65 citations · 196 across the 14 of their papers we have counts for
4 papers · 1 filter
Nuclear data activities for medium mass and heavy nuclei at Los Alamos
M. R. Mumpower, T. M Sprouse, T. Kawano +7
Nuclear data is critical for many modern applications from stockpile stewardship to cutting edge scientific research. Central to these pursuits is a robust pipeline for nuclear mod…
Physically Interpretable Machine Learning for nuclear masses
M. R. Mumpower, T. M. Sprouse, A. E. Lovell +1
We present a novel approach to modeling the ground state mass of atomic nuclei based directly on a probabilistic neural network constrained by relevant physics. Our Physically Inte…
Beta-delayed fission in the coupled Quasi-particle Random Phase Approximation plus Hauser-Feshbach approach
M. R. Mumpower, T. Kawano, T. M. Sprouse
Beta-delayed neutron emission and -delayed fission (df) probabilities were calculated for heavy, neutron-rich nuclei using the Los Alamos coupled Quasi-Particle Random Phase…
Nuclear masses learned from a probabilistic neural network
A. E. Lovell, A. T. Mohan, T. M. Sprouse +1
Machine learning methods and uncertainty quantification have been gaining interest throughout the last several years in low-energy nuclear physics. In particular, Gaussian processe…