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Monte Carlo tuning using ATLAS data

Monte Carlo tuning using ATLAS data. Davide Costanzo (on behalf of the ATLAS collaboration). Monte Carlo simulation process. The Monte Carlo simulation of the ATLAS detector is used in most ATLAS papers/results. Event generators:

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Monte Carlo tuning using ATLAS data

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  1. Monte Carlo tuning usingATLAS data DavideCostanzo (on behalf of the ATLAS collaboration) MonteCarlo tuning using ATLAS data

  2. Monte Carlo simulation process The Monte Carlo simulation of the ATLAS detector is used in most ATLAS papers/results Event generators: Pythia6, Pythia8, Herwig, Herwig++, Alpgen, AcerMC Mc@NLO, Powheg, Sherpa ... Tuning a combination ofevent generator and simulation parameters Data/MC comparison example ATLAS-CONF-2011-098 Search for Supersymmetry with MET, bjets and no leptons Data AtlasG4 simulation Reconstruction, Analysis Reconstruction, Analysis, Systematics MonteCarlo tuning using ATLAS data

  3. Event Generator tunings ATL-PHYS-PUB-2011-008 ATL-PHYS-PUB-2011-009 • PYTHIA 6 is used as the main general-purpose event generator in ATLAS. • The tune is performed in four stages: • 1) Flavour parameters tuned to hadron multiplicities/ratios, from e+e- collisions • 2) Final State Radiation (FSR) and hadronisation parameters, tuned to event shapes and jet rates from e+e- collisions • 3) Initial state shower parameters and primordial kT, tuned to Tevatron and ATLAS data • 4) Multiple Partonic Interaction (MPI) parameters, tuned to Tevatron and ATLAS data • For HERWIG/JIMMY, only the MPI parameters were tuned: • The inverse proton radius squared [PRRAD] • The MPI cut-off at √s = 1800 GeV [PTJIM0] • The MPI cut-off evolution [EXP] • Energy evolution of the MPI cut-off was added to HERWIG/JIMMY MPI model, to allow simultaneous tuning to 7 TeV and 900 GeV ATLAS UE data. MonteCarlo tuning using ATLAS data

  4. Pythia 6 tune ATL-PHYS-PUB-2011-009 AUET2B tuning to ATLAS data. To be used for 2011 analyses AUET2B (CTEQ6L1) main Pythia 6 tune for ATLAS MC11 MonteCarlo tuning using ATLAS data

  5. Pythia8 tune ATL-PHYS-PUB-2011-009 Pythia8 has a better diffractive modelling than Pythia 6 ATLAS A1 and AU1 tunes to √s=7TeV minimum bias and underlying event data For ATLAS MC11 MonteCarlo tuning using ATLAS data

  6. Herwig/Jimmy tune ATL-PHYS-PUB-2011-008 MonteCarlo tuning using ATLAS data

  7. The AtlasG4 simulation EPJC 70 (2010) 823 Over 109 events simulated with AtlasG4 so far A few examples of AtlasG4 tuning using data in the next few slides MonteCarlo tuning using ATLAS data

  8. Inner Detector material validation Use photon conversions in the Inner Detector to map the material distribution: Conversion rate (in colour) for R vs z The beam pipe, the pixel barrel and part of the SCT detectors are visible MonteCarlo tuning using ATLAS data

  9. Inner Detector material validation (2) Conversion rates for fixed eta: Small discrepancies still visible, geometry description in continuous evolution MonteCarlo tuning using ATLAS data

  10. Inner Detector hadron-graphy Reconstruct secondary vertices inclusively and select those arising from secondary hadronic interactions Details of modules in 1st Pixel layer. Cooling Pipe, Cables, Carbon Fibre shell MonteCarlo tuning using ATLAS data

  11. Calorimeter response to single hadrons ATLAS-CONF-2011-028 Measure the calorimeter response to isolated tracks in pp collisions: E=Energy deposited in the calorimeter p=track momentum (Central region) Pythia AMBT1 tune Geant4 QGSP_BERT Physics list E/p for isolated tracks (2.2<p<2.8 GeV) Translates into a jet energy scale uncertainty of 1% to 3%

  12. Calorimeter response to single hadrons (2) ATLAS-CONF-2011-019 Use Ks -> π+ π-, Λ-> π-p and Λ -> π+p to measure response to pion, protonsand anti-protons Response to anti-protons underestimated by MC (Only few % of the total energy in a jet) (Central region) Pythia AMBT1 tune Geant4 QGSP_BERT Physics list

  13. Jet shape measurement PRD 83 052003 ATL-PHYS-PUB-2011-010 Jets are composed by hadrons. The distribution of the hadrons within the jet depends on the parton-jet fragmentation process Differential jet shape ρ(r): Average fraction of jet PT in an annulus or radius r

  14. Conclusions • Simulation is a very important component of the ATLAS physics programme • Different components need to be tuned and validated. Tuning is a cyclic process : • Event generators • Geant4 MonteCarlo • ATLAS detector response • A good agreement is achieved between the ATLAS data and simulation • With more data available small discrepancies become visible resulting in a continuous improvement of the ATLAS Monte Carlo strategy MonteCarlo tuning using ATLAS data

  15. Response to electrons Use J/Psi and Z decay to study the response to electrons

  16. Response to muons Use Z->μμ events to study theresponse to muons. The Z mass reconstructed width, and hence the muon momentum resolution is underestimated in the simulation

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