Advances in machine learning methods provide tools that have broad applicability in
scientific research. These techniques are being applied across the diversity of nuclear …

Atomic nuclei are quantum many-body systems of protons and neutrons held together by
strong nuclear forces. Under the proper conditions, nuclei can break into two (sometimes …

Metamodeling for the nucleonic equation of state (EOS), inspired from a Taylor expansion
around the saturation density of symmetric nuclear matter, is proposed and parameterized in …

There has been much recent interest in nuclear fission, due in part to a new appreciation of
its relevance to astrophysics, stability of superheavy elements, and fundamental theory of …

This article reviews how nuclear fission is described within nuclear density functional theory.
A distinction should be made between spontaneous fission, where half-lives are the main …

We perform a joint Bayesian inference of neutron-star mass and radius constraints based on
GW170817, observations of quiescent low-mass x-ray binaries (QLMXBs), photospheric …

Background: The mass, or binding energy, is the basis property of the atomic nucleus. It
determines its stability and reaction and decay rates. Quantifying the nuclear binding is …

We describe the Bayesian analysis of nuclear dynamics (BAND) framework, a
cyberinfrastructure that we are develo** which will unify the treatment of nuclear models …

The observation of neutrino oscillations and hence non-zero neutrino masses provided a
milestone in the search for physics beyond the Standard Model. But even though we now …

This is an exciting time for the study of r-process nucleosynthesis. Recently, a neutron star
merger GW170817 was observed in extraordinary detail with gravitational waves and …