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A factorisation-aware Matrix element emulator

Maître, Daniel; Truong, Henry

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Authors

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Henry Truong henry.truong@durham.ac.uk
PGR Student Doctor of Philosophy



Abstract

In this article we present a neural network based model to emulate matrix elements. This model improves on existing methods by taking advantage of the known factorisation properties of matrix elements. In doing so we can control the behaviour of simulated matrix elements when extrapolating into more singular regions than the ones used for training the neural network. We apply our model to the case of leading-order jet production in e+e− collisions with up to five jets. Our results show that this model can reproduce the matrix elements with errors below the one-percent level on the phase-space covered during fitting and testing, and a robust extrapolation to the parts of the phase-space where the matrix elements are more singular than seen at the fitting stage.

Citation

Maître, D., & Truong, H. (2021). A factorisation-aware Matrix element emulator. Journal of High Energy Physics, 2021(11), Article 066. https://doi.org/10.1007/jhep11%282021%29066

Journal Article Type Article
Acceptance Date Oct 18, 2021
Online Publication Date Nov 10, 2021
Publication Date 2021-11
Deposit Date Oct 29, 2021
Publicly Available Date Jan 24, 2022
Journal Journal of High Energy Physics
Print ISSN 1126-6708
Electronic ISSN 1029-8479
Publisher Scuola Internazionale Superiore di Studi Avanzati (SISSA)
Peer Reviewed Peer Reviewed
Volume 2021
Issue 11
Article Number 066
DOI https://doi.org/10.1007/jhep11%282021%29066
Related Public URLs https://arxiv.org/pdf/2107.06625.pdf

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
Open Access. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits any use, distribution and reproduction in any medium, provided the original author(s) and source are credited.





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