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Systematic event generator tuning for the LHC

  • Andy Buckley
  • Hendrik Hoeth
  • Heiko Lacker
  • Holger Schulz
  • Jan Eike von Seggern
Open Access
Special Article - Tools for Experiment and Theory

Abstract

In this article we describe Professor, a new program for tuning model parameters of Monte Carlo event generators to experimental data by parameterising the per-bin generator response to parameter variations and numerically optimising the parameterised behaviour. Simulated experimental analysis data is obtained using the Rivet analysis toolkit. This paper presents the Professor procedure and implementation, illustrated with the application of the method to tunes of the Pythia 6 event generator to data from the LEP/SLD and Tevatron experiments. These tunes are substantial improvements on existing standard choices, and are recommended as base tunes for LHC experiments, to be themselves systematically improved upon when early LHC data is available.

Keywords

Monte Carlo DELPHI Collaboration Monte Carlo Generator Charged Multiplicity Minimisation Result 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag / Società Italiana di Fisica 2009

Authors and Affiliations

  • Andy Buckley
    • 1
  • Hendrik Hoeth
    • 2
  • Heiko Lacker
    • 3
  • Holger Schulz
    • 3
  • Jan Eike von Seggern
    • 3
  1. 1.Institute for Particle Physics PhenomenologyDurham UniversityDurhamUK
  2. 2.Department of Theoretical PhysicsLund UniversityLundSweden
  3. 3.Physics DepartmentBerlin Humboldt UniversityBerlinGermany

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