Prediction of nuclear charge density distribution with feedback neural network

Determination of neutron-skin thickness using configurational information entropy

(2022) Chun-Wang Ma et al.   Nuclear Science and Techniques

Precise Machine Learning Models for fragment production in Projectile Fragmentation Reactions by Bayesian Neural Networks

(2022) Chun-Wang 马春旺 Ma et al.   Chinese Physics C

Bayesian evaluation of residual production cross sections in proton induced nuclear spallation reactions

(2022) Dan Peng et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Iterative Bayesian Monte Carlo for nuclear data evaluation

(2022) Erwin Alhassan et al.   Nuclear Science and Techniques

Nuclear mass based on the multi-task learning neural network method

(2022) Xing-Chen Ming et al.   Nuclear Science and Techniques

Study of nuclear low-lying excitation spectra with the Bayesian neural network approach

(2022) Y.F. Wang et al.   PHYSICS LETTERS B

Magnetic moment predictions of odd-$A$ nuclei with the Bayesian neural network approach

(2021) Zilong Yuan et al.   Chinese Physics C

Machine learning the nuclear mass

(2021) Ze-Peng Gao et al.   Nuclear Science and Techniques

Nuclear fragments in projectile fragmentation reactions

(2021) Chun-Wang Ma et al.   PROGRESS IN PARTICLE AND NUCLEAR PHYSICS

Isotopic cross-sections in proton induced spallation reactions based on the Bayesian neural network method

(2020) Chun-Wang Ma et al.   Chinese Physics C

Taming Nuclear Complexity with a Committee of Multilayer Neural Networks

(2020) Raphaël-David Lasseri et al.   PHYSICAL REVIEW LETTERS

A Bayesian-Neural-Network Prediction for Fragment Production in Proton Induced Spallation Reaction

(2020) Chun-Wang 马春旺 Ma et al.   Chinese Physics C

Nuclear matter and neutron star properties with the extended Nambu-Jona-Lasinio model

(2019) Yan-Jun Chen   Chinese Physics C

Alpha half-lives calculation of superheavy nuclei with Qα-values predictions based on Bayesian neural network approach

(2019) Ubaldo Baños Rodríguez et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Towards an ab initio covariant density functional theory for nuclear structure

(2019) Shihang Shen et al.   PROGRESS IN PARTICLE AND NUCLEAR PHYSICS

Neutron rich matter in the laboratory and in the heavens after GW170817

(2019) C.J. Horowitz   ANNALS OF PHYSICS

Finite nuclear size effect to the fine structure of heavy muonic atoms

(2018) Abu Saleh Musa Patoary et al.   EUROPEAN PHYSICAL JOURNAL D

Nuclear mass predictions based on Bayesian neural network approach with pairing and shell effects

(2018) Z.M. Niu et al.   PHYSICS LETTERS B

An equation-of-state-meter of quantum chromodynamics transition from deep learning

(2018) Long-Gang Pang et al.   Nature Communications

Constraining Effective Field Theories with Machine Learning

(2018) Johann Brehmer et al.   PHYSICAL REVIEW LETTERS

Nuclear magnetic moments in covariant density functional theory

(2018) Jian Li et al.   Frontiers of Physics

Machine learning phases of matter

(2017) Juan Carrasquilla et al.   Nature Physics

Matter density distributions and elastic form factors of some two-neutron halo nuclei

(2017) Ahmed N Abdullah   PRAMANA-JOURNAL OF PHYSICS

Solving the quantum many-body problem with artificial neural networks

(2017) Giuseppe Carleo et al.   SCIENCE

Nuclear charge radii: density functional theory meets Bayesian neural networks

(2016) R Utama et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Quantum Monte Carlo methods for nuclear physics

(2015) J. Carlson et al.   REVIEWS OF MODERN PHYSICS

Estimations of fission barrier heights forRa,Ac,RfandDbnuclei by neural networks

(2014) Serkan Akkoyun et al.   INTERNATIONAL JOURNAL OF MODERN PHYSICS E-NUCLEAR PHYSICS

Coupled-cluster computations of atomic nuclei

(2014) G Hagen et al.   REPORTS ON PROGRESS IN PHYSICS

Searching for exotic particles in high-energy physics with deep learning

(2014) P. Baldi et al.   Nature Communications

A study on ground-state energies of nuclei by using neural networks

(2013) Tuncay Bayram et al.   ANNALS OF NUCLEAR ENERGY

An artificial neural network application on nuclear charge radii

(2013) S Akkoyun et al.   JOURNAL OF PHYSICS G-NUCLEAR AND PARTICLE PHYSICS

Progress on tilted axis cranking covariant density functional theory for nuclear magnetic and antimagnetic rotation

(2013) Jie Meng et al.   Frontiers of Physics

Table of experimental nuclear ground state charge radii: An update

(2012) I. Angeli et al.   ATOMIC DATA AND NUCLEAR DATA TABLES

Decodingβ-decay systematics: A global statistical model forβ−half-lives

(2009) N. J. Costiris et al.   PHYSICAL REVIEW C

Lattice simulations for few- and many-body systems

(2008) Dean Lee   PROGRESS IN PARTICLE AND NUCLEAR PHYSICS