Precision-Machine Learning for the Matrix Element Method

Abstract

The matrix element method is the LHC inference method of choice for limited statistics. We present a dedicated machine learning framework, based on efficient phase-space integration, a learned acceptance and transfer function. It is based on a choice of INN and diffusion networks, and a transformer to solve jet combinatorics. We showcase this setup for the CP-phase of the top Yukawa coupling in associated Higgs and single-top production.

Comments: 26 pages, 12 figures, v2: update references, v3: include evaluation on Herwig