A5070133976- Particle physics theoretical and experimental studies
- High-Energy Particle Collisions Research
- Quantum Chromodynamics and Particle Interactions
- Distributed and Parallel Computing Systems
- Computational Physics and Python Applications
- Particle Detector Development and Performance
- Information and Cyber Security
Fraunhofer Institute for Open Communication Systems
2022-2024
Humboldt-Universität zu Berlin
2020
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 QCD radiation and detector effects without any simplifying assumptions, while keeping computation likelihoods individual events numerically efficient. illustrate our approach CP-violating phase top Yukawa coupling in associated Higgs single-top production. Currently, limiting factor precision jet combinatorics.
In this article we study a Standard Model extension modifying the top-quark Yukawa coupling to Higgs boson by allowing mixture of CP-odd and -even couplings. Single production in association with an additional provides natural laboratory search for such extensions. However, because small cross section experimental analysis is challenging. Already measurement process highly non-trivial. Furthermore, using only measurements, certain parameter region would escape detection. Using explicit BSM...
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 QCD radiation and detector effects without any simplifying assumptions, while keeping computation likelihoods individual events numerically efficient. illustrate our approach CP-violating phase top Yukawa coupling in associated Higgs single-top production. Currently, limiting factor precision jet combinatorics.
The Matrix Element Method is a promising multi-variate analysis tool which offers an optimal approach to compare theory and experiment according the Neyman-Pearson lemma. However, until recently its usage has been limited by fact that only leading-order predictions could be employed. imperfect approximation of underlying probability distribution can introduce significant bias into requires major calibration for method when applied parameter determination. Moreover, estimating theoretical...
The Matrix Element Method is a promising multi-variate analysis tool which offers an optimal approach to compare theory and experiment according the Neyman-Pearson lemma. However, until recently its usage has been limited by fact that only leading-order predictions could be employed. imperfect approximation of underlying probability distribution can introduce significant bias into requires major calibration for method when applied parameter determination. Moreover, estimating theoretical...