Numerical relativity simulations of compact binaries: Comparison of cell- and vertex-centered adaptive meshes

Year: 2025

Type: article

Abstract: Given the compact binary evolution problem of numerical relativity, in the finite-difference, block-based, adaptive mesh refinement context, choices must be made on how evolved fields are to be discretized. In -thena++, the space-time solver was previously fixed to be vertex centered. Here, our recent extensions to a cell-centered treatment are described. Simplifications in the handling of variables during the treatment of general relativistic magneto-hydrodynamical (GRMHD) evolution are found. A novelty is that performance comparison for the two choices of grid sampling is made within a single code base. In the case of a binary black hole inspiral-merger problem, by evolving geometric fields on vertex centers, an average ∼ 20 % speed increase is observed, when compared against cell-centered sampling. The opposite occurs in the GRMHD setting. A binary neutron star inspiral-merger-collapse problem, representative of typical production simulations, is considered. We find that cell-centered sampling for the space-time solver improves performance, by a similar factor.

Source: Physical review. D/Physical review. D.

DOI: 10.1103/lxp5-c1g1

Authors: Boris Daszuta, William Cook, Peter Hammond, Jacob Fields, Eduardo M. Gutiérrez, Sebastiano Bernuzzi, David Radice

Institutions: Friedrich Schiller University Jena, Pennsylvania State University

Language: English

Topic: Pulsars and Gravitational Waves Research

Subfield: Astronomy and Astrophysics

Field: Physics and Astronomy

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Science Foundation, U.S. Department of Energy, National Aeronautics and Space Administration, Alfred P. Sloan Foundation, Friedrich-Schiller-Universität Jena, Deutsche Forschungsgemeinschaft, Nuclear Safety and Security Commission, Gauss Centre for Supercomputing, Office of Science, European Research Council, Leibniz-Gemeinschaft, Leibniz-Rechenzentrum, National Cancer Institute, Nuclear Physics

OpenAlex ID: W4415944666