Help us make Indico better by taking this survey! Aidez-nous à améliorer Indico en répondant à ce sondage !

May 8 – 10, 2023
University of Pittsburgh
US/Eastern timezone

Search for long-lived particles decaying to trackless jets with advanced machine learning techniques at CMS

May 9, 2023, 5:30 PM
15m
Lawrence Hall 104

Lawrence Hall 104

BSM BSM X

Speaker

Lisa Benato (Hamburg University (DE))

Description

Novel techniques, using trackless and delayed jet information combined in a deep neural network discriminator, can be employed to identify decays of long-lived particles. In this talk we present how such techniques could be exploited to search for long-lived particles decaying in the outer regions of the CMS silicon tracker or in the calorimeters. The results, obtained using the full Run-II dataset collected at the LHC, are interpreted in a simplified model of chargino-neutralino production, where the neutralino is the next-to-lightest supersymmetric particle, is long-lived, and decays to a gravitino and either a Higgs or Z boson.

Primary author

Lisa Benato (Hamburg University (DE))

Presentation materials