Baryons from Mesons: A Machine Learning Perspective
High Energy Physics - Phenomenology
2020-03-26 v1 Machine Learning
High Energy Physics - Lattice
High Energy Physics - Theory
Computational Physics
Abstract
Quantum chromodynamics (QCD) is the theory of the strong interaction. The fundamental particles of QCD, quarks and gluons, carry colour charge and form colourless bound states at low energies. The hadronic bound states of primary interest to us are the mesons and the baryons. From knowledge of the meson spectrum, we use neural networks and Gaussian processes to predict the masses of baryons with 90.3% and 96.6% accuracy, respectively. These results compare favourably to the constituent quark model. We as well predict the masses of pentaquarks and other exotic hadrons.
Cite
@article{arxiv.2003.10445,
title = {Baryons from Mesons: A Machine Learning Perspective},
author = {Yarin Gal and Vishnu Jejjala and Damian Kaloni Mayorga Pena and Challenger Mishra},
journal= {arXiv preprint arXiv:2003.10445},
year = {2020}
}
Comments
25 pages, 3 figures, 1 table