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Status of the Geant4 Physics Evaluation in ATLAS. Andrea Dell’Acqua CERN EP/SFT [email protected] On behalf of the ATLAS Geant4 Validation Team. Solenoid. EndCap Toroid. Shielding. ATLAS: A Multi-Pur- pose LHC Detector. EMB (LAr/Pb,Barrel) & EMEC (LAr/Pb,EndCap).

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status of the geant4 physics evaluation in atlas
Status of the Geant4 Physics Evaluation in ATLAS

Andrea Dell’Acqua

CERN EP/SFT

[email protected]

On behalf of the ATLAS Geant4 Validation Team

slide2

Solenoid

EndCap Toroid

Shielding

  • 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)

slide3

This Talk:

  • Strategies for G4 physics validation in ATLAS
  • Muon energy loss and secondaries production in the ATLAS calorimeters and muon detectors
  • Electromagnetic processes in tracking detectors and shower simulations in calorimeters
  • Hadronic interactions in tracking devices and calorimeters
  • Conclusions
slide4

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 references 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 respects;
slide5

G4 Validation Strategies: Some Requirements…

  • 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…);
  • Work as much as possible in a common simulation framework
slide6

Muon Detector Testbeam

Detector plastic

Cover (3mm thick)

Silicon sensor (280 μm thick)

FE chip (150 μm thick)

PCB (1 mm thick)

Geant4 Setups (1)

Hadronic Interaction in Silicon Pixel Detector

slide7

Geant4 Setups (2)

Electromagnetic Barrel Accordion Calorimeter

Forward Calorimeter

(FCal) Testbeam

Setup

Excluder

FCal1 Module 0

10 GeV Electron Shower

FCal2 Module 0

slide8

10-1

10-2

Fraction events/0.1 GeV

10-3

Eμ= 100 GeV, ημ ≈ 0.975

10-4

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Reconstructed Energy [GeV]

0

-0.5

-1.0

-1.5

Δ events/0.1 GeV [%]

-2.0

-2.5

-3.0

-3.5

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Reconstructed Energy [GeV]

Muon Energy Loss

Electromagnetic Barrel Calorimeter

EMB (Liquid Argon/Lead Accordion)

Hadronic EndCap Calorimeter (HEC)

(Liquid Argon/Copper Parallel Plate)

800

700

600

180 GeV μ

500

Events/10 nA

400

300

200

100

0

400

-100

0

100

200

300

500

Calorimeter Signal [nA]

  • 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);
slide9

agreement at the level of <1%

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 or between the chambers;
  • 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;
silicon detectors ionisation and pai model
Silicon Detectors – ionisation and PAI model
  • Standard ionisation model compared to PAI model for 100 GeV pions crossing a Pixel detector module (280 mm thick silicon):
  • distribution around peak identical
  • PAI model does not link properly to d-ray production
  • more important is the correct spatial distribution of ionisation energy loss: range cut should match detector resolution (<10 mm for Pixels)
transition radiation tracker

300 GeV muons

20 GeV pions

Transition Radiation Tracker
  • Very good agreement with data (and G3) for pions and muons
  • Several models tried for describing transition radiation with moderate success

Currently “on-hold” in favour of a home-grown TR model as the G4 one turns out to be too demanding in terms of geometry and tracking

20 GeV electrons

Deposited energy (keV)

slide12

GEANT4

GEANT4

GEANT3

GEANT3

data

data

0.2

0.3

0.4

0.5

9

9.2

9.4

9.6

Geant4 Electron Response in ATLAS Calorimetry

Overall signal characteristics:

Geant4 reproduces the average electron signal as

function of the incident energy in all ATLAS

calorimeters very well (testbeam setup or analysis

induced non-linearities 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;

TileCal Electron Energy Resolution

EMB Electron Energy Resolution

TileCal: stochastic term 41.%GeV1/2 G4, 38.6%GeV1/2 data; high energy limit very comparable;

slide13

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]

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:

slide14

Geant4 Hadronic Signals in ATLAS Calorimeters

Calorimeter pion response:

Rather difficult start, with inadequate models (“GHEISHA++”) and “mix-and-match” problems (transition from low energy to high energy charged pion models)

fixes suggested by H.P. Wellisch (LHEP, new energy thresholds in model transition + code changes) and new models (QGS) improved the situation dramatically

HEC Pions

Quantitative agreements between data and G4 for most of the observables, with QGS models which seem to provide the better answer

finally going in the right direction!

Still a few problems and open questions, that will require further investigation (in particular shower shape and pion energy deposition)

TileCal

Pion non-linearity

slide15

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;
  • All recent simulations show definite improvements as far as QGSP is concerned (and wrt Geant3)

TileCal Pion Energy Resolution

HEC Pion Energy Resolution

stoch. const

Data 68.895.82

QGSP 70.266.00

G3 64.444.70

slide16

Geant4 Hadronic Signal Characteristics (2)

Pion longitudinal shower profiles:

measured by energy sharing in four depth segments of HEC; all available Geant4 models studied;

rather poor description of experimental energy sharing by QGS; pion showers start too early; requires further investigation

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);

slide17

Conclusions:

  • Geant4 can simulate relevant features of muon, electron and pion signals in various ATLAS detectors, in most cases better than Geant3;
  • remaining discrepancies, especially for hadrons, are addressed and progress is continuous and measurable;
  • ATLAS can has a huge amount of the right 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;
  • Geant4 is definitely becoming a mature and useful product for larga scale detector response simulation!
slide18

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

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

slide19

10-1

10-2

10-3

10-4

10-5

10-6

0

50

100

150

200

250

300

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

slide20

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

slide21

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

slide22

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

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