Speaker
Roberto Seidita
(Istituto Nazionale di Fisica Nucleare)
Description
A model-agnostic search for new physics in the dijet final state with the CMS experiment is presented. Other than the requirement of a narrow dijet resonance with a mass in the range of 1800-6000 GeV, minimal additional assumptions are placed on the signal hypothesis. Search regions are obtained by utilizing multivariate machine learning methods to select jets with anomalous substructure. A collection of complementary anomaly detection methods – based on unsupervised, weakly-supervised and semi-supervised algorithms – are used in order to maximize the sensitivity to unknown new physics signatures.
Primary authors
Roberto Seidita
(Istituto Nazionale di Fisica Nucleare)
hongbo liao
