Artificial neural network approach for mass spectra of (ηc(nS),ψ(nS)) states and X(3940), X(4160), Y(4260), ψ(4415), Y(4660) charmonium-like resonances

This work is devoted to the study of charmonium S-states by solving the Schrödinger equation with Cornell plus spin–spin interaction term via the artificial neural network (ANN) approach. From the solutions provided by ANN approach, we propose possible assignments for some of the recently discovered charmonium-like resonances. For simplicity purpose, we restricted the study to the ground and radially excited S-states of charmonium. The charmonium wave function is represented by the feed forward ANN and its inputs are assimilated to coordinate values. We calculated the masses, hyperfine splittings, spin-averaged mass spectrum and Regge trajectories of pseudoscalar and vector charmonium states. Overall, our results are in good accordance with the available experimental data and past studies of the mass spectrum of [Formula: see text] and [Formula: see text] charmonium states. Further, we propose a possible assignment for some of the recently discovered charmonium-like mesons. We concluded that [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] are, respectively, good candidates of [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] charmonium-like resonances.

Authors

Institutions

Publication Details

Journal
International Journal of Modern Physics A
Published
2024-09-20
DOI
https://doi.org/10.1142/s0217751x24501239
Citations
1
Primary Topic
Quantum Chromodynamics and Particle Interactions
Type
article
Field-Weighted Citation Impact
0.66
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial neural network approach for mass spectra of (ηc(nS),ψ(nS)) states and X(3940), X(4160), Y(4260), ψ(4415), Y(4660) charmonium-like resonances

J. M. Ema’a Ema’a, A. Atangana Likéné, D. Nga Ongodo, G. H. Ben-Bolie et al.
1 citations
International Journal of Modern Physics A
Quantum Chromodynamics and Particle Interactions
0.66
article

Artificial neural network approach for mass spectra of (ηc(nS),ψ(nS)) states and X(3940), X(4160), Y(4260), ψ(4415), Y(4660) charmonium-like resonances

J. M. Ema’a Ema’a, A. Atangana Likéné, D. Nga Ongodo, G. H. Ben-Bolie, P. Ele Abiama
article en
1 citations

Abstract

This work is devoted to the study of charmonium S-states by solving the Schrödinger equation with Cornell plus spin–spin interaction term via the artificial neural network (ANN) approach. From the solutions provided by ANN approach, we propose possible assignments for some of the recently discovered charmonium-like resonances. For simplicity purpose, we restricted the study to the ground and radially excited S-states of charmonium. The charmonium wave function is represented by the feed forward ANN and its inputs are assimilated to coordinate values. We calculated the masses, hyperfine splittings, spin-averaged mass spectrum and Regge trajectories of pseudoscalar and vector charmonium states. Overall, our results are in good accordance with the available experimental data and past studies of the mass spectrum of [Formula: see text] and [Formula: see text] charmonium states. Further, we propose a possible assignment for some of the recently discovered charmonium-like mesons. We concluded that [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] are, respectively, good candidates of [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] charmonium-like resonances.

International Journal of Modern Physics AVol. 39(31)
Université de Yaoundé I (CM), University of Maroua (CM), Institut de Recherches Géologiques et Minières (CM)
Openalex Percentile: Top 14%
Quantum Chromodynamics and Particle Interactions
0.66
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.