Professor Daniel Maitre daniel.maitre@durham.ac.uk
Professor
Professor Daniel Maitre daniel.maitre@durham.ac.uk
Professor
Henry Truong henry.truong@durham.ac.uk
PGR Student Doctor of Philosophy
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.
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 |
Public URL | https://durham-repository.worktribe.com/output/1224179 |
Related Public URLs | https://arxiv.org/pdf/2107.06625.pdf |
Published Journal Article
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PDF
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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