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 |
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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.
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Uncontrolled Keywords: Nuclear and High Energy Physics, General Physics and Astronomy |
SWORD Depositor: Publication Router |
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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... |
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Catalogue record
Date Deposited: 20 Jan 2021 15:35 |
Last Modified: 04 Jun 2025 14:58 |
Author: |
T. A. Nahool
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Author: | A. M. Yasser |
Author: | M. Anwar |
Author: | Chris Bowerman |
Author: | G. A. Yahya |
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Faculty of Business and Technology > School of Computer Science and EngineeringActions (login required)
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