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Sunderland Repository records the research produced by the University of Sunderland including practice-based research and theses.

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

Item Type: Article

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.

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More Information

Uncontrolled Keywords: Nuclear and High Energy Physics, General Physics and Astronomy
SWORD Depositor: Publication Router
Depositing User: Publication Router

Identifiers

Item ID: 12915
Identification Number: https://doi.org/10.1142/s0218301320500925
ISSN: 1793-6608
URI: http://sure.sunderland.ac.uk/id/eprint/12915
Official URL: https://www.worldscientific.com/doi/epdf/10.1142/S...

Users with ORCIDS

ORCID for T. A. Nahool: ORCID iD orcid.org/0000-0002-3967-0103

Catalogue record

Date Deposited: 20 Jan 2021 15:35
Last Modified: 09 Feb 2021 10:22

Contributors

Author: T. A. Nahool ORCID iD
Author: A. M. Yasser
Author: M. Anwar
Author: Chris Bowerman
Author: G. A. Yahya

University Divisions

Faculty of Technology > School of Computer Science

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