Seminari di Fenomenologia delle Particelle Elementari

Machine learning for hadron spectroscopy

by Dr Cesar Fernandez Ramirez (UNAM)

Europe/Rome
602 e online (Dip.to di Fisica Univ. di Genova)

602 e online

Dip.to di Fisica Univ. di Genova

Description

Recently, JPAC collaboration has developed and benchmarked a systematic approach to use Deep Neural Networks as a model-independent tool to analyze and interpret experimental data and to determine the nature of an exotic hadron. Specifically, we studied the line shape of the Pc(4312) signal reported by the LHCb collaboration. This novel method presents great potential and can be applied to other near-threshold resonance candidates.
 

Per connettersi a zoom

Topic: Theory and Pheno seminars

https://infn-it.zoom.us/j/8573185271
Meeting ID: 857 318 5271