Oct 19 – 23, 2020
Europe/Zurich timezone

General recipe to form input space for deep learning analysis of HEP scattering processes.

Oct 22, 2020, 11:55 AM
5m
Lightning talk 2 ML for analysis : Application of Machine Learning to analysis, event classification and fundamental parameters inference Workshop

Speaker

Lev Dudko (M.V. Lomonosov Moscow State University (RU))

Description

The important step of the analysis of HEP scattering processes is the optimization of the input space for multivariate technique. We propose general recipe how to form the set of low-level observables which are sensitive to the differences in hard scattering processes at the colliders. It will be demonstrated that without any sophisticated analysis of the kinematic properties one can achieve close to optimal performance of DNN with the proposed general set of low-level observables. The proposed approach is already described in [Int.J.Mod.Phys.A 35 (2020) 21, 2050119, hep-ph:2002.09350].

Primary authors

Lev Dudko (M.V. Lomonosov Moscow State University (RU)) Georgii Vorotnikov (M.V. Lomonosov Moscow State University (RU)) Petr Volkov (M.V. Lomonosov Moscow State University (RU)) Maksim Perfilov (M.V. Lomonosov Moscow State University (RU))

Presentation materials