Using Artificial Neural Networks to Search for the Production of the Higgs Boson Together with a Single Top Quark

The possibility of using artificial neural networks to search for a rare process at the Large Hadron Collider is considered. An evolutionary algorithm that makes it possible to construct a neural network with an optimal set of parameters has been developed. Using Monte Carlo simulation, the signific...

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Bibliographic Details
Published in:	Physics of particles and nuclei letters Vol. 21; no. 3; pp. 481 - 488
Main Authors:	Boiko, I. R., Guseinov, N. A., Eletskikh, I. V., Didenko, A. R., Dolovova, O. A., Tropina, A. D.
Format:	Journal Article
Language:	English
Published:	Moscow Pleiades Publishing 2024 Springer Nature B.V
Subjects:	Artificial neural networks Evolutionary algorithms Higgs bosons Large Hadron Collider Monte Carlo simulation Particle and Nuclear Physics Physics Physics and Astronomy Physics of Elementary Particles and Atomic Nuclei. Experiment
Online Access:	Get full text
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Summary:	The possibility of using artificial neural networks to search for a rare process at the Large Hadron Collider is considered. An evolutionary algorithm that makes it possible to construct a neural network with an optimal set of parameters has been developed. Using Monte Carlo simulation, the significance of signal separation from the background is assessed. The use of neural networks significantly increases the signal significance and makes it possible to detect the process based on the data from completed sessions of the Large Hadron Collider.
ISSN:	1547-4771 1531-8567
DOI:	10.1134/S1547477124700468