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Status of the Geant4 Physics Evaluation in ATLAS. Peter Loch University of Arizona. With contributions from D. Barberis 1 , K. Kordas 2 , A. Kiryunin 2 , R. Mazini 2 , B. Osculati 1 , G. Parrour 2 , A. Rimoldi 3 , P. Strizenec 2 , V. Tsulaia 4 , M.J. Varanda 4 et al.
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Peter Loch University of Arizona Tucson, Arizona 85721 Status of the Geant4 Physics Evaluation in ATLAS Peter Loch University of Arizona With contributions from D. Barberis1, K. Kordas2, A. Kiryunin2, R. Mazini2, B. Osculati1, G. Parrour2, A. Rimoldi3, P. Strizenec2, V. Tsulaia4, M.J. Varanda4et al. 1 – ATLAS Inner Detector/Pixels 2 – ATLAS Liquid Argon Calorimeters 3 – ATLAS Muon System 4 – ATLAS Tile Calorimeter
Solenoid EndCap Toroid Shielding Peter Loch University of Arizona Tucson, Arizona 85721 • ATLAS: • A Multi-Pur- • pose LHC • Detector EMB (LAr/Pb,Barrel) & EMEC (LAr/Pb,EndCap) Muon Detectors (μ) Electromagnetic Calorimeters (μ,e) Forward Calorimeters (e) FCal (LAr/Cu/W) Barrel Toroid Inner Detector (e,μ,π) Hadronic Calorimeters (e,μ,π) HEC (LAr/Cu,EndCap) & TileCal (Scint/Fe,Barrel/Extended)
Peter Loch University of Arizona Tucson, Arizona 85721 This Talk: • Strategies for G4 physics validation in ATLAS • Muon energy loss and secondaries production in the ATLAS calorimeters and muon detectors • Electromagnetic shower simulations in calorimeters • Hadronic interactions in tracking devices and calorimeters • Conclusions
Peter Loch University of Arizona Tucson, Arizona 85721 Strategies for G4 Physics Validation in ATLAS • Geant4 physics benchmarking: • compare features of interaction models with similar features in the old Geant3.21 baseline (includes variables not accessible in the experiment); • try to understand differences in applied models, like the effect of cuts on simulation parameters in the different variable space (range cut vs energy threshold…); • Validation: • use available experimental reference data from testbeams for various sub-detectors and particle types to determine prediction power of models in Geant4 (and Geant3); • use different sensitivities of sub-detectors (energy loss, track multiplici-ties, shower shapes…) to estimate Geant4 performance; • tune Geant4 models (“physics lists”) and parameters (range cut) for optimal representation of the experimental detector signal with ALL relevant aspects;
Geometry description: • has to be as close as possible to the testbeam setup (active detectors and relevant parts of the environment, like inactive materials in beams); • identical in Geant3 and Geant4; • often common (simple) database used (muon detectors, calorimeters) to describe (testbeam) detectors in Geant3 and Geant4: • Environment in the experiment: • particles in simulations are generated following beam profiles (muon detectors, calorimeters) and momentum spectra in testbeam (muon system); • features of electronic readout which can not be unfolded from experimental signal are modeled to best knowledge in simulation (incoherent and coherent electronic noise, digitization effect on signal…); example: forward calorimeter uses actual machining and cabling database in simulations to describe electrode dimensions, locations and readout channel mapping; Peter Loch University of Arizona Tucson, Arizona 85721 G4 Validation Strategies: Some Requirements…
Muon Detector Testbeam Detector plastic Cover (3mm thick) Silicon sensor (280 μm thick) FE chip (150 μm thick) PCB (1 mm thick) • Hadronic Interaction in Silicon Pixel Detector Peter Loch University of Arizona Tucson, Arizona 85721 Geant4 Setups (1)
Electromagnetic Barrel Accordion Calorimeter • 10 GeV Electron Shower Peter Loch University of Arizona Tucson, Arizona 85721 Geant4 Setups (2) • Forward Calorimeter • (FCal) Testbeam • Setup Excluder FCal1 Module 0 FCal2 Module 0
Hadronic EndCap Calorimeter (HEC) • (Liquid Argon/Copper Parallel Plate) 10-1 10-2 180 GeV μ Events/10 nA Fraction events/0.1 GeV 10-3 Eμ= 100 GeV, ημ ≈ 0.975 10-4 800 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 700 Reconstructed Energy [GeV] Calorimeter Signal [nA] 600 0 500 -0.5 • G4 simulations (+ electronic noise) describe testbeam signals well, also in Tile Calorimeter (iron/scintillator technology, TileCal); • some range cut dependence of G4 signal due to contribution from electromagnetic halo (δ-electrons); -1.0 400 -1.5 300 Δ events/0.1 GeV [%] -2.0 200 -2.5 100 -3.0 0 -3.5 400 -100 0 100 200 300 500 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 Reconstructed Energy [GeV] Peter Loch University of Arizona Tucson, Arizona 85721 Muon Energy Loss • Electromagnetic Barrel Calorimeter • EMB (Liquid Argon/Lead Accordion)
Peter Loch University of Arizona Tucson, Arizona 85721 Secondaries Production by Muons • Muon Detector: • extra hits produced in dedicated testbeam setup with Al and Fe targets (10, 20 and 30 cm deep), about ~37 cm from first chamber; • probability for extra hits measured in data at various muon energies (20-300 GeV); • Geant4 can reproduce the distance of the extra hit to the muon track quite well; • extra hit probability can be reproduced between 3 – 10% for Fe, some larger discrepancies (35%) remain for Al (preliminary analysis); • subject is still under study (more news expected in mid-October);
2 0 -2 -4 -6 2 0 -2 -4 GEANT4 GEANT4 -6 GEANT3 GEANT3 data data 0 1 2 3 4 5 GEANT4 GEANT4 GEANT3 GEANT3 0.2 0.3 0.4 0.5 9 9.2 9.4 9.6 Peter Loch University of Arizona Tucson, Arizona 85721 Geant4 Electron Response in ATLAS Calorimetry • Overall signal characteristics: • Geant4 reproduces the average electron signal as func- • tion of the incident energy in all ATLAS calorimeters • very well (testbeam setup or analysis induced non-line- • arities typically within ±1%)… • …but average signal • can be smaller than in G3 • and data (1-3% for 20- • 700 μm range cut in HEC); • signal fluctuations in EMB • very well simulated; • electromagnetic FCal: • high energy limit of reso- • lution function ~5% in G4, • ~ 4% in data and G3; FCal Electron Response EMB Electron Energy Resolution ΔErec MC-Data [%] • TileCal: stochastic term • 22%GeV1/2 G4/G3, 26%GeV1/2 • data; high energy limit very • comparable;
4.3 1.6 Geant3 4.2 Geant3 Evis [GeV] Sampling Frac. [%] 1.5 4.1 61 60 2.1 Edep [GeV] 59 σ/E [%] 2 7 1.9 6 σ/E [%] 10-2 10-1 1 10 5 GEANT4 range cut [mm] GEANT4 range cut [mm] 10-3 10-2 10-1 Peter Loch University of Arizona Tucson, Arizona 85721 Geant4 Electron Signal Range Cut Dependence • maximum signal in HEC and FCal found at 20 μm – unexpected signal drop for lower range cuts; • HEC and FCal have very different readout geometries (parallel plate, tubular gap) and sampling characteristics, but identical absorber (Cu) and active (LAr) materials; • effect under discussion with Geant4 team (M. Maire et al.), but no solution yet (??); FCal 60 GeV Electrons HEC 100 GeV Electrons 20 μm 20 μm
TileCal 100 GeV Electrons TileCal 100 GeV Electrons 0.12 0.6 dE/E per X0 dE/E per RM 0.1 0.5 0.08 0.4 0.06 0.3 0.04 0.2 0.02 0.1 0 0 -3 -2 -1 0 1 2 3 0 2.5 5 7.5 10 12.5 15 17.5 20 Shower depth [X0 = 2.25cm] Distance from shower axis [RM = 2.11cm] Peter Loch University of Arizona Tucson, Arizona 85721 Electron Shower Shapes & Composition (1) • Shower shape analysis: • Geant4 electromagnetic showers in the EMB are more compact longitudinally than in G3: about 3-13% less signal in the first 4.3X0, but 1.5-2.5% more signal in the following 16X0, and 5-15% less signal (large fluctuations) in the final 2X0 for 20-245 GeV electrons; • Geant4 electron shower in TileCal starts earlier and is slightly narrower than in G3:
10-1 10-2 10-3 10-4 10-5 10-6 0 50 100 150 200 250 300 Peter Loch University of Arizona Tucson, Arizona 85721 Electron Shower Shapes & Composition (2) • Shower composition: • cell signal significance spectrum is • the distribution of the signal-to-noise • ratio in all individual channels for all • electrons of a given impact energy; • to measure this spectrum for simu- • lations requires modeling of noise in • each channel in all simulated events • (here: overlay experimental “empty” • noise events on top of Geant4 events) • spectrum shows higher end point for data than for Geant4 and Geant3, indicating that • larger (more significant) cell signals occur more often in the experiment -> denser • showers on average; FCal 60 GeV Electrons electronic noise excess in experiment shower signals Rel. entries
Peter Loch University of Arizona Tucson, Arizona 85721 Individual Hadronic Interactions • Inelastic interaction properties: • energy from nuclear break-up in the course of a hadronic inelastic interactions causes large signals in the silicon pixel detector in ATLAS, if a pixel (small, 50 μm x 400 μm), is directly hit; • this gives access to tests of • single hadronic interaction • modeling, especially concerning • the nuclear part; • testbeam setup of pixel • detectors supports the study • of these interactions; • presently two models in Geant4 studied: the parametric “GHEISHA”-type model (PM) and the quark-gluon string model (QGS, H.P. Wellisch); Special interaction trigger ~3000 sensitive pixels
Peter Loch University of Arizona Tucson, Arizona 85721 Individual Hadronic Interactions: Energy Release • Interaction cluster: • differences in shape and average (~5% too small for PM, ~7% too small for QGS) of released energy distribution for 180 GeV pions in interaction clusters; • fraction of maximum single pixel release and total cluster energy release not very well reproduced by PM (shape, average ~26% too small); • QGS does better job on average (identical to data) for this variable, but still shape not completely reproduced yet (energy sharing between pixels in cluster); PM QGS Experiment log(energy equivalent # of electrons) PM QGS Experiment
Peter Loch University of Arizona Tucson, Arizona 85721 More on Individual Hadronic Interactions • Spread of energy: • other variables tested with pixel detector: cluster width, longest distance between hit pixel and cluster barycenter -> no clear preference for one of the chosen models at this time (most problems with shapes of distributions); • Charged track multiplicity: • average charged track multiplicity in in- • elastic hadronic interaction described well • with both models (within 2-3%), with a • slight preference for PM; PM QGS Experiment
Peter Loch University of Arizona Tucson, Arizona 85721 Geant4 Hadronic Signals in ATLAS Calorimeters • Calorimeter pion response: • after discovery of “mix-and-match” problem (transition from low energy to high energy char-ged pion models) in the deposited energy from energy loss of charged particles in pion showers in the HEC (G4 4.0, early 2002): fixes suggested by H.P. Wellisch (LHEP, new energy thresholds in model transition + code changes) and QGS model tested; • e/π signal ration in HEC and TileCal still not well reproduced by Geant4 QGS or LHEP - but better than with GCalor in Geant3.21; • energy dependence in HEC in QGS smoother, “discontinuities” between ~20 GeV and ~80 GeV gone; HEC Pions QGS e/π signal ratio LHEP e/π signal ratio Pion energy [GeV]
Peter Loch University of Arizona Tucson, Arizona 85721 Geant4 Hadronic Signal Characteristics (1) • Pion energy resolution: • good description of experimental pion energy resolution by QGS in TileCal; LHEP cannot describe stochastic term, but fits correct high energy limit; • larger discrepancies in HEC: stochastic term significantly too large for QGS and LHEP, but reasonable description of high energy behaviour by QGS; TileCal Pion Energy Resolution HEC Pion Energy Resolution Exp QGS GCalor relative energy resolution [%] Pion energy [GeV]
Peter Loch University of Arizona Tucson, Arizona 85721 Geant4 Hadronic Signal Characteristics (2) • Pion longitudinal shower profiles: • measured by energy sharing in four depth segments of HEC; both Geant4 models (LHEP and QGS) studied; • rather poor description of experimental energy sharing by QGS; pion showers start too early; • LHEP describes longitudinal energy sharing in the experiment quite well for pions in the the studied energy range 20-200 GeV (at the same level as GCalor in Geant3.21);
Peter Loch University of Arizona Tucson, Arizona 85721 Conclusions (1): • Geant4 can simulate relevant features of muon, electron and pion signals in various ATLAS detectors, often better than Geant3; • remaining discrepancies, especially for hadrons, are addressed and progress can be expected in the near future; • ATLAS has a huge amount of appropriate testbeam data for the calorimeters, inner detector modules, and the muon detectors to evaluate the Geant4 physics models in detail; • feedback loops to Geant4 team are for most systems established since quite some time; communication is not a problem;
Peter Loch University of Arizona Tucson, Arizona 85721 Conclusions (2): • lack of man power in all ATLAS systems makes it hard to follow up on Geant4 progress; hard to catch up with G4 evolution! Need to look into more automated benchmark tests ?? • Geant4 is definitively a mature and useful product for large scale detector response simulations!