9-13 July 2018
Sofia, Bulgaria
Europe/Sofia timezone

Application of a Convolutional Neural Network for image classification to the analysis of collisions in High Energy Physics

10 Jul 2018, 15:45
15m
Hall 9 (National Palace of Culture)

Hall 9

National Palace of Culture

presentation Track 6 – Machine learning and physics analysis T6 - Machine learning and physics analysis

Speaker

Mr Ignacio Heredia Cacha (Instituto de Física de Cantabria)

Description

The application of deep learning techniques using convolutional neu-
ral networks to the classification of particle collisions in High Energy Physics is
explored. An intuitive approach to transform physical variables, like momenta of
particles and jets, into a single image that captures the relevant information, is
proposed. The idea is tested using a well known deep learning framework on a sim-
ulation dataset, including leptonic ttbar events and the corresponding background
at 7 TeV from the CMS experiment at LHC, available as Open Data. This initial
test shows competitive results when compared to more classical approaches, like
those using feedforward neural networks.

Primary authors

Mrs Celia Fernandez Madrazo (Instituto de Física de Cantabria) Mr Ignacio Heredia Cacha (Instituto de Física de Cantabria) Mrs Lara Lloret Iglesias (Instituto de Física de Cantabria) Mr Jesus Marco de Lucas (Instituto de Física de Cantabria)

Presentation Materials