A new machine learning approach for predicting the spectra of meson bound states

Yasser, A. M., Nahool, T. A., Anwar, M., Bowerman, Chris and Yahya, G. A. (2020) A new machine learning approach for predicting the spectra of meson bound states. International Journal of Modern Physics E. p. 2050092. ISSN 1793-6608

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Abstract

In this paper, we investigate the benefits of machine learning (ML) approaches in predicting the spectra of meson bound states. A linear model (LM) approach is used to predict the spectra of some heavy mesons. Our proposed method has been successfully reproduced in recent experiments, to validate known outcomes. Our results are compared favorably to those obtained using other techniques. This novel perspective opens up a new future in the use of ML in the field of particle physics.

Item Type: Article
Uncontrolled Keywords: Nuclear and High Energy Physics, General Physics and Astronomy
Divisions: Faculty of Technology > School of Computer Science
SWORD Depositor: Publication Router
Depositing User: Publication Router
Date Deposited: 20 Jan 2021 15:35
Last Modified: 09 Feb 2021 10:22
URI: http://sure.sunderland.ac.uk/id/eprint/12915
ORCID for T. A. Nahool: ORCID iD orcid.org/0000-0002-3967-0103

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