The PANDA experiment at the future facility FAIR will study anti-proton proton and anti-proton nucleus collisions in a beam momentum range from 2 GeV/c up to 15 GeV/c. The PandaRoot framework is part of the FairRoot project, a common software framework for the future FAIR experiments, and is currently used to simulate detector performances and to evaluate different detector concepts. It is based on the packages ROOT and Virtual MonteCarlo with Geant3 and Geant4. Different reconstruction algorithms for tracking and particle identification are under development and optimization, in order to achieve the performance requirements of the experiment. In the central tracker a first track fit is performed using a conformal map transformation based on a helix assumption, then the track is used as input for a Kalman Filter (package genfit), using GEANE as track follower. The track is then correlated to the pid detectors (e.g. Cerenkov detectors, EM Calorimeter or Muon Chambers) to evaluate a global particle identification probability, using a Bayesian approach or multivariate methods. Further implemented packages in PandaRoot are: the analysis tools framework Rho, the kinematic fitter package for vertex and mass constraint fits, and a fast simulation code based upon parametrized detector responses. PandaRoot was also tested on an Alien-based GRID infrastructure. The contribution will report about the status of PandaRoot and show some example results for analysis of physics benchmark channels.

The PandaRoot framework for simulation, reconstruction and analysis

SPATARO, STEFANO GIOVANNI;
2011-01-01

Abstract

The PANDA experiment at the future facility FAIR will study anti-proton proton and anti-proton nucleus collisions in a beam momentum range from 2 GeV/c up to 15 GeV/c. The PandaRoot framework is part of the FairRoot project, a common software framework for the future FAIR experiments, and is currently used to simulate detector performances and to evaluate different detector concepts. It is based on the packages ROOT and Virtual MonteCarlo with Geant3 and Geant4. Different reconstruction algorithms for tracking and particle identification are under development and optimization, in order to achieve the performance requirements of the experiment. In the central tracker a first track fit is performed using a conformal map transformation based on a helix assumption, then the track is used as input for a Kalman Filter (package genfit), using GEANE as track follower. The track is then correlated to the pid detectors (e.g. Cerenkov detectors, EM Calorimeter or Muon Chambers) to evaluate a global particle identification probability, using a Bayesian approach or multivariate methods. Further implemented packages in PandaRoot are: the analysis tools framework Rho, the kinematic fitter package for vertex and mass constraint fits, and a fast simulation code based upon parametrized detector responses. PandaRoot was also tested on an Alien-based GRID infrastructure. The contribution will report about the status of PandaRoot and show some example results for analysis of physics benchmark channels.
2011
International Conference on Computing in High Energy and Nuclear Physics (CHEP)
Taipei
18-22 October 2010
331
032031
-
Data acquisition: hardware and software; Applications of Monte Carlo methods; Calorimeters; Computer data analysis; Numerical optimization; Cherenkov detectors; Data presentation and visualization: algorithms and implementation; Data analysis: algorithms and implementation, data management
S. Spataro; the PANDA Collaboration
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/94156
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