Göttingen 2025 – scientific programme
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T: Fachverband Teilchenphysik
T 46: Higgs Physics VI (top-Higgs Coupling)
T 46.2: Talk
Wednesday, April 2, 2025, 16:30–16:45, ZHG105
Preliminary Studies of the ttH(bb) Process in the Dileptonic Channel with SPANet, using CMS Run3 data — •Matin Torkian1, Maria Aldaya martin2, Dina Leyva Pernia2, and Henriette Petersen2 — 1DESY, Hamburg University, Germany — 2DESY, Hamburg, Germany
The Standard Model (SM) of particle physics predicts that the Higgs boson couples to fermions via a Yukawa-type interaction, with a strength proportional to the fermion mass. This makes the associated production of a Higgs boson with a top-quark pair ( ttH ) a crucial process to directly probe the top-Higgs Yukawa coupling, an essential parameter for confirming the SM nature of the Higgs boson. Among Higgs boson decays, the channel into a bb quark pair has the largest branching fraction, offering an experimentally promising final state. However, ttH(bb) process faces significant challenges regarding backgrounds, especially tt +jets production, with the ttbb background being irreducible with respect to the ttH, H → bb signal. Advance Machine Learning techniques are essential to improve the sensitivity to the signal process.
This work focuses on the analysis of the ttH, H → bb process in events with two leptons, using proton-proton collision data collected by the CMS experiment at the LHC during Run3 at √s = 13.6 TeV . ML methods are explored to significantly enhance the sensitivity to the ttH signal. For the first time in this final state we are exploring the potential of SPANet for jet-parton assignment and neutrino kinematic regressions and finally signal and background classification.
Keywords: Top; spanet; machine learining; tthbb; ttbb