SMuK 2023 – scientific programme

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T: Fachverband Teilchenphysik

T 30: Higgs Charm, Di-Higgs

T 30.6: Talk

Tuesday, March 21, 2023, 18:15–18:30, HSZ/0105

A neural network based regression of the neutrinos in H→ττ decays for a resonant HH→bbττ analysis — Philip Keicher, •Tobias Kramer, Nathan Prouvost, Marcel Rieger, Peter Schleper, Jan Voss, and Bogdan Wiederspan — Universität Hamburg

The CMS resonant HH→bbττ analysis searches for heavy spin 0/2 resonances decaying into two Higgs bosons which subsequently decay into bottom quarks and tau leptons. It uses the Run 2 data collected from 2016-2018 at a center of mass energy of √s = 13 TeV corresponding to an integrated luminosity of 138 fb⁻¹. As a wide range of resonance masses is covered, reconstructing the invariant mass of the HH system and therefore the individual Higgs bosons is crucial. Especially for the Higgs boson decaying into tau leptons a significant amount of information is lost in the form of neutrinos not being measured by the detector. This talk presents a study on how to regress the full HH system using deep neural networks in order to improve the mass resolution of a potential new heavy particle.