Related papers: Hypernuclei with Neural Network Quantum States
Variational Monte Carlo and Green's function Monte Carlo are powerful tools for calculations of properties of light nuclei using realistic two-nucleon and three-nucleon potentials. Recently the GFMC method has been extended to multiple…
There is increasing interest in using high-energy collisions to probe the structure of nuclei, in particular with the high-precision data made possible by collisions performed with pairs of isobaric species. A systematic study requires a…
We analyze the peculiarities of the interaction of the lambda hyperon with s-shell nuclei. The spectra of bound and scattering states are studied in the hypernuclei $_{\Lambda}^{2}$H, $_{\Lambda}^{3}$H, $_{\Lambda}^{4}$H, $_{\Lambda}^{4}$He…
The improved quark mass density- dependent model, which has been successfully used to describe the properties of both finite nuclei and bulk nuclear matter, is extended to include the strange quark. The parameters of the model are…
Variational Monte Carlo calculations have been made for the $_{ \Lambda}^{17}$O hypernucleus using realistic two- and three-baryon interactions. A two pion exchange potential with spin- and space-exchange components is used for the…
In order to clarify the nature of hypernuclear low-lying states, we carry out a comprehensive study for the structure of $^{144-154}_{~~~~~~~~\Lambda}$Sm-hypernuclei, which exhibit a transition from vibrational to rotational characters as…
Shell-model calculations that include both Lambda and Sigma configurations with p-shell cores are used to interpret gamma-ray transitions in Lambda-7Li, -9Be, -10B, -11B, -12C, -15N, and -16O observed with the Hyperball array of Ge…
A fully microscopic model for the description of nuclear level density (NLD) in spherical nuclei is proposed. The model is derived by combining the partition function of the exact pairing solution plus the independent-particle model at…
Charge radii can be generally used to encode information about various fine structures of finite nuclei. In this work, a constructed Bayesian neural network based on the Monte Carlo dropout approach is proposed to accurately describe the…
We investigate the influence of phenomenological three-nucleon interactions on the systematics of ground-state energies and charge radii throughout the whole nuclear mass range from 4-He to 208-Pb. The three-nucleon interactions supplement…
Quantum computing is increasingly offering concrete solutions toward the simulation of nuclear structure, with the potential to overcome the exponential scaling that limits classical diagonalization methods in large spaces. A particularly…
The properties of low-density neutron matter are important for the understanding of neutron star crusts and the exterior of large neutron-rich nuclei. We examine various properties of dilute neutron matter using quantum Monte Carlo methods,…
Recently it was argued that it might be possible treat the conventional nuclear structure problem -- nonrelativistic point nucleons interacting through a static and rather singular potential -- as an effective theory in a shell-model basis.…
The interaction of Lambda*=Lambda(1405) with a nucleon is studied from the viewpoint of chiral dynamics. We construct the coordinate space Lambda* N potential in the meson-exchange picture, which serves as a fundamental ingredient for the…
The work presents the recent developments in Quantum Monte Carlo calculations for nuclear systems including strange degrees of freedom. The Auxiliary Field Diffusion Monte Carlo algorithm has been extended to the strange sector by the…
We use machine learning techniques to solve the nuclear two-body bound state problem, the deuteron. We use a minimal one-layer, feed-forward neural network to represent the deuteron S- and D-state wavefunction in momentum space, and solve…
We study the properties of double-$\Lambda$ hypernuclei in the relativistic mean-field theory, which has been successfully used for the description of stable and unstable nuclei. With the meson-hyperon couplings determined by the…
The analysis of quasiparticle spectra in heaviest $A\sim 250$ nuclei with spectroscopic data provides an additional constraint for the choice of effective interaction for the description of superheavy nuclei. It strongly suggest that only…
Due to its powerful capability and high efficiency in big data analysis, machine learning has been applied in various fields. We construct a neural network platform to constrain the behaviors of the equation of state of nuclear matter with…
Non-Hermitian quantum many-body systems exhibit a rich array of physical phenomena, including non-Hermitian skin effects and exceptional points, that remain largely inaccessible to existing numerical techniques. In this work, we investigate…