11–12 Nov 2021
Europe/Budapest timezone

Machine Learning for Simulation in High Energy Physics

12 Nov 2021, 09:00
45m
Lecture Track #2 AIME21 12. Nov. Morning

Speaker

Dalila Salamani (CERN)

Description

The simulation of the passage of particles through the detectors of High Energy Physics (HEP) experiments is a core component of any physics analysis. However, a detailed and accurate simulation of the detector response using the Geant4 toolkit is a time and CPU consuming process, making it a challenge to gather enough statistics. This is especially problematic for the upcoming High Luminosity LHC upgrade, with more complex events and a much increased trigger rate. In this talk, we discuss novel machine learning techniques that demonstrate efficient and accurate detector simulation and can be used to bridge the HL-LHC resource gap.

Primary author

Dalila Salamani (CERN)

Presentation materials

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