ATLAS Simulation/Reconstruction Software Reported by S. Rajagopalan Reported by S. Rajagopalan work done by most US Institutes. work done by most US Institutes. U.S. ATLAS PCAP review U.S. ATLAS PCAP review Lawrence Berkeley National Laboratory Lawrence Berkeley National Laboratory January 15, 2002 January 15, 2002
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ATLAS Simulation/Reconstruction Software Reported by S. Rajagopalan work done by most US Institutes. U.S. ATLAS PCAP review Lawrence Berkeley National.
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ATLAS Simulation/Reconstruction Software
Reported by S. Rajagopalan Reported by S. Rajagopalan
work done by most US Institutes.work done by most US Institutes.
U.S. ATLAS PCAP reviewU.S. ATLAS PCAP review
Lawrence Berkeley National LaboratoryLawrence Berkeley National Laboratory
Simulation/Reconstruction Activities:Simulation/Reconstruction Activities:(mostly by physicists)
Subsystems with US participation:
Pixels, TRT, EM Cal, Forwad Cal, Tile Cal, Muons, Trigger
In addition, extensive participation in combined reconstruction, test
beam software and physics analysis.
Well integrated into overall ATLAS computing effort.Well integrated into overall ATLAS computing effort. In particular, the US core efforts on Athena and DB.
First revision of geometry since Physics TDR Latest geometry of the Inner Detector (incertable pixels, 2/3
layer variation, strip tilt inverted to minimize cluster size, realistic R/T in TRT)
Service Material updated Calorimeter: gap between barrel and endcap calorimeters
introduced readout of calorimeters updated (including 5 sample
digitization) dead material of the calorimeter readout updated Muon layout modified to latest geometry, digitization updated Optimised pile-up procedure allowing up to > 1k events to be
F. Luehring (Indiana) is the ATLAS TRT software coordinator.F. Luehring (Indiana) is the ATLAS TRT software coordinator. (and member of the TRT steering group)
compare features of interaction models with similar features in compare features of interaction models with similar features in the old Geant3.21 baselinethe old Geant3.21 baseline
try to understand differences in applied models, like the try to understand differences in applied models, like the effect of cuts on simulation parameters in the different effect of cuts on simulation parameters in the different variable space (range cut vs energy threshold…);variable space (range cut vs energy threshold…);
use available experimental references from testbeams for use available experimental references from testbeams for various sub-detectors and particle types to determine various sub-detectors and particle types to determine prediction power of models in Geant4 (and Geant3);prediction power of models in Geant4 (and Geant3);
use different sensitivities of sub-detectors (energy loss, track use different sensitivities of sub-detectors (energy loss, track multiplicities, shower shapes…) to estimate Geant4 multiplicities, shower shapes…) to estimate Geant4 performance;performance;
tune Geant4 models (“physics lists”) and parameters (range tune Geant4 models (“physics lists”) and parameters (range cut) for optimal representation of the experimental detector cut) for optimal representation of the experimental detector signal with ALL relevant repects;signal with ALL relevant repects;
Muon energy loss and secondaries production in the ATLAS Muon energy loss and secondaries production in the ATLAS calorimeters and muon detectorscalorimeters and muon detectors
Electromagnetic shower Electromagnetic shower simulations in calorimeterssimulations in calorimeters
Hadronic interactions in tracking Hadronic interactions in tracking devices and calorimeters devices and calorimeters
Geant4 can simulate relevant features of muon, electron and Geant4 can simulate relevant features of muon, electron and pion signals in various ATLAS detectors, often better than pion signals in various ATLAS detectors, often better than Geant3;Geant3;
Remaining discrepancies, especially for hadrons, are being Remaining discrepancies, especially for hadrons, are being addressed and progress can be expected in the near future;addressed and progress can be expected in the near future;
ATLAS can has a huge amount of the right testbeam data for ATLAS can has a huge amount of the right testbeam data for the calorimeters, inner detector modules, and the muon 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;
feedback loops to Geant4 team are for most systems feedback loops to Geant4 team are for most systems established since quite some time; communication is not a established since quite some time; communication is not a problem;problem;
Few people in US involved in G4 validation studies Few people in US involved in G4 validation studies I don’t think anyone from US is a member of the G4 team
Extensive involvement by US people, primarily in:Extensive involvement by US people, primarily in: LAr, Tile and Muon reconstruction Combined reconstruction: egamma, Jets, tau’s and MissingET
The overall reconstruction chain is functional, a lot of the fortran The overall reconstruction chain is functional, a lot of the fortran code has been rewritten in C++, albeit several missing pieces code has been rewritten in C++, albeit several missing pieces and far from perfect.and far from perfect.
Most of the effort is focussed on:Most of the effort is focussed on: Validation Calibration issues Test Beam Analysis Standardizing the EDM and Detector Description usage
Support for ROOT persistency for current Detector Description & some Support for ROOT persistency for current Detector Description & some Event Data Objects (Hong Ma, BNL who also coordinates ATLAS LAr Event Data Objects (Hong Ma, BNL who also coordinates ATLAS LAr database activities)database activities)
LAr Database/Detector Description activitiesLAr Database/Detector Description activities
Designed interfaces for accessing conditions data in Athena. Implemented interim solution for conditions data in MySQL for MC simulation, reconstruction, and some testbeam analysis.
Provide requirements input to ATLAS Conditions DB development
Detector Description: 2-day workshop at BNL (12/16/02) to discuss the adoption of the new Detector Description Architecture in LAr Simu/Rec.
Tile Database activities coordinated by Tom Lecompte (ANL)Tile Database activities coordinated by Tom Lecompte (ANL)
Similar activities as those for LAr.
Muon database and detector descriptionMuon database and detector description
XML detector description: MDTs, RPCs, TGCs implemented
Identifier scheme for Muons implemented by Goldfarb, Assamagan
Liquid Argon : Liquid Argon : H. Ma, S. Rajagopalan (BNL), P. Loch (Arizona)H. Ma, S. Rajagopalan (BNL), P. Loch (Arizona) Tile Calorimeter : Tile Calorimeter : A. Gupta, F. Merritt (Chicago)A. Gupta, F. Merritt (Chicago) Combined Calorimeter Data Classes and AlgorithmsCombined Calorimeter Data Classes and Algorithms
Raw Data Flow Model establishedRaw Data Flow Model established London Meeting: (D.Quarrie & S. Rajagopalan met with London Meeting: (D.Quarrie & S. Rajagopalan met with
HLT to discuss their software design) HLT to discuss their software design) Established strategy on use of Athena/StoreGate in HLT
Data Converters (Hong Ma, BNL): Data Converters (Hong Ma, BNL): Simulation of ROB data and establishing relevant services ByteStream Raw Data and Calibrated Objects for use in
L2, L3 coordinated across all sub-systems by Hong Ma (and implemented for Liquid Argon)
Being implemented for Muons (K. Assamagan, BNL) Efficient on demand access to data in Regions of Interest
The ATLAS EF will use selection and classification algorithms derived The ATLAS EF will use selection and classification algorithms derived
from the offline suitefrom the offline suite
Offline software performance therefore has a direct impact on EF farm Offline software performance therefore has a direct impact on EF farm
size and costsize and cost
The HLT community has started “validation studies” (detailed The HLT community has started “validation studies” (detailed
benchmarking) of Athena, offline algorithms, and event modelbenchmarking) of Athena, offline algorithms, and event model
The aim is to set metrics for monitoring trends in software performanceThe aim is to set metrics for monitoring trends in software performance
It is clear that the software is presently far from adequateIt is clear that the software is presently far from adequate Not fair to judge during development phase But benchmarking can (and has) helped spur improvements Feedback during monthly meetings with A-team and regular interactions with
developers
Software performance is also important for offline – hope that offline Software performance is also important for offline – hope that offline
community will continue this workcommunity will continue this work
egamma Reconstruction egamma Reconstruction Algorithms developed by H. Ma, S. Rajagopalan (BNL) Algorithms to associate clusters and tracks and analyze variables necessary
for e identification (shower shapes, isolation, E/p, …) Calorimeter Cluster calibration (J. McDonald, Pittsburgh)
Jet ReconstructionJet Reconstruction Jet Algorithms (KT and cone) developed by A. Gupta, F. Merritt (Chicago) Jet and Tau Calibration (F. Paige, H. Ma, S. Rajagopalan) (BNL)
H1 style calibration adopted : Provides weighting at a cell level. EM showers are denser than hadronic showers: Cells with dense energy
deposition are weighted toward EM scale. Effective in improving linearity and resolution over standard techniques
(sampling weights).
Missing ET ReconstructionMissing ET Reconstruction
DC1 data production includes datasets from single electrons, pions, DC1 data production includes datasets from single electrons, pions, di-jet events to full physics events with & without pile-up using G3.di-jet events to full physics events with & without pile-up using G3.
Much of this data is already being analyzed to extract the relevant
calibration constants that is fed back into the process for full
reconstruction. One of the physics signatures fully simulated is 50k SUSY events at One of the physics signatures fully simulated is 50k SUSY events at
the following msugra point : (I. Hinchliffe, F. Paige driving this effort)the following msugra point : (I. Hinchliffe, F. Paige driving this effort)
m0=100, m1/2=300, A0=-300, tan=6, sign() = +
Rich in leptons (including tau’s), jets, b-jets, high multiplicity hard events which is an ideal candidate to test the software.
Most such signatures have previously been studied only with fast simulation