geant4 physics evaluation in atlas

Slide 1

Peter LochUniversity of Arizona

Tucson, Arizona 85721

GEANT4 Physics Evaluation in ATLASUS ATLAS Computing MeetingBNL August 28, 2003



Geant4 Physics Evaluation in ATLASGeant4 Physics Evaluation in ATLASGeant4 Physics Evaluation in ATLASGeant4 Physics Evaluation in ATLAS

With contributions from D. Barberis1, K. Kordas2, A. Kiryunin2, M. Leltchouk2, R. Mazini2, B. Osculati1, G. Parrour2, A. Rimoldi3, W. Seligman2, P. Strizenec2, V. Tsulaia4, M.J. Varanda4 et al.

1 – ATLAS Inner Detector/Pixels2 – ATLAS Liquid Argon Calorimeters3 – ATLAS Muon System4 – ATLAS Tile Calorimeter

Slide 2




GEANT4: brief history and introductionGEANT4: brief history and introduction

Strategies for GEANT4 physics validation in ATLASStrategies for GEANT4 physics validation in ATLAS

Muon energy loss and secondaries production in the Muon energy loss and secondaries production in the ATLAS calorimeters and muon detectorsATLAS calorimeters and muon detectors

Electromagnetic shower simulations in calorimetersElectromagnetic shower simulations in calorimeters

Hadronic interactions in tracking devices and Hadronic interactions in tracking devices and calorimeterscalorimeters

ConclusionsConclusions

GEANT4: brief history and introductionGEANT4: brief history and introduction

Strategies for GEANT4 physics validation in ATLASStrategies for GEANT4 physics validation in ATLAS

Muon energy loss and secondaries production in the Muon energy loss and secondaries production in the ATLAS calorimeters and muon detectorsATLAS calorimeters and muon detectors

Electromagnetic shower simulations in calorimetersElectromagnetic shower simulations in calorimeters

Hadronic interactions in tracking devices and Hadronic interactions in tracking devices and calorimeterscalorimeters

ConclusionsConclusions

This Talk:This Talk:

Slide 3




GEANT4: A Brief IntroductionGEANT4: A Brief Introduction

Some GEANT4 history: Some GEANT4 history: (see also http://wwwasd.web.cern.ch/wwwasd/geant4/geant4.html)

started as RD44 (1994-1998) at CERN with aim to provide a toolkit based on object-oriented software technology as a replacement for the GEANT3 framework;

since the first production version in 1999 the world-wide GEANT4 collaboration provides development, maintenance and user support;

GEANT4 in ATLAS: GEANT4 in ATLAS:

• ATLAS/GEANT4 Comparison Project initiated in 2000 to validate available physics models and establish lines of communication with GEANT4 developers;

• mostly “private” codes used by various (sub)detectors in GEANT4 physics evaluation phase (2000-now) -> avoid delays by software integration and design issues -> quick response highly appreciated by GEANT4 team!

• now software consolidation and integration phase, preparation for full physics simulation in Data Challenge 2 (spring 2004): GEANT4 -> ATHENA integration nearly complete for Liquid Argon calorimeters (Leltchouk, Seligman);

Slide 4




What are the GEANT4 Features?What are the GEANT4 Features?

Similarities to GEANT3:Similarities to GEANT3: provides all tools to describe complex detector geometries based on a

pre-defined list of volume shapes;

has pre-defined list with principal particle properties;

has default particle tracking and stepping functionality;

has default hit definition;

has similar physics models for various particle types for direct comparisons;

allows graphical presentations of detector geometries and shower development;

Differences to GEANT3: Differences to GEANT3:

• allows implementation of complex user-defined volume shapes (G4Accordion for the ATLAS Electromagnetic Barrel absorber folds, for example);

• no pre-defined materials or tracking medium properties, but straight forward client interfaces to implement those (also for mixtures);

Slide 5




More GEANT4 FeaturesMore GEANT4 Features

Other differences to GEANT3:Other differences to GEANT3: interaction physics (“physics lists”) completely user controlled, but

some important examples and support from experts are provided, especially for hadronic interactions – also attempt by GEANT4 to collect and publish user experience;

no overall tracking (kinetic) energy threshold;

explicit production of secondaries controlled by minimum range cut, rather than energy threshold;

no default I/O or persistency package;

very configurable: user can control interaction physics, tracking, stepping (mandatory in case of user defined volume shapes), graphical viewer (DAWN, VRML…);

toolkit, rather than framework, allows integration into other frameworks like ATHENA;

Slide 6




Strategies for G4 Physics Validation in ATLAS

Strategies for G4 Physics Validation in ATLAS GEANT4 physics benchmarking: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 in secondaries production…);

Validation: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;

GEANT4 physics benchmarking: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 in secondaries production…);

Validation: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;

Slide 7




G4 Validation Strategies: Some Requirements…

G4 Validation Strategies: Some Requirements… Geometry description: 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: 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…);

Geometry description: 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: 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;

example: forward calorimeter uses actual machining and cabling database in simulations to describe electrode dimensions, locations and readout channel mapping;

Slide 8




Geant4 Setups (1)Geant4 Setups (1) Muon Detector Testbeam Muon Detector Testbeam

Detector plasticCover (3mm thick) Silicon sensor (280 μm thick)

FE chip (150 μm thick)PCB (1 mm thick)

Hadronic Interaction in Silicon Pixel Detector Hadronic Interaction in Silicon Pixel Detector

Slide 9




Geant4 Setups (2)Geant4 Setups (2) Electromagnetic Barrel Accordion Calorimeter

Electromagnetic Barrel Accordion Calorimeter

10 GeV Electron Shower 10 GeV Electron Shower

Forward Calorimeter (FCal) Testbeam Setup

Forward Calorimeter (FCal) Testbeam Setup

FCal1 Module 0FCal1 Module 0

FCal2 Module 0FCal2 Module 0

ExcluderExcluder

Slide 10




Muon Energy Loss (Sept. 2002)

Muon Energy Loss (Sept. 2002)

Reconstructed Energy [GeV]

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

0

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

Reconstructed Energy [GeV]Δ

events

/0.1

GeV

[%

]Fra

ctio

n e

vents

/0.1

GeV

10-4

10-3

10-2

10-1

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Eμ= 100 GeV, ημ ≈ 0.975

Electromagnetic Barrel Calorimeter EMB (Liquid Argon/Lead Accordion)

Electromagnetic Barrel Calorimeter EMB (Liquid Argon/Lead Accordion)

-100 1000 200 300 400 5000

600

100

200

300

400

500

700

800

Calorimeter Signal [nA]

Events

/10

nA

180 GeV μ

180 GeV μ

Hadronic EndCap Calorimeter (HEC) (Liquid Argon/Copper Parallel Plate)

Hadronic EndCap Calorimeter (HEC) (Liquid Argon/Copper Parallel Plate)

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);

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);

Slide 11




Secondaries Production by Muons (Sept. 2002)Secondaries Production by Muons (Sept. 2002)

Muon Detector: Muon Detector: Muon Detector: 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);

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);

Slide 12




Geant4 Electron Response in ATLAS Calorimetry

(Sept. 2002)

Geant4 Electron Response in ATLAS Calorimetry

(Sept. 2002) Overall signal characteristics: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-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 resolution function ~5% in G4, ~ 4% in data and G3;

Overall signal characteristics: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-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 resolution function ~5% in G4, ~ 4% in data and G3;

0 1 2 4 53

0

-2

-4

-6

2

0

-2

-4

-6

2

ΔE

rec M

C-D

ata

[%

]

noiseNoise Cut Level σ

GEANT4

GEANT4

GEANT3

GEANT3

stochastic term

%× GeV

9.2 9.40.3 0.40.2 0.5 9 9.6

data data

GEANT3GEANT3

GEANT4GEANT4

high energy limit %

TileCal: stochastic term 22%GeV1/2 G4/G3, 26%GeV1/2 data; high energy limit very comparable;

TileCal: stochastic term 22%GeV1/2 G4/G3, 26%GeV1/2 data; high energy limit very comparable;

FCal Electron ResponseFCal Electron Response

EMB Electron Energy Resolution

EMB Electron Energy Resolution

Slide 13




Electron Shower Shapes & Composition (1)

(Sept. 2002)


(Sept. 2002) Shower shape analysis: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:

Shower shape analysis: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:

0 1 2 3-1-2-30

0.1

0.2

0.3

0.4

0.5

0.6

dE/E

per

RM

Distance from shower axis [RM = 2.11cm]0 2.5 5 7.5 10 12.5 15 17.5 200

0.02

0.04

0.06

0.08

0.1

0.12

Shower depth [X0 = 2.25cm]

dE/E

per

X0 TileCal 100 GeV ElectronsTileCal 100 GeV Electrons TileCal 100 GeV ElectronsTileCal 100 GeV Electrons

Slide 14





(Sept. 2002)


(Sept. 2002) Shower composition: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 simulations 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;

Shower composition: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 simulations 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;

10-1

10-4

10-3

10-2

10-5

10-6R

el. e

ntr

ies electronic

noiseelectronic

noise

shower signalsshower signals

0 50 100 150 200 250 300

noiseCell Signal Signifi cance Γ σ

FCal 60 GeV Electrons

excess in experimentexcess in

experiment

Slide 15




Hadronic Shower Models in GEANT4 Hadronic Shower Models in GEANT4

LHEP (similar to GHEISHA): LHEP (similar to GHEISHA): uses parametrized models from LEP and others for inelastic scattering,

no resonances;

detailed secondary angular distributions for O(100 MeV) reactions may not be described very well;

can often describe average quantities quite well (energy resolution, signal energy dependence…);

QGSP (GEANT4 only): QGSP (GEANT4 only): features theory-driven modeling of high energetic pion, kaon and

nucleon reactions – uses currently best known pion cross-sections;

quark-gluon string model for “punch-through” interactions of projectile with nucleus, string excitation from quasi-eikonal approximation;

pre-equilibrium decay model with evaporation phase for behaviour of nucleus after reaction (slow hadronic shower component);

LHEP (similar to GHEISHA): LHEP (similar to GHEISHA): uses parametrized models from LEP and others for inelastic scattering,

no resonances;

detailed secondary angular distributions for O(100 MeV) reactions may not be described very well;

can often describe average quantities quite well (energy resolution, signal energy dependence…);

QGSP (GEANT4 only): QGSP (GEANT4 only): features theory-driven modeling of high energetic pion, kaon and

nucleon reactions – uses currently best known pion cross-sections;

quark-gluon string model for “punch-through” interactions of projectile with nucleus, string excitation from quasi-eikonal approximation;

pre-equilibrium decay model with evaporation phase for behaviour of nucleus after reaction (slow hadronic shower component);

(see also http://cmsdoc.cern.ch/~hpw/GHAD/HomePage/calorimetry/index.html

Slide 16




Hadronic Shower Models in GEANT4 Hadronic Shower Models in GEANT4

QGSC (GEANT4 only): QGSC (GEANT4 only): like QGSP for initial reaction, but fragmentation by chiral invariant

phase-space decay (multi-quasmon fragmentation);

FTFP (GEANT4 only): FTFP (GEANT4 only): similar to QGSP in the treatment of the fragmentation, but diffractive

string excitation similar to FRITJOF, instead of quark-gluon strings;

QGSP, QGSC, and FTFP are very similar for all practical purposes, especially for the simulation of hadronic showers in calorimeters. LHEP shows larger differences to these packages. Results shown

here concentrate on LHEP/QGSP comparisons with testbeam data and GEANT3.

Also, single interaction comparisons as shown here for GEANT4 hadronic shower models are not easy with GEANT3 hadronic

shower models like GCALOR or GHEISHA, due to quantum number and energy/momentum non-conservation at this level in

these models…

Slide 17




Individual Hadronic Interactions(Sept. 2002)

Individual Hadronic Interactions(Sept. 2002)

Inelastic interaction properties: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;

two models in GEANT4 studied: the parametric “GHEISHA”-type model (LHEP) and the quark-gluon string model (QGSP, H.P. Wellisch);

Special interaction trigger

~3000 sensitive pixels

Slide 18




Individual Hadronic Interactions: Energy Release

(Sept. 2002)

Individual Hadronic Interactions: Energy Release

(Sept. 2002) Interaction cluster:Interaction cluster:

differences in shape and average (~5%-~7% too small for LHEP/QGSP) 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 LHEP (shape, average ~26% too small);

QGSP does better job on average (identical to data) for this variable, but still shape not completely reproduced yet (energy sharing between pixels in cluster);

LHEP QGSP Experiment


log(energy equivalent # of electrons)

Slide 19




More on Individual Hadronic Interactions(Sept. 2002)

More on Individual Hadronic Interactions(Sept. 2002)

Spread of energy: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 (mostly problems with shapes of distributions);

Charged track multiplicity:Charged track multiplicity:

average charged track multiplicity in in-elastic hadronic interaction described wellwith both models (within 2-3%), with aslight preference for LHEP;


Slide 20




Geant4 Hadronic Signals in ATLAS Calorimeters

(July 2003)

Geant4 Hadronic Signals in ATLAS Calorimeters

(July 2003) Calorimeter pion Calorimeter pion response:response:

e/π signal ratio for non-compensating calorimeter like the ATLAS Liquid Argon Hadronic Endcap Calorimeter (HEC) is important characteristic to be reproduced by shower models -> required for use of simulation to determine calibration functions;

e/π signal ration in HEC (and hadronic TileCal) not well reproduced by GEANT4 LHEP – but already somewhat better than GCALOR in GEANT3.21;

GEANT4 QGSP, QGSC and FTFP do a much better job for this important variable;

e/π

e/π

e/π

e/π

Beam Energy [GeV]

Beam Energy [GeV]

LHEP QGSP

QGSC FTFP

Slide 21




Geant4 Hadronic Signal CharacteristicsGeant4 Hadronic Signal Characteristics Pion energy resolution:Pion energy resolution:

good description of experimental pion energy resolution by QGSP in TileCal; LHEP cannot describe stochastic term, but fits correct high energy limit;L

GEANT3/GCALOR predicts significantly less signal fluctuations than measured in testbeam for pions in HEC and TileCal;

GEANT4 QGSP reproduces shower- and sampling fluctuations and constant term for pions in HEC within the errors; QGSC and FTFP close, but LHEP significantly off (July 2003);

TileCal Pion Energy Resolution

(Sept. 2002)

Pion longitudinal shower profiles:Pion longitudinal shower profiles:

rather poor description of experimental energy sharing between longitudinal segments in HEC by all GEANT4 quark-string models; pion showers generally start too early; LHEP delivers an acceptable description of the longitudinal profiles, at about the same level as GCalor in Geant3.21 (July 2003);

Slide 22




Conclusions (1):Conclusions (1): GEANT4 can simulate relevant features of muon, electron and GEANT4 can simulate relevant features of muon, electron and

pion signals in various ATLAS detectors, now generally better pion signals in various ATLAS detectors, now generally better than GEANT3;than GEANT3;

remaining discrepancies are addressed and reported to the remaining discrepancies are addressed and reported to the GEANT4 team; communication with experts is well established, GEANT4 team; communication with experts is well established, and most problems are addressed quickly;and most problems are addressed quickly;

ATLAS has a significant amount of appropriate testbeam data ATLAS has a significant amount of appropriate testbeam data for the calorimeters, inner detector modules, and the muon for the calorimeters, inner detector modules, and the muon detectors to evaluate the GEANT4 physics models in detail – detectors to evaluate the GEANT4 physics models in detail – excellent use of the testbeam data!excellent use of the testbeam data!

sometimes not easy to follow up with GEANT4 progress for sometimes not easy to follow up with GEANT4 progress for ATLAS sub-detector systems, due to lack of manpower -> hard to ATLAS sub-detector systems, due to lack of manpower -> hard to follow and monitor GEANT4 evolution -> more automated follow and monitor GEANT4 evolution -> more automated benchmark tests needed;benchmark tests needed;

GEANT4 can simulate relevant features of muon, electron and GEANT4 can simulate relevant features of muon, electron and pion signals in various ATLAS detectors, now generally better pion signals in various ATLAS detectors, now generally better than GEANT3;than GEANT3;

remaining discrepancies are addressed and reported to the remaining discrepancies are addressed and reported to the GEANT4 team; communication with experts is well established, GEANT4 team; communication with experts is well established, and most problems are addressed quickly;and most problems are addressed quickly;

ATLAS has a significant amount of appropriate testbeam data ATLAS has a significant amount of appropriate testbeam data for the calorimeters, inner detector modules, and the muon for the calorimeters, inner detector modules, and the muon detectors to evaluate the GEANT4 physics models in detail – detectors to evaluate the GEANT4 physics models in detail – excellent use of the testbeam data!excellent use of the testbeam data!

sometimes not easy to follow up with GEANT4 progress for sometimes not easy to follow up with GEANT4 progress for ATLAS sub-detector systems, due to lack of manpower -> hard to ATLAS sub-detector systems, due to lack of manpower -> hard to follow and monitor GEANT4 evolution -> more automated follow and monitor GEANT4 evolution -> more automated benchmark tests needed;benchmark tests needed;

Slide 23




• Geant4 is definitively a mature and useful product for large Geant4 is definitively a mature and useful product for large scale detector response simulations, therefore: start using it for all scale detector response simulations, therefore: start using it for all simulations, specifically testbeams and physics – it is the only open simulations, specifically testbeams and physics – it is the only open source toolkit backed by a large number of interaction model source toolkit backed by a large number of interaction model teams and experts from all over the world -> guarantees future teams and experts from all over the world -> guarantees future support and improvements!!support and improvements!!

• still work needed to fully integrate GEANT4 into ATHENA to be still work needed to fully integrate GEANT4 into ATHENA to be ready for DC2 in spring 2004 – contact your sub-detector ready for DC2 in spring 2004 – contact your sub-detector simulation software coordinator for actual status of simulation software coordinator for actual status of implementation…;implementation…;

• … …and again, start using it in the ATHENA framework! and again, start using it in the ATHENA framework!

• Geant4 is definitively a mature and useful product for large Geant4 is definitively a mature and useful product for large scale detector response simulations, therefore: start using it for all scale detector response simulations, therefore: start using it for all simulations, specifically testbeams and physics – it is the only open simulations, specifically testbeams and physics – it is the only open source toolkit backed by a large number of interaction model source toolkit backed by a large number of interaction model teams and experts from all over the world -> guarantees future teams and experts from all over the world -> guarantees future support and improvements!!support and improvements!!

• still work needed to fully integrate GEANT4 into ATHENA to be still work needed to fully integrate GEANT4 into ATHENA to be ready for DC2 in spring 2004 – contact your sub-detector ready for DC2 in spring 2004 – contact your sub-detector simulation software coordinator for actual status of simulation software coordinator for actual status of implementation…;implementation…;

• … …and again, start using it in the ATHENA framework! and again, start using it in the ATHENA framework!

Conclusions (2):Conclusions (2):

geant4 physics evaluation in atlas

Documents