3 citations · 6 across the 7 of their papers we have counts for
4 papers · 1 filter
Bayesian model mixing with multi-reference energy density functional
Aman Sharma, Nicolas Schunck, Kyle Wendt
Reliably predicting nuclear properties across the entire chart of isotopes is important for applications ranging from nuclear astrophysics to superheavy science to nuclear technolo…
Evaluation of phase shifts for non-relativistic elastic scattering using quantum computers
Francesco Turro, Kyle A. Wendt, Sofia Quaglioni +2
Simulations of scattering processes are essential in understanding the physics of our universe. Computing relevant scattering quantities from ab initio methods is extremely difficu…
Illuminating Systematic Trends in Nuclear Data with Generative Machine Learning Models
Jordan M. R. Fox, Kyle A. Wendt
We introduce a novel method for studying systematic trends in nuclear reaction data using generative adversarial networks. Libraries of nuclear cross section evaluations exhibit in…
Learning nuclear cross sections across the chart of nuclides with graph neural networks
Hongjun Choi, Sinjini Mitra, Jason Brodksy +6
In this work, we explore the use of deep learning techniques to learn how nuclear cross sections change as we add or remove protons and neutrons. As a proof of principle, we focus…