CHEP04 Interlaken, CH 26 September – 1 October 2004

1. adele.rimoldi@cern.ch adele rimoldi University of Pavia & INFN, Italy CHEP04 Interlaken, CH26 September – 1 October 2004 A.Rimoldi, J. Boudreau, D. Costanzo A. Dell’Acqua, M. Gallas, A. Nairz, V.Tsulaia The full detector simulation for the ATLAS experiment: status and outlook

2. outlook • Simulation data flow • The ATLAS Simulation Project • G4ATLAS the Geant4-based simulation for ATLAS • The ATLAS Simulation from the Data Challenge and Physics Validation perspective • The ATLAS Detector in GEANT4 and its Subdetectors • the Inner Detector Simulation • The ATLAS Calorimeters simulation • The Muon System Simulation • The ATLAS Testbeam • The Detector Digitization • The Simulation Validation Preproduction and DC2 • Memory usage @runtime • Timing for different event samples • The Data Challenges in ATLAS • The Physics with DC2 and CTB as a feedback for Simulation • Conclusions A.Rimoldi, University of Pavia & INFN, Italy

3. Generator HepMC Particle Filter McTruth(Gen) Simulation RawDataObjects ROD Emulation Algorithm ROD Input Digits Digitization Hits McTruth(Sim) ROD Emulation (passthru) MergedHits PileUp McTruth(PileUp) ByteStream ConversionSvc L1Result L1 Emulation (inc. L1 ROD) L1Digits L1 Digitization L2Result L2 Selection Algorithm ByteStream Uses RawDataObjects EFResult EF Selection Algorithm ATLAS ATLAS Simulation data flow A.Rimoldi, University of Pavia & INFN, Italy

4. The ATLAS Simulation Project • Present Status • GEANT3-based simulation was operational for the last 10 years, now discontinued (mid 2004) • It provided a simulation infrastructure used for Data Challenges(DC0,DC1), heavy ions, early testbeam and design optimization, experiment commissioning • GEANT4-based simulation developed in a full OO environment since 2000 • Very detailed and up-to-date in all the previous items, in most cases more accurate and performant • used for DC2 • the 2004 combined testbeam, the last before the first data-taking • Heavy ions production • Ready for early commissioning studies • A strategy for passage from GEANT3 to GEANT4 was successfully launched and followed in ATLAS end of last Year • ATL-SOFT-2003-013 . Strategy for the transition from Geant3 to Geant4 in ATLAS. by:Barberis, D.; Polesello, G.; Rimoldi, A ; Geneva : CERN, 13 Nov 2003 • Now the Geant4-based simulation is the main simulation engine in ATLAS A.Rimoldi, University of Pavia & INFN, Italy

5. G4ATLAS: the GEANT4-based simulation for ATLAS • Features • Completely written in C++ • Extensively usage of dynamical loading and action on demand • Completely embedded in the ATLAS ATHENA framework • Success story in terms of • open software • Multi programmers facility • Results: Performance and robustness optimal after a short ramp-up • Started as standalone exercise, then embedded in the ATLAS framework, now fully operational for experiment and testbeam purposes with the same software • POOL utilized for the I/O • Functionality • Most functionality is there. Interactivity is provided • Python scripting replacing the old macro-files structure • Developments • backward compatibility always provided • Not the end of the story: improvemnet foreseen in many fields (background treatment, visualization, more interactivity, documentation for end users, etc.) • Validation process • Multi-step process through Data Challenges -> see next slide • Readiness for the next Physics Workshop in 2005 with new features and upgrades A.Rimoldi, University of Pavia & INFN, Italy

6. The Atlas Simulation in GEANT4 from.. • theData Challenge viewpoint • DC0 (since end 2001 tests of event productions Geant3 & Geant4) • DC1(Phase I ->II) • Geant3 based • Validation samples (single particle, Et scans,Higgs) 740K ev • Single-particle production 30 million ev • Minimum-bias production 1.5 million ev • QCD di-jet production 5.2 million ev • Physics events requested by HLT groups 4.4 million ev • Pile-up • Data samples requests from end-user community • DC2 and following • GEANT4 based • large scale physics analysis, tests on computing model, test calibrations and alignment procedures • 12 millions fully simulated events • And a grand total of 1 job crash ! • Distributed production • 1M Z->ee events in 10K jobs and no failures (@NorduGrid) • the Physics Validation viewpoint • Used since 2001 mainly for testbeam simulations and simple setups • from 2004 for physics events analyses (Z->ee, mm, single particle ..) • Growing users community (the only way of shaking down bugs…) • Comparisons with real data in the testbeams, different layouts A.Rimoldi, University of Pavia & INFN, Italy

7. The ATLAS detector in Geant4 • Four main subdetectors • Inner detector - momentum measurement of charged particles, electron ID • high precision silicon trackers • straw tracker with TR capability • Calorimeters - measurement of particle energies • EM LAr calorimeters (barrel & endcap) • Hadron Lar calorimeters (endcap) • Scintillating Tile hadron calorimeter • Muon spectrometer - muon identification and measurement • High precision Drift Tubes for tracking, RPCs and TGCs for triggering • Magnet system - bending of charged particles for momentum measurements • 5.2M volumes objects(G3 27M) • 110K volume types (G3 23K) A.Rimoldi, University of Pavia & INFN, Italy

8. Pixel+SCT SCT Red: Initial Black: Final Pixel Eta The Inner Detector • Geometry • Three subdetectors components • Pixel • SCT • TRT • Final / initial layout available, preliminary validation on hits content done • Still to do • Allow global movements of the Pixel • Increase the level of details • Detector response • Tuned on test beam results • Home-grown TR model • Digitization • Adapt hit reading for pile-up • Introduce the concept of time in the digitization • Noise for TRT • Digitization packages used by the Combined Test Beam • Tuning with data to feed the Atlas Simulation A.Rimoldi, University of Pavia & INFN, Italy

9. The ATLAS Calorimeters Simulation • 4 subsystems • Electromagnetic barrel (EMB) • Hadronic end-cap (HEC) • Forward calorimeter (FCal) • Hadronic calorimeter (Tile) • Heavy tests/investigations for optimizing • the physics in Geant4 • the geometry for reducing memory consumption and cpu time • Parameterization studies ongoing • Main software infrastructure issues: • the detector description • no more hand-coded numbers, full GeoModel version available (library of geometrical primitives for describing detector geometries) • -> V.Tsulaia talk #279, tomorrow • the versioning of the database constants • LAr has already been switched to Oracle • the inclusion of calibration hits • do a careful accounting of where the energy goes in ATLAS A.Rimoldi, University of Pavia & INFN, Italy

10. The Muon System Simulation • System composed by • Four main subdetectors • 2 precision chambers tracking detectors • MDT, CSC • 2 trigger chambers detectors • RPC,TGC • Interleaved with the toroids structure • Feets and rails • The outermost detector of ATLAS • Services and cables passing through • Pileup & cavern background • Functionality for handling pileup in place • digitization time window for all technologies • Current DC2 production: no cavern background yet, only minimum-bias • Full background as in DC1 expected soon • CombinedTestBeam (Muon side) • Robustness of sim-digi chain demonstrated through tons of events produced • Comparisons with real data for all technologies • Now the fine-tuning stage A.Rimoldi, University of Pavia & INFN, Italy

11. The ATLAS Testbeam • The 2004 CTB case • All the components for a complete ATLAS sector are being tested together on a beam line in Summer 2004 (Combined TestBeam Setup) • @different beam energies • Magnetic field (2) • Ancillary detectors • Customized beam profile at generation • Deep comparisons with real data sample in each subdetector prototype • Fine tuning • Full chain Simulation-Digitization-Reconstruction done!. • In production mode. • Same software as for the full experiment A.Rimoldi, University of Pavia & INFN, Italy

12. The Detector Digitization • The digitization procedure is disentangled from the simulation process proper and it can be started from pregenerated hits or in a full chain • Fully functional and "leak free" since months • Each subdetector loaded on demand • Digitization of GEANT4 hits done • Hits I/O with Pool for all subdetectors • Expect extensive Validation work from the CTB by comparing with data • All assumptions (resolutions, smearing, …) to be revisited • Pileup • Pile-up stays in ~1Gbyte of memory, takes 5mn/event (1GHz) and needs ~10Mbyte/event of disk • Pythia used for the min-bias pile up events • A set of 500K min bias events with the atlas tunings is used • To do • Optimize I/O use vs. memory • Occupancy studies need to be done • MC truth navigation, not supported for pile-up • Lot of work still needed. Both for Validation and new Development A.Rimoldi, University of Pavia & INFN, Italy

13. The Simulation Validation Preproduction and DC2 • preliminary tests started at end 2003 • comparisons with Geant3 using common event samples and about the same geometry. • Hits and digits for all the ATLAS subdetectors generated • jobs run in parallel using the LSF batch facility and Castor facility (at CERN and outside) • we measured at different event/run phases the local peformance and memory usage • Generated samples • Single particle vs. E • SUSY events • H->4 leptons, Z->2leptons(e, mu,tau) • di-jet • minimum bias • Initial failure rate of ~10% for single particle jobs (30% in physics events), corrected patiently (geometry problems, G4 physics problems…) • Final failure rate is approximately 0% apart from AFS or Castor problems. • All jobs go straightforward to the end A.Rimoldi, University of Pavia & INFN, Italy

14. Watching the application @runtime • Inspections @runtime allow to • control the memory consumption • control the possible memory leaks during data production • evaluate pros / cons when a new feature is implemented • They are possible everywhere in the production flow, particulary useful at • Begin of Run • Begin of Event • Begin of Step • And at EOR, EOE, EOS A.Rimoldi, University of Pavia & INFN, Italy

15. Configuration • CPU Time per Event(2.4 GHz PIV) [s] • Event Size • [kB] • e±, ||<2.5 • ±,||<3.2 • ±, ||<3.2 • pT=50 GeV • Full Detector (DC1 Layout) • 54.04 • 1.33 • 22.7 /40.4 / 10.6 • 69.21 • 60.27 • Full Detector, no B-Field • 45.01 • .92 • 22.0 / 39.3 /10.2 • Inner Detector • 0.44 • .93 • .11 • 14.0 /10.2 / 5.1 • LAr Calorimeter • 69.50 • 149.57 • .82 • 5.8 /16.6 / .6 • Tile Calorimeter • 10.91 • 19.13 • .16 • 0.7 / 0.8 / .3 • Muon System + Toroids • 16.45 • 38.82 • .17 • 147.9 / 74.4 /2.7 • Configuration • CPU Time per Event • Event Size • Full Detector (DC1 Layout) • (2.4 GHz PIV) [s] • [NCU-s] • [SI2k-s] • [kB] • 200 H(130)  4l, ||<5 • 664.0 • 2191.2 • 394420 • 2200 • 200 Z  ee, ||<5 • 686.5 • 2265.5 • 407790 • 1890 • 200 SUSY/SUGRA events,||<5 • 771.5 • 2546.1 • 458290 • 1950 G4 Timing: single particle and full events Heavy ions (Hijing) 3 full events produced A.Rimoldi, University of Pavia & INFN, Italy

16. The Physics with DC2 & CTB as a feedback to Simulation • Our goals • Get physics community familiar with the new software, new persistency, new analysis tools • Use large produced samples to understand performance and tune new simulation • Test algorithms on CTB data: • Understand limitations of simulation • Understand key issues for reconstruction algorithms • Tune simulation parameters • Get to the end of the yearwith large well-understood samples of simulated data, stable and tested software chain • Full simulation analyses (signal + background) for initial detector setup on key physics channels • Inject additional realism into simulation studies • Waiting for feedback from our users community A.Rimoldi, University of Pavia & INFN, Italy

17. Conclusions • The Simulation Geant4-based was successfully tested and it has by now replaced the Geant3-based one • We extensively measured the performance and robustness of the new simulation with great success • We can use Parameterizations for further improving the simulation performance • Geant4 is the main engine for the simulation in ATLAS A.Rimoldi, University of Pavia & INFN, Italy

18. Thanks • To all the core developers • For the robust, versatile and complete code provided • To the subdetector people • For their prompt implementation of any new functionality provided • To the GEANT4 collaboration • for their help in transforming this exercise into a success A.Rimoldi, University of Pavia & INFN, Italy