activity
20222026
most citedDeep-neural-network approach to solving the ab initio nuclear structure problem

31 citations · 59 across the 11 of their papers we have counts for

collaborators
Showing 2025Show all

5 papers · 1 filter

nucl-th2025

Zemach radii and nuclear structure effects in hyperfine splitting of lithium isotopes

Yilong Yang, Evgeny Epelbaum, Chen Ji +1

Nuclear structure effects are essential for describing hyperfine splittings from high-precision atomic spectroscopy measurements. These effects are often parametrized by the effect…

nucl-th2025★ 1 cited

Machine learning the single- hypernuclei with neural-network quantum states

Zi-Xiao Zhang, Yi-Long Yang, Wan-Bing He +3

Single- hypernuclei are the most straightforward extension of atomic nuclei. A thorough description of baryonic system beyond first-generation quark sector is indispensable for…

nucl-th2025

Nuclear and neutron matter in the relativistic Brueckner-Hartree-Fock theory with next-to-leading order covariant chiral nuclear force

Wei-Jiang Zou, Yi-Long Yang, Jun-Xu Lu +3

The symmetric nuclear matter and pure neutron matter are investigated by the relativistic Brueckner-Hartree-Fock (RBHF) theory with the covariant chiral nuclear forces up to the ne…

nucl-th2025

Nuclear matter in relativistic Brueckner-Hartree-Fock theory with local and nonlocal covariant chiral interactions at leading order

Wei-Jiang Zou, Yi-Long Yang, Shihang Shen +1

The simultaneous description for nuclear matter and finite nuclei has been a long-standing challenge in nuclear ab initio theory. With the success for nuclear matter, the relativis…

nucl-th2025★ 5 cited

Chiral symmetry and peripheral neutron- scattering

Yilong Yang, Evgeny Epelbaum, Jie Meng +2

We propose and demonstrate that peripheral neutron- scattering at low energies can serve as a sensitive and clean probe of the long-range three-nucleon forces. To this aim, we p…