Reconstructing particles in jets using deep learning on graphs and hypergraphs

by Dr. Etienne Dreyer

Weizmann Institute

at Particles and Fields Seminar

Mon, 21 Nov 2022, 14:00
Sacta-Rashi Building for Physics (54), room 207

Abstract

Data recorded by particle detectors are crucial for furthering our knowledge of fundamental particles and their interactions. At today’s energy frontier, detectors at the Large Hadron Collider such as ATLAS generate datasets with a quantity and feature complexity that cannot be fully exploited by traditional analysis methods. In this talk I will focus on how graph-based neural network algorithms are redefining what is possible at one of the most foundational steps of data analysis: particle reconstruction.

Created on 16-11-2022 by Chapman, Shira (schapman)
Updaded on 16-11-2022 by Chapman, Shira (schapman)