Göttingen 2025 – wissenschaftliches Programm

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T: Fachverband Teilchenphysik

T 68: Higgs Physics VIII (CP)

T 68.2: Vortrag

Donnerstag, 3. April 2025, 16:30–16:45, ZHG105

Machine Learning for Top-Associated Higgs Production: Probing CP Structure with Neural Simulation-Based Inference — •Stefan Katsarov, Stephen Jiggins, and Judith Katzy — Deutsches Elektronen-Synchrotron (DESY), Hamburg, Germany

The Standard Model (SM) predicts that the CP structure of the fermionic Higgs couplings is CP even. However, experimentally, a CP odd component is not yet fully excluded. Detecting an additional CP odd coupling would provide direct evidence of physics beyond the SM, with significant implications, such as explaining the baryon asymmetry in the universe. The CP structure can be directly measured in top-associated Higgs production processes (ttH and tH). However, this measurement is very challenging due to the extreme rarity of these production modes and the presence of irreducible backgrounds. I will demonstrate how Neural Simulation-Based Inference (NSBI), a novel machine-learning technique, can aid this measurement, presenting the first results of research in this direction.

Keywords: CP structure; Top-associated Higgs production; Neural Simulation-Based Inference; Physics beyond the Standard Model; Machine learning