Large eddy simulations in astrophysics

Abstract In this review, the methodology of large eddy simulations (LES) is introduced and applications in astrophysics are discussed. As theoretical framework, the scale decomposition of the dynamical equations for compressible neutral fluids by means of spatial filtering is explained. For cosmological applications, the filtered equations in co-moving coordinates are formulated. Moreover, the decomposition is extended to magnetohydrodynamics (MHD). While energy is dissipated through numerical diffusivities in implicit large eddy simulations (ILES), explicit subgrid-scale (SGS) models are applied in LES to compute energy dissipation, mixing, and dynamo action due to numerically unresolved turbulent eddies. The most commonly used models in astrophysics are the Smagorinsky model, the hydrodynamical SGS turbulence energy equation model, and the non-linear structural model for both non-relativistic and relativistic MHD. Model validation is carried out a priori by testing correlations between model and data for specific terms or a posteriori by comparing turbulence statistics in LES and ILES. Since most solvers in astrophysical simulation codes have significant numerical diffusion, the additional effect of SGS models is generally small. However, convergence with resolution increases in some cases. A recent example is magnetic field amplification in binary neutron star mergers. For mesh-free codes, it has been shown that explicit modelling of turbulent diffusion of metals has a significant impact. Moreover, SGS models can help to compute the turbulent velocity dispersion consistently and to parameterize sub-resolution processes that are influenced by turbulence, such as the star formation efficiency in galaxy simulations.

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Publication Details

Journal
Living Reviews in Computational Astrophysics
Published
2025-11-10
DOI
https://doi.org/10.1007/s41115-025-00023-1
Primary Topic
Galaxies: Formation, Evolution, Phenomena
Type
article
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article

Large eddy simulations in astrophysics

W. Schmidt
Living Reviews in Computational Astrophysics
Galaxies: Formation, Evolution, Phenomena
article

Large eddy simulations in astrophysics

W. Schmidt
article en

Abstract

Abstract In this review, the methodology of large eddy simulations (LES) is introduced and applications in astrophysics are discussed. As theoretical framework, the scale decomposition of the dynamical equations for compressible neutral fluids by means of spatial filtering is explained. For cosmological applications, the filtered equations in co-moving coordinates are formulated. Moreover, the decomposition is extended to magnetohydrodynamics (MHD). While energy is dissipated through numerical diffusivities in implicit large eddy simulations (ILES), explicit subgrid-scale (SGS) models are applied in LES to compute energy dissipation, mixing, and dynamo action due to numerically unresolved turbulent eddies. The most commonly used models in astrophysics are the Smagorinsky model, the hydrodynamical SGS turbulence energy equation model, and the non-linear structural model for both non-relativistic and relativistic MHD. Model validation is carried out a priori by testing correlations between model and data for specific terms or a posteriori by comparing turbulence statistics in LES and ILES. Since most solvers in astrophysical simulation codes have significant numerical diffusion, the additional effect of SGS models is generally small. However, convergence with resolution increases in some cases. A recent example is magnetic field amplification in binary neutron star mergers. For mesh-free codes, it has been shown that explicit modelling of turbulent diffusion of metals has a significant impact. Moreover, SGS models can help to compute the turbulent velocity dispersion consistently and to parameterize sub-resolution processes that are influenced by turbulence, such as the star formation efficiency in galaxy simulations.

Living Reviews in Computational AstrophysicsVol. 11(1)
Universität Hamburg (DE)
Openalex Percentile: Top 77%
Galaxies: Formation, Evolution, Phenomena
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