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Modeling the Solid Neutron-Star Crust with SPH

ORAL

Abstract

The crust of a neutron star is a Coulomb crystal that is composed of a lattice of iron-type nuclei. As microphysical calculations show, it is the strongest material known in nature. This leads to potentially observable phenomena such as toroidal oscillations of the crust after giant X-ray flares, continuous gravitational waves from neutron-star mountains, and resonant shattering flares due to crustal failure in a neutron star merger event. Observations of these phenomena can in turn give insight into the properties of dense nuclear matter such as the nuclear equation of state.

However, the dynamical evolution of neutron stars, when modeled numerically, is usually described as a purely fluid dynamics problem. Here, we present the first 3D simulations of neutron-star crustal toroidal oscillations including material strength with the Los Alamos National Laboratory SPH code FleCSPH. The code has been extended by constitutive models for terrestrial and astrophysical solids as well as a fixed general relativistic background metric for compact stars.

In the first half of the talk, we present the numerical implementation of solid material modeling together with standard tests. The second half is on the simulation of crustal oscillations in the fundamental toroidal mode. Here, the crust is initially modeled as a thin layer on top of the neutron star. As it is very sensitive to density fluctuations and numerical interactions with the

core, we discuss different strategies to decouple the crust and core dynamics from each other and suppress numerical variations in crustal density.

Publication: I. Sagert et al. Modeling solids in nuclear astrophysics with sph. APJS, 267(2):47, Aug 2023

Presenters

  • Irina Sagert

    Los Alamos National Laboratory

Authors

  • Irina Sagert

    Los Alamos National Laboratory

  • Oleg Korobkin

    Los Alamos National Laboratory

  • Ingo Tews

    Los Alamos National Laboratory

  • Bing-Jyun Tsao

    University of Texas at Austin

  • Hyun Lim

    Los Alamos National Laboratory

  • Michael Falato

    Los Alamos National Laboratory

  • Abigail I Hartley

    University of Colorado Boulder

  • Julien Loiseau

    LANL

  • Christopher Mauney

    Los Alamos National Laboratory