Fully Dynamical General Relativistic SPH: Progress and Challenges

ORAL

Abstract

The method of Smoothed Particle Hydrodynamics (SPH) has a lot of appeal for simulating variety of catastrophic astrophysical scenarios, such as mergers of compact objects, tidal disruptions, etc. SPH naturally refines dense areas and avoids vacuum without need for a “density floor”. With the recent detections of binary neutron star mergers GW170817 and GW190425 by the LIGO/Virgo collaboration, there is an increasing demand for better understanding of such mergers. Of particlar interest is the amount and composition of the neutron-rich matter ejected during the merger, as it harbors robust rapid neutron capture nucleosynthsis. Several previous works explored SPH with various degrees of approximations to general relativity, and a novel recent study proposed a fully dynamical relativistic SPH (Rosswog & Diener 2021). In this study, we explore another SPH approach to fully general relativistic dynamical geometry with a new code SPaRTA. It uses the Generalized Harmonic formulation of Einstein’s equations for evolving the dynamical metric. For the hydro, SPaRTA builds upon the fixed-metric SPH approach of Tejeda et al. (2017), generalizing it to time-dependent curvilinear geometries. We will discuss progress and challenges, and present several test problems.

*This work has been funded by the US Department of Energy through the Los Alamos National Laboratory. Los Alamos National Laboratory is operated by Triad National Security, LLC, for the National Nuclear Security Administration of U.S. Department of Energy (Contract No. 89233218CNA000001). Research presented in this article was supported by the Laboratory Directed Research and Development program of Los Alamos National Laboratory under projects number 20200145ER and 20190021DR. This research used resources provided by the Los Alamos National Laboratory Institutional Computing Program, which is supported by the U.S. Department of Energy National Nuclear Security Administration under Contract No. 89233218CNA000001.

Presenters

  • Oleg Korobkin

    • Los Alamos National Laboratory

Authors

  • Oleg Korobkin

    • Los Alamos National Laboratory
  • Bing-Jyun Tsao

    • Los Alamos National Laboratory
  • Hyun Lim

    • Los Alamos National Laboratory
  • Irina Sagert

    • Los Alamos National Laboratory
  • Wesley Even

    • Los Alamos National Laboratory
  • Julien Loiseau

    • Los Alamos National Laboratory