General relativistic MHD large eddy simulations with gradient subgrid-scale model

Autor: Federico Carrasco, Carlos Palenzuela, Borja Miñano, Daniele Viganò, Ricard Aguilera-Miret
Přispěvatelé: Ministerio de Economía y Competitividad (España), Ministerio de Educación y Ciencia (España), European Commission, European Research Council
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Zdroj: Physical Review D
Digital.CSIC. Repositorio Institucional del CSIC
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Popis: In several relativistic astrophysics scenarios, the understanding of the rich magnetohydrodynamics is hampered by the limitations set by the achievable numerical resolution. In these cases, it is a tremendous challenge to accurately simulate numerically all the relevant scales. We present how to study such systems by using large eddy simulations with a self-consistent subgrid-scale gradient model that we generalized to the special relativistic case in a previous work and now extend to the general relativistic case. Adapted from nonrelativistic scenarios, the so-called gradient model allows us to capture part of the effects of the hidden dynamics on the resolved scales, by means of a physically agnostic, mathematically based Taylor expansion of the nonlinear terms in the conservative evolution equations’ fluxes. One of the main applications is the binary neutron star mergers, where the collision excites a nontrivial amplification at small spatial scales. Motivated by this scenario, we assess the validity of this approach in bounding-box simulations of the magnetic Kelvin-Helmholtz instability. Several resolutions and a broad range of scenarios are considered in order to carefully test the performance of the model under three crucial aspects: (i) highly curved backgrounds, (ii) jumps on the fluid density profiles, and (iii) strong shocks. The results suggest that our extension of the gradient subgrid-scale model to general relativistic magnetohydrodynamics is a promising approach for studying binary neutron star mergers and other relevant astrophysical scenarios.
We acknowledge support from Spanish Ministry of Economy and Competitiveness Grants No. FPA2013-41042-P and No. AYA2016-80289-P (AEI/FEDER, UE). C. P. also acknowledges support from the Spanish Ministry of Education and Science through a Ramon y Cajal grant. D. V. is supported by the ERC Consolidator Grant “MAGNESIA” (No. 817661). We thankfully acknowledge the computer resources at MareNostrum and the technical support provided by Barcelona Supercomputing Center, with the time granted through the 17th PRACE regular call (project Tier-0 GEEFBNSM, Principal Investigator (P. I.) C. P.) and the RES calls AECT-2018-1-0005 (P. I. D. V.), AECT-2019-1-0007 (P. I. D. V.).
Databáze: OpenAIRE
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