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HAMMER: Reweighting tool for simulated data samples
Modern flavour physics experiments, such as Belle II or LHCb, require large samples of generated Monte Carlo events. Monte Carlo events often are processed in a sophisticated chain that includes a simulation of the detector response. The generation and reconstruction of large samples is resource-int...
Autores principales: | , , , , |
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Lenguaje: | eng |
Publicado: |
SISSA
2017
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Materias: | |
Acceso en línea: | https://dx.doi.org/10.22323/1.282.1074 http://cds.cern.ch/record/2287330 |
Sumario: | Modern flavour physics experiments, such as Belle II or LHCb, require large samples of generated Monte Carlo events. Monte Carlo events often are processed in a sophisticated chain that includes a simulation of the detector response. The generation and reconstruction of large samples is resource-intensive and in principle would need to be repeated if e.g. parameters responsible for the underlying models change due to new measurements or new insights. To avoid having to regenerate large samples, we work on a tool, The Helicity Amplitude Module for Matrix Element Reweighting (HAMMER), which allows one to easily reweight existing events in the context of semileptonic b → q ` ̄ ν ` analyses to new model parameters or new physics scenarios. |
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