Constraining Hamiltonians from chiral effective field theory with neutron-star data
Cassandra L. Armstrong, Brendan T. Reed, Tate Plohr, Henrik Rose, Soumi De, Rahul Somasundaram, Ingo Tews

TL;DR
This paper develops a computational framework combining emulators and neural networks to directly infer nuclear Hamiltonian parameters from neutron star observations, bridging astrophysics and nuclear physics.
Contribution
It introduces a novel method that efficiently constrains chiral EFT Hamiltonian couplings using multi-messenger neutron star data.
Findings
Astrophysical data constrains two-nucleon couplings.
Emulators enable rapid EOS calculations from Hamiltonians.
Method bridges nuclear physics and astrophysical observations.
Abstract
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 microscopic nuclear interactions that are described by nuclear Hamiltonians. These Hamiltonians are commonly derived within chiral effective field theory (EFT). Ideally, multi-messenger observations of NSs could be used to directly inform our understanding of EFT interactions, but such a direct inference necessitates millions of model evaluations. This is computationally prohibitive because each evaluation requires us to calculate the EOS from a Hamiltonian by solving the quantum many-body problem with methods such as auxiliary-field diffusion Monte Carlo (AFDMC), which provides very accurate and precise solutions but at a significant computational cost. Additionally, we need to solve the stellar structure…
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Taxonomy
TopicsPulsars and Gravitational Waves Research · Nuclear physics research studies · Quantum Chromodynamics and Particle Interactions
