6 papers
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…
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…
Mirror-skin thickness: a possible observable sensitive to the charge symmetry breaking energy density functional
Tomoya Naito, Yuto Hijikata, Juzo Zenihiro +2
We propose a new observable, named the mirror-skin thickness, in order to extract the strength of the charge symmetry breaking (CSB) term in an energy density functional (EDF). The…
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…
Charge symmetry breaking effects of - mixing in relativistic mean-field model
Yusuke Tanimura, Tomoya Naito, Hiroyuki Sagawa +1
We present a relativistic mean-field model that incorporates charge symmetry breaking (CSB) of nuclear force via - meson mixing, along with corrections to the electrom…
QCD sum rule approach to Okamoto-Nolen-Schiffer anomaly
Hiroyuki Sagawa, Tomoya Naito, Xavier Roca-Maza +1
A new framework is introduced to connect between a charge symmetry breaking (CSB) energy density functional (EDF) and the low-energy constants derived from quantum chromodynamics (…