4 citations · 4 across the 1 of their papers we have counts for
4 papers
Deep learning: Extrapolation tool for ab initio nuclear theory
Gianina Alina Negoita, James P. Vary, Glenn R. Luecke +8
Ab initio approaches in nuclear theory, such as the no-core shell model (NCSM), have been developed for approximately solving finite nuclei with realistic strong interactions. The…
Ab Initio No Core Shell Model with Leadership-Class Supercomputers
James P. Vary, Robert Basili, Weijie Du +9
Nuclear structure and reaction theory is undergoing a major renaissance with advances in many-body methods, strong interactions with greatly improved links to Quantum Chromodynamic…
Deep Learning: A Tool for Computational Nuclear Physics
Gianina Alina Negoita, Glenn R. Luecke, James P. Vary +6
In recent years, several successful applications of the Artificial Neural Networks (ANNs) have emerged in nuclear physics and high-energy physics, as well as in biology, chemistry,…
Recent progress in Hamiltonian light-front QCD
J. P. Vary, H. Honkanen, Jun Li +5
Hamiltonian light-front quantum field theory constitutes a framework for the non-perturbative solution of invariant masses and correlated parton amplitudes of self-bound systems. B…