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  4. Two invertible networks for the matrix element method
 
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2023
Journal Article
Title

Two invertible networks for the matrix element method

Abstract
The matrix element method is widely considered the ultimate LHC inference tool for small event numbers. We show how a combination of two conditional generative neural networks encodes the QCD radiation and detector effects without any simplifying assumptions, while keeping the computation of likelihoods for individual events numerically efficient. We illustrate our approach for the CP-violating phase of the top Yukawa coupling in associated Higgs and single-top production. Currently, the limiting factor for the precision of our approach is jet combinatorics.
Author(s)
Butter, Anja
Heimel, Theo
Martini, Till
Fraunhofer-Institut für Kurzzeitdynamik Ernst-Mach-Institut EMI  
Peitzsch, Sascha
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
Plehn, Tilman
Journal
SciPost physics  
Open Access
DOI
10.21468/SciPostPhys.15.3.094
Language
English
Fraunhofer-Institut für Kurzzeitdynamik Ernst-Mach-Institut EMI  
Fraunhofer-Institut für Offene Kommunikationssysteme FOKUS  
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