2021

Machine Learning for Detector R&D

A cura di Prof. Fedor Ratnikov (National Research University - Moscow)

Europe/Rome
Aula C. Voci (Dipartimento di Fisica e Astronomia)

Aula C. Voci

Dipartimento di Fisica e Astronomia

Descrizione

The use of advanced machine learning techniques to speed up and improve the precision of the detector development and optimization cycle, with an emphasis on the experience and practical results obtained by applying this approach to optimizing the electromagnetic calorimeter design as a part of the upgrade project for the LHCb detector at LHC will be discussed.

Zoom link: https://cern.zoom.us/j/64604705321?pwd=SnZXRy9ndXBsYVNSaGgyam9BOXd2Zz09

Organizzato da

INFN Padova (S. Lacaprara, T. Dorigo)