Göttingen 2025 – wissenschaftliches Programm
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T: Fachverband Teilchenphysik
T 66: Searches/BSM IV (BSM with Tops, LQs)
T 66.1: Vortrag
Donnerstag, 3. April 2025, 16:15–16:30, ZHG010
Search for new physics in all-hadronic tttt using ML with the CMS experiment — •Shahzad Sanjrani1,2, Freya Blekman1,3, and Joel Goldstein2 — 1Deutsches ElektronenSynchrotron DESY, Hamburg, Germany — 2University of Bristol, Bristol, United Kingdom — 3University of Hamburg, Hamburg, Germany
There is current interest in searching for beyond the standard model particles produced in association with a top quark pair, tt + X(X→ t t). This project focuses on a top-philic Z* resonance model that may significantly enhance the tttt cross section. The all-hadronic channel is explored in the resolved regime using a novel machine learning algorithm, SPA-Net, which performs permutation-invariant jet-parton assignment to reconstruct events. This talk presents initial limits using this network to discriminate signal against large QCD multijet- and tt-dominated backgrounds. Studies shown use Monte Carlo simulations of proton-proton collision data gathered by the CMS detector at the LHC.
Keywords: Machine Learning; Z' resonance; Top quark