Quark Model Study of Doubly Heavy $\Xi$ and $\Omega$ Baryons via Deep Neural Network and Hybrid Optimization
Abstract
In the present work we investigate the mass spectrum and semileptonic decays of double charm and bottom baryon states using the hypercentral quark model. We solve the six-dimensional Schr\"odinger equation via deep learning and particle swarm optimization techniques to improve the speed and accuracy. Then, we predict the masses of the ground and excited states of single and doubly heavy baryons. Working close to the zero recoil point, we also study the semileptonic decay widths and branching ratios of doubly heavy and baryons for the transitions. A comparison between our results and the evaluations of other theoretical models is also presented. Our predictions of mass spectrum and decay widths provide valuable information for the experiment searching for undiscovered heavy baryon states.
Keywords
Cite
@article{arxiv.2411.13091,
title = {Quark Model Study of Doubly Heavy $\Xi$ and $\Omega$ Baryons via Deep Neural Network and Hybrid Optimization},
author = {Zahra Ghalenovi and Masoumeh Moazzen Sorkhi and Amir Hossein Sovizi},
journal= {arXiv preprint arXiv:2411.13091},
year = {2025}
}
Comments
3 figures