Mechnich, J.

English

The Monte Carlo simulation of the detector response is an integral component of any analysis performed with data from the LHC experiments. As these simulated data sets must be both large and precise, their production is a CPU-intensive task. ATLAS has developed full and fast detector simulation techniques to achieve this goal within the computing limits of the collaboration. At the current early stages of data-taking, it is necessary to reprocess the Monte Carlo event samples continuously, while integrating adaptations to the simulation modules in order to improve the agreement with data taken by means of the detector itself. FATRAS is a fast track simulation engine which produces a Monte Carlo simulation based on modules and the geometry of the standard ATLAS track reconstruction algorithm. It can be combined with a fast parametrized-response simulation of the calorimeters. This approach shows a high level of agreement with the full simulation, while achieving a relative timing gain of two orders of magnitude. FATRAS was designed to provide a fast feedback cycle for tuning the MC simulation with real data: this includes the material distribution inside the detector, the integration of misalignment and current conditions, as well as calibration at the hit level. We present the updated and calibrated version of FATRAS based on the first LHC data. Extensive comparisons of the fast track simulation with the full simulation and data at 900 GeV are shown.<br/

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UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl)UvA-DARE (Digital Academic Repository)FATRAS - the ATLAS Fast Track Simulation projectMechnich, J.DOI10.1088/1742-6596/331/3/032046Publication date2011Document VersionFinal published versionPublished inJournal of Physics. Conference SeriesLink to publicationCitation for published version (APA):Mechnich, J. (2011). FATRAS - the ATLAS Fast Track Simulation project. Journal of Physics.Conference Series, 331(3), [032046]. https://doi.org/10.1088/1742-6596/331/3/032046General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s)and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an opencontent license (like Creative Commons).Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, pleaselet the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the materialinaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letterto: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. Youwill be contacted as soon as possible.Download date:09 Mar 2023FATRAS - the ATLAS Fast Track Simulation projectThis article has been downloaded from IOPscience. Please scroll down to see the full text article.2011 J. Phys.: Conf. Ser. 331 032046(http://iopscience.iop.org/1742-6596/331/3/032046)Download details:IP Address: 145.18.109.227The article was downloaded on 04/06/2012 at 12:16Please note that terms and conditions apply.View the table of contents for this issue, or go to the journal homepage for moreHome Search Collections Journals About Contact us My IOPscienceFATRAS - the ATLAS Fast Track Simulation projectJörg Mechnich (on behalf of the ATLAS collaboration)Nikhef, Science Park 105, 1098XG Amsterdam, The NetherlandsE-mail: Joerg.Mechnich@nikhef.nlAbstract. The Monte Carlo simulation of the detector response is an integral componentof any analysis performed with data from the LHC experiments. As these simulated datasets must be both large and precise, their production is a CPU-intensive task. ATLAS hasdeveloped full and fast detector simulation techniques to achieve this goal within the computinglimits of the collaboration. At the current early stages of data-taking, it is necessary to reprocessthe Monte Carlo event samples continuously, while integrating adaptations to the simulationmodules in order to improve the agreement with data taken by means of the detector itself.FATRAS is a fast track simulation engine which produces a Monte Carlo simulation basedon modules and the geometry of the standard ATLAS track reconstruction algorithm. It canbe combined with a fast parametrized-response simulation of the calorimeters. This approachshows a high level of agreement with the full simulation, while achieving a relative timing gain oftwo orders of magnitude. FATRAS was designed to provide a fast feedback cycle for tuning theMC simulation with real data: this includes the material distribution inside the detector, theintegration of misalignment and current conditions, as well as calibration at the hit level. Wepresent the updated and calibrated version of FATRAS based on the first LHC data. Extensivecomparisons of the fast track simulation with the full simulation and data at 900 GeV are shown.1. IntroductionModeling the elementary physics processes and simulating the interactions of particles withthe detection apparatus is an ever-growing complex field in contemporary high-energy physics.The tiny cross-sections of the signatures of new physics with respect to background processesrequire a large number of events to be generated for Monte Carlo studies. The major fraction ofdedicated computing time can be accounted to the simulation of interactions with the active andpassive material of the detector and in particular the determination of the detector response.With the construction and commissioning of the ATLAS experiment [1] at CERN a newera began: it is the largest volume particle detector ever constructed so far. Many differentsub-detectors, such as tracking devices and calorimeters, together with cabling and coolinginfrastructure, as well as two magnet systems form an immensely complicated apparatusweighing about 7000 tonnes.Estimating the response of the system as a whole is traditionally done in the most accurateway, modeling small structures which could affect traversing particles from the interaction pointin the center of the detector. However, this approach is not always feasible. Some analysesrequire a large number of collision events to be simulated which can only be done usinga simplified approach of modeling the detector material and the response of active detectorelements.International Conference on Computing in High Energy and Nuclear Physics (CHEP 2010) IOP PublishingJournal of Physics: Conference Series 331 (2011) 032046 doi:10.1088/1742-6596/331/3/032046Published under licence by IOP Publishing Ltd 12. The ATLAS ExperimentAbout one hundred meters below the surface of the French and Swiss countryside close toCERN, the Large Hadron Collider (LHC) is delivering streams of protons to four particledetectors since its start-up in 2008. ATLAS (Figure 1a) is a “multi-purpose” detector witha primary focus on the search for new physics, such as Supersymmetry or the Higgs Boson.The apparatus can be divided into three main parts: inner detector, calorimeters and the muonsystem. The former and the latter are tracking systems, responsible for precisely measuringthe momenta of charged particles. The calorimeters are used for determining the energiesof traversing particles. The inner detector (Figure 1b) consists of three subsystems: closestto the LHC beam line are the pixel detectors with very high granularity for determining theorigin of the hard scattering process and the position of secondary vertices from longer-livedunstable particles. The Semiconductor Tracker (SCT) and the Transition Radiation Tracker(TRT) provide additional precision hits for reconstructing tracks of charged particles.(a) The ATLAS detector (b) The ATLAS inner detectorFigure 1: The ATLAS detector at the LHC, full overview (a) and an enlarged view of the innerdetector (b) which consists of the pixel detector, the semiconductor tracker and the transitionradiation tracker.3. SimulationIn high energy physics, the modeling of the detector response with Monte Carlo methods is anintegral component of many studies. Tracking devices like the ATLAS pixel detectors and theSCT are extremely complex instruments that have to be commissioned and fully understood,also with respect to the results of previously conducted simulation efforts. In addition to that,physics analyses often require extensive data sets of simulated physics data for the estimationof systematic effects. The production of those simulated data to the very detail is usuallya very CPU-intensive task. The ATLAS collaboration has developed full and fast detectorsimulation techniques to achieve this goal within the computing limits of the collaboration [2].At the current stage of data-taking, it is necessary to reprocess the Monte Carlo event samplescontinuously, while integrating adaptations to the simulation modules in order to improve theagreement with the data taken from the detector itself. FATRAS is a fast track simulation engineof the ATLAS inner detector and muon system. It produces a Monte Carlo simulation basedon the software modules and the geometry used by the standard ATLAS track reconstructionalgorithms. It can be combined with a fast parametrized-response simulation of the calorimeter.This approach shows a high level of agreement with the Geant4-based full simulation, whilereducing the amount of computing time by two orders of magnitude. FATRAS was designed toprovide a fast feedback cycle for tuning the MC simulation to real data, including the materialInternational Conference on Computing in High Energy and Nuclear Physics (CHEP 2010) IOP PublishingJournal of Physics: Conference Series 331 (2011) 032046 doi:10.1088/1742-6596/331/3/0320462distribution inside the detector, the integration of misalignment and current conditions, as wellas calibration at the detector hit level. Figure 2 shows an overview of the different ATLAS tracksimulation strategies and different subtasks done in FATRAS.EVENT GENERATIONPrimary Interaction, Decay, Fragmentationqqg ttGeant4Detector Simulation,Full physics listDigitisationReconstructionFATRASTrack SimulationMaterial effectsParticle decayPhoton conversionsDigitisationATLFASTTrack representationsmearing4-Vector, PIDd0hsicriTrack(a) Track simulation in ATLASSIMULATION MODEREFIT MODE RECONSTRUCTION MODEnoise hitspatternrecognition(b) Track simulation and reconstruction in FATRASFigure 2: (a) Overview of the data flow for the full simulation with Geant4, the ATLAS fast tracksimulation FATRAS and the ATLAS fast simulation framework, ATLFAST. (b) Visualizationof the simulation and refit/reconstruction of a track of a charged particle. In all modes, thestandard ATLAS reconstruction software is used for navigating the different detector partsin the geometry and the extrapolation of the particle path through the magnetic field. Inreconstruction mode, detector effects such as the granularity and noise are taken into accountas well.4. Features of FATRASThe software takes care of modeling the most dominant effects of the traversed detector materialon the particle, such as multiple scattering/ionization loss, bremsstrahlung, hadronic interactionsand photon conversions. Also particle decays are simulated for all unstable particle types andtheir decay products are iteratively processed by the same algorithms. Design details of thedetectors (e.g. their granularity and readout methods) are also accounted for, such as forexample the cluster creation in the pixel detectors from neighbouring detector elements beinghit. As an example, the momentum spectra of photons produced by the bremsstrahlung ofelectrons is shown in Figure 3a. The simplified detector geometry which is used by FATRAScan be seen in a map of the origins of photon conversions, e.g. in the r/z-plane of the detectoras shown in the bottom of Figure 3b, and it can be compared with the corresponding geometryin the Geant4 based simulation, which is shown in the upper part of the same figure. A moreextensive description of FATRAS and its features can be found in [3].5. TimingComparison of the simulation time per event in kSI2K seconds for different simulationframeworks used by the ATLAS collaboration show a significant speed gain when using FATRAScombined with a fast calorimeter simulation (ATLFAST-IIF) w.r.t. to the Geant4 full simulation(see Table 1).International Conference on Computing in High Energy and Nuclear Physics (CHEP 2010) IOP PublishingJournal of Physics: Conference Series 331 (2011) 032046 doi:10.1088/1742-6596/331/3/0320463Mean  0 20 40 60 80 100 120110210310410510Entries  307120   4111p [GeV]Entries/binMean  Entries 195013   5874Geant4FATRAS(a) Momentum spectra of Bremsstrahlung photons  event:JiveXML_0_00025 run:0 ev:25  geometry: <default>40Y´ (m) 20040060080010001200ConversionPositionZ-3000 -2000 -1000 0 1000 2000 300002004006008001000z [mm]r [mm]r [mm]Geant4FATRAS(b) Tracker geometries derived from photon conversionsFigure 3: (a) Comparison of momentum spectra of Bremsstrahlung photons simulated withGeant4 (histogram) and FATRAS (points). (b) Simulated image of the ATLAS trackingdetectors using photon conversions for the underlying full Geant4 geometry and the simplifiedATLAS reconstruction geometryTable 1: Timing comparison for typical types of physics Monte Carlo events. All numbers aregiven in kSI2K-seconds per simulated event. The left column contains the times achieved withthe full simulation using Geant4. The middle column shows the same information for ATLFAST-II (using Geant4 for tracking and a fast calorimeter simulation). The right column displays thetiming of ATLFAST-IIF where FATRAS is used for tracking. An improvement of at least oneorder of magnitude can be seen between each column to the next for all signatures.Sample Type Full Simulation ATLFAST-II ATLFAST-IIFMinimum Bias 551.0 31.2 2.1tt̄ 1990.0 101.0 7.4Jets 2640.0 93.6 7.7γ + Jets 2850.0 71.4 5.7W → eνe 1150.0 57.0 4.1W → µνµ 1030.0 55.1 4.1Heavy Ion 56000.0 3050.0 203.06. Comparison with Experimental DataBased on data taken at a centre-of-mass energy of 900 GeV, several tracking-specific observableshave been compared to the output from FATRAS. The plots shown here concentrate ondistributions related to the pixel detectors and the track resolution of the vertex.The simple geometrical approach (Figure 4a) for reproducing the proper sizes for neighbouringpixel hits shows an excellent agreement between data and MC (Figure 4b).The number of hits in the pixel detector in dependence of the pseudorapidity η (Figure 5a)and the azimuthal angle φ (Figure 5b) are reproduced to a large extent, the general shape fitsvery nicely.The impact parameters z0 (Figure 6a) and d0 (Figure 6b) of the reconstructed tracks giveInternational Conference on Computing in High Energy and Nuclear Physics (CHEP 2010) IOP PublishingJournal of Physics: Conference Series 331 (2011) 032046 doi:10.1088/1742-6596/331/3/0320464dpxpyABCA B Ctrackpixel position (vetoed)(  )intersection with surfaceexit of sensor materialcluster position (a) Schematic display of the pixel cluster creationin FATRAS(b) Mean size of pixel clusters versus the η of theassociated trackFigure 4: (a) In FATRAS, pixel clusters are created by calculating the relative path length ofa track to a pixel volume and counting all pixels as hits where this quantity passes a tunablethreshold. (b) Comparison of the mean cluster size in the ATLAS pixel detector in 900 GeVcollision data (black points) and MC simulated with FATRAS (shaded histogram). The clustersize ∆η is given in a local coordinate along the global η coordinate.(a) Number of pixels hits versus η (b) Number of pixels hits versus φFigure 5: Comparison of the geometric distribution of pixel detector hits in η (a) and φ (b)in 900 GeV collision data (black points) and MC simulated with FATRAS (shaded histogram).The distribution is shaped by the existence of inactive pixel modules which are also taken intoaccount by FATRAS.information about the closest point of approach of a track w.r.t. to the beam line. They arerelevant for vertex reconstruction. While the general shape is reproduced sufficiently well byFATRAS, small deviations exist in the tails of the distributions.7. SummarySince the development of FATRAS was started, it has proven to be a useful tool, not only fordebugging the track reconstruction algorithms and the simplified reconstruction geometry ofthe ATLAS detector, but also as a fast simulation engine. Comparisons with real collision datashow that the description of the physics processes and the material distribution are modeled inInternational Conference on Computing in High Energy and Nuclear Physics (CHEP 2010) IOP PublishingJournal of Physics: Conference Series 331 (2011) 032046 doi:10.1088/1742-6596/331/3/0320465(a) d0 w.r.t. the primary vertex (b) z0 w.r.t. the primary vertexFigure 6: Comparison of the track impact parameters d0 (a) and z0 (b) w.r.t. the primary vertexin 900 GeV collision data (black points) and MC simulated with FATRAS (shaded histogram).a realistic way. The speed increase with respect to a detailed detector simulation which alsouses a much more complex description of the detector is significant. This implies that FATRASis a perfect tool for investigating questions that are related to tracking and also for simulatingalternative geometries. It has already been successfully used for studying different concepts ofa potential replacement of the ATLAS inner detector [4].References[1] The ATLAS Collaboration 2008, JINST 3 S08003, doi: 10.1088/1748-0221/3/08/S08003[2] The ATLAS Collaboration 2010, Eur.Phys.J.C70:823-874,2010[3] Edmonds K, Fleischmann S, Lenz T, Magass C, Mechnich J and Salzburger A 2008, ATL-SOFT-PUB-2008-01[4] Husemann U, Mechnich J and Salzburger A 2010 J. Phys.: Conf. Ser. 219 032021, doi: 10.1088/1742-6596/219/3/032021International Conference on Computing in High Energy and Nuclear Physics (CHEP 2010) IOP PublishingJournal of Physics: Conference Series 331 (2011) 032046 doi:10.1088/1742-6596/331/3/0320466

FATRAS - the ATLAS Fast Track Simulation project

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FATRAS - the ATLAS Fast Track Simulation project

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