5 papers
The High Explosives and Affected Targets (HEAT) Dataset
Bryan Kaiser, Kyle Hickmann, Sharmistha Chakrabarti +6
Artificial Intelligence (AI) surrogate models provide a computationally efficient alternative to full-physics simulations, but no public datasets currently exist for training and v…
Direct Inference of Nuclear Equation-of-State Parameters from Gravitational-Wave Observations
Brendan T. Reed, Cassandra L. Armstrong, Rahul Somasundaram +4
The observation of neutron star mergers with gravitational waves (GWs) has provided a new method to constrain the dense-matter equation of state (EOS) and to better understand its…
Constraining Hamiltonians from chiral effective field theory with neutron-star data
Cassandra L. Armstrong, Brendan T. Reed, Tate Plohr +4
Multi-messenger observations of neutron stars (NSs) and their mergers have placed strong constraints on the dense-matter equation of state (EOS). The EOS, in turn, depends on micro…
Inferring three-nucleon couplings from multi-messenger neutron-star observations
Rahul Somasundaram, Isak Svensson, Soumi De +5
Understanding the interactions between nucleons in dense matter is an important challenge in theoretical physics. Effective field theories have emerged as the dominant approach to…
Inferring neutron star merger ejecta morphologies with kilonovae
Brendan L. King, Soumi De, Oleg Korobkin +2
In this study we incorporate a new grid of kilonova simulations produced by the Monte Carlo radiative transfer code SuperNu in an inference pipeline for astrophysical transients, a…