MOGLI: model for multiphase gas using multifluid hydrodynamics
Multiphase gas, with hot (∼ 10^6 K) and cold (∼ 10^4 K) gas, is ubiquitous in astrophysical media across a wide range of scales. However, simulating multiphase gas has been a long-standing challenge, due to large separation between the size of cold gas structures and scales at which such gas impacts...
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| Hauptverfasser: | , , |
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| Dokumenttyp: | Article (Journal) |
| Sprache: | Englisch |
| Veröffentlicht: |
December 2025
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| In: |
Monthly notices of the Royal Astronomical Society
Year: 2025, Jahrgang: 544, Heft: 4, Pages: 4447-4468 |
| ISSN: | 1365-2966 |
| DOI: | 10.1093/mnras/staf1976 |
| Online-Zugang: | Verlag, kostenfrei, Volltext: https://doi.org/10.1093/mnras/staf1976
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| Verfasserangaben: | Hitesh Kishore Das, Max Gronke and Rainer Weinberger |
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| 520 | |a Multiphase gas, with hot (∼ 10^6 K) and cold (∼ 10^4 K) gas, is ubiquitous in astrophysical media across a wide range of scales. However, simulating multiphase gas has been a long-standing challenge, due to large separation between the size of cold gas structures and scales at which such gas impacts the evolution of associated systems. In this study, we introduce a new subgrid framework for such multiphase gas, MOGLI: model for multiphase Gas using multifluid hydrodynamics, in multifluid arepo . We develop this approach using theoretical results from previous studies with resolved small-scale simulations, leading to a minimal number of free parameters in the formulation. We divide the interactions in the model into three sources: drag, turbulent mixing, and cold gas growth. As part of the model, we also include two methods for estimating local turbulent velocities, one using the Kolmogorov scaling, and the other using local velocity gradients. We verify different components of the framework through extensive comparison with benchmark single-fluid simulations across different simulation parameters, such as how resolved the cold gas is initially, turbulent Mach number, spatial resolution, and random initialization of turbulence. We find a very good qualitative and quantitative agreement across different simulation parameters and diagnostics for both local turbulent velocity estimation methods. We also reproduce behaviour like the cold gas survival criteria as an emergent property. We discuss applications and possible extensions of MOGLI and demonstrate its capability by running a simulation which would be computationally prohibitive to run as a resolved single-fluid simulation. | ||
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