt = 20 Ge. V Pt = 100 Ge. V Pt = 300 Ge. V Total energy loss Tile Endcap hadronic LAr EM LAr from MC-Truth (Ge. V) 11

Stand. Alone Tracks : pulls @vertex cotq pulls Single Pt = 20 Ge. V F pulls 12

Pt corrections @vertex Pt = 20 Ge. V Pt @MS entrance (Moore) Pt @vertex Pt = 100 Ge. V Pt @MS entrance (Moore) Pt @vertex 13

Pt Resolutions & Combination Muon Track (Moore + Calo + Muid) In. Det (i. Pat. Rec) Combined (Muid) Pt = 100 Ge. V Pt = 20 Ge. V = 3. 6 = 2. 1 = 2. 0 Pt = 300 Ge. V = 2. 9 = 3. 9 = 5. 2 = 12. 5 = 2. 6 = 3. 8 14

Conclusions l Moore – What is needed l Description of inert material l EDM implemantation l Layout P – DC 1 data reconstruction – Items l Material, EDM, testbeam version, geometry/event description, repackaging/intergration, LVL 2 … l Muon. Identification – to do l Energy loss parametrisation l Fit-tracking optimization l Calorimeter multiple scattering tuning l Integration with the new version of Moore (material description and EDM) l Better design, full debug … 15