Three-Dimensional General-Relativistic Hydrodynamic Simulations of Binary Neutron Star Coalescence and Stellar Collapse with Multipatch Grids
arXiv:1212.1191 · doi:10.1103/PhysRevD.87.064023
Abstract
We present a new three-dimensional general-relativistic hydrodynamic evolution scheme coupled to dynamical spacetime evolutions which is capable of efficiently simulating stellar collapse, isolated neutron stars, black hole formation, and binary neutron star coalescence. We make use of a set of adapted curvi-linear grids (multipatches) coupled with flux-conservative cell-centered adaptive mesh refinement. This allows us to significantly enlarge our computational domains while still maintaining high resolution in the gravitational-wave extraction zone, the exterior layers of a star, or the region of mass ejection in merging neutron stars. The fluid is evolved with a high-resolution shock capturing finite volume scheme, while the spacetime geometry is evolved using fourth-order finite differences. We employ a multi-rate Runge-Kutta time integration scheme for efficiency, evolving the fluid with second-order and the spacetime geometry with fourth-order integration, respectively. We validate our code by a number of benchmark problems: a rotating stellar collapse model, an excited neutron star, neutron star collapse to a black hole, and binary neutron star coalescence. The test problems, especially the latter, greatly benefit from higher resolution in the gravitational-wave extraction zone, causally disconnected outer boundaries, and application of Cauchy-characteristic gravitational-wave extraction. We show that we are able to extract convergent gravitational-wave modes up to (l,m)=(6,6). This study paves the way for more realistic and detailed studies of compact objects and stellar collapse in full three dimensions and in large computational domains. The multipatch infrastructure and the improvements to mesh refinement and hydrodynamics codes discussed in this paper will be made available as part of the open-source Einstein Toolkit.
36 pages, 26 figures
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