activity
20192025
most citedA deep neural network approach to solve the Dirac equation

6 citations · 13 across the 4 of their papers we have counts for

collaborators

5 papers

nucl-th2025★ 3 cited

Quartet correlations near the surface of nuclei

Yixin Guo, Tomoya Naito, Hiroyuki Tajima +1

We theoretically investigate Cooper quartet correlations in doubly-magic nuclei (, , and ). We firs…

quant-ph2024★ 6 cited

A deep neural network approach to solve the Dirac equation

Chuanxin Wang, Tomoya Naito, Jian Li +1

We extend the method from [Naito, Naito, and Hashimoto, Phys. Rev. Research 5, 033189 (2023)] to solve the Dirac equation not only for the ground state but also for low-lying excit…

nucl-th2024★ 2 cited

A neural network approach for two-body systems with spin and isospin degrees of freedom

Chuanxin Wang, Tomoya Naito, Jian Li +1

We propose an enhanced machine learning method to calculate the ground state of two-body systems. By extending the original method [Naito, Naito, and Hashimoto, Phys. Rev. Research…

nucl-th2023

Possible inconsistency between phenomenological and theoretical determinations of charge symmetry breaking in nuclear energy density functionals

Tomoya Naito, Gianluca Colò, Tetsuo Hatsuda +3

We summarize the recent progress on the determination of the charge symmetry breaking term of nuclear energy density functionals. We point out that the strength of the term determi…

physics.comp-ph2019★ 2 cited

Relativistic density functional theory with finite-light-speed correction for the Coulomb interaction: a non-relativistic-reduction based approach

Tomoya Naito, Ryosuke Akashi, Haozhao Liang +1

The Breit correction, the finite-light-speed correction for the Coulomb interaction of the electron-electron interaction in , is introduced to density fu…