10-15 March 2019
Steinmatte conference center
Europe/Zurich timezone

Machine Learning helping Monte-Carlo collider simulations

11 Mar 2019, 16:10
20m
Steinmatte Room C

Steinmatte Room C

Oral Track 3: Computations in Theoretical Physics: Techniques and Methods Track 3: Computations in Theoretical Physics: Techniques and Methods

Speaker

Dr Valentin Hirschi (ETHZ)

Description

The high-energy community recently witnessed the first attempts at leveraging machine (deep) learning techniques for improving the efficiency of the numerical Monte-Carlo integrations that lie at the core of most high-energy physics simulations.
The first part of my talk will characterise the various type of integrations necessary in these simulations as well as the type of improvements that could significantly impact their efficiency.
The second part will focus on reviewing the objectives and achievements of the first attempts at applying modern machine learning techniques in this context.

Primary author

Presentation materials