1. Status of the Geant4 Physics Evaluation in ATLAS
Andrea Dell’Acqua
CERN EP/SFT
On behalf of the ATLAS Geant4 Validation Team

2. 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)
Solenoid
EndCap Toroid
Shielding
Barrel Toroid
Inner Detector (e,μ,π)
Hadronic Calorimeters (e,μ,π)
HEC (LAr/Cu,EndCap) &
TileCal (Scint/Fe,Barrel/Extended)

3. Strategies for G4 physics validation in ATLAS
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

4. 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;

5. 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

6. Geant4 Setups (1) 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

7. Geant4 Setups (2) Electromagnetic Barrel Accordion Calorimeter
Forward Calorimeter
(FCal) Testbeam
Setup
Excluder
FCal1 Module 0
10 GeV Electron Shower
FCal2 Module 0

8. Muon Energy Loss
Electromagnetic Barrel Calorimeter
EMB (Liquid Argon/Lead Accordion)
Hadronic EndCap Calorimeter (HEC)
(Liquid Argon/Copper Parallel Plate)
Reconstructed Energy [GeV]
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9 1
-3.5
-3.0
-2.5
-2.0
-1.5
-1.0
-0.5
Δ events/0.1 GeV [%]
Fraction events/0.1 GeV
10-4
10-3
10-2
10-1
Eμ= 100 GeV, ημ ≈ 0.975
800
700
600
180 GeV μ
500
Events/10 nA
400
300
200
100
-100
100
200
300
400
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);

9. 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 ( GeV);
Geant4 can reproduce the distance of the extra hit to the muon track quite well;
agreement at the level of <1%

10. 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)

11. 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 pions
300 GeV muons
20 GeV electrons
Deposited energy (keV)

12. 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
9.2
9.4
0.3
0.4
0.2
0.5 9
9.6
data
GEANT3
GEANT4
EMB Electron Energy Resolution
TileCal: stochastic term 41.%GeV1/2 G4, 38.6%GeV1/2 data; high energy limit very comparable;

13. 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 % more signal in the following 16X0, and 5-15% less signal (large fluctuations) in the final 2X0 for GeV electrons;
Geant4 electron shower in TileCal starts earlier and is slightly narrower than in G3: 1 2 3 -1 -2 -3
0.1
0.2
0.3
0.4
0.5
0.6
dE/E per RM
Distance from shower axis [RM = 2.11cm]
2.5 5
7.5 10
12.5 15
17.5 20
0.02
0.04
0.06
0.08
0.12
Shower depth [X0 = 2.25cm]
dE/E per X0
TileCal 100 GeV Electrons

14. 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

15. 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
QGSP G

16. 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 GeV (at the same level as GCalor in Geant3.21);

17. 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!

18. 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
10-3
10-2
10-1 5 6 7 59 60 61
1.5
1.6
GEANT4 range cut [mm]
Sampling Frac. [%]
Edep [GeV]
σ/E [%]
10-2
10-1 1 10
4.1
4.2
4.3
1.9 2
2.1
GEANT4 range cut [mm]
σ/E [%]
Evis [GeV]
Geant3
Geant3
20 μm
20 μm

19. 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
10-1
10-4
10-3
10-2
10-5
10-6
excess in experiment
shower signals
Rel. entries 50
100
150
200
250
300

20. 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

21. 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

22. 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