Hybrid radiation hydrodynamics scheme with adaptive gravity-tree-based pseudo-particles

ABSTRACT H ii regions powered by ionizing radiation from massive stars drive the dynamical evolution of the interstellar medium. Fast radiative transfer methods for incorporating photoionization effects are thus essential in astrophysical simulations. Previous work by Petkova et al. established a hybrid radiation hydrodynamics (RHD) scheme that couples smoothed particle hydrodynamics (SPH) to grid-based Monte Carlo radiative transfer (MCRT) code. This particle-mesh scheme employs the Exact mapping method for transferring fluid properties between SPH particles and Voronoi grids on which the MCRT simulation is carried out. The mapping, however, can become computationally infeasible with large numbers of particles or grid cells. We present a novel optimization method that adaptively converts gravity tree nodes into pseudo-SPH particles. These pseudo-particles act in place of the SPH particles when being passed to the MCRT code, allowing fluid resolutions to be temporarily reduced in regions which are less dynamically affected by radiation. A smoothing length solver and a neighbour-finding scheme dedicated to tree nodes have been developed. We also describe the new heating and cooling routines implemented for improved thermodynamic treatment. We show that this tree-based RHD scheme produces results in strong agreement with benchmarks, and achieves a speed-up that scales with the reduction in the number of particle-cell pairs being mapped.

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Publication Details

Journal
Monthly Notices of the Royal Astronomical Society
Published
2025-02-28
DOI
https://doi.org/10.1093/mnras/staf366
Citations
1
Primary Topic
Fluid Dynamics Simulations and Interactions
Type
article
Field-Weighted Citation Impact
1.33
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article

Hybrid radiation hydrodynamics scheme with adaptive gravity-tree-based pseudo-particles

Maya A. Petkova, I. A. Bonnell, Cheryl S. C. Lau
1 citations
Monthly Notices of the Royal Astronomical Society
Fluid Dynamics Simulations and Interactions
1.33
article

Hybrid radiation hydrodynamics scheme with adaptive gravity-tree-based pseudo-particles

Maya A. Petkova, I. A. Bonnell, Cheryl S. C. Lau
article en
1 citations

Abstract

ABSTRACT H ii regions powered by ionizing radiation from massive stars drive the dynamical evolution of the interstellar medium. Fast radiative transfer methods for incorporating photoionization effects are thus essential in astrophysical simulations. Previous work by Petkova et al. established a hybrid radiation hydrodynamics (RHD) scheme that couples smoothed particle hydrodynamics (SPH) to grid-based Monte Carlo radiative transfer (MCRT) code. This particle-mesh scheme employs the Exact mapping method for transferring fluid properties between SPH particles and Voronoi grids on which the MCRT simulation is carried out. The mapping, however, can become computationally infeasible with large numbers of particles or grid cells. We present a novel optimization method that adaptively converts gravity tree nodes into pseudo-SPH particles. These pseudo-particles act in place of the SPH particles when being passed to the MCRT code, allowing fluid resolutions to be temporarily reduced in regions which are less dynamically affected by radiation. A smoothing length solver and a neighbour-finding scheme dedicated to tree nodes have been developed. We also describe the new heating and cooling routines implemented for improved thermodynamic treatment. We show that this tree-based RHD scheme produces results in strong agreement with benchmarks, and achieves a speed-up that scales with the reduction in the number of particle-cell pairs being mapped.

Monthly Notices of the Royal Astronomical SocietyVol. 538(3)
University of St Andrews (GB), Chalmers University of Technology (SE)
Openalex Percentile: Top 26%
Fluid Dynamics Simulations and Interactions
1.33
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Hybrid radiation hydrodynamics scheme with adaptive gravity-tree-based pseudo-particles — Maya A. Petkova, I. A. Bonnell, et al. · Monthly Notices of the Royal Astronomical Society (2025) | TGRS Research Map | TGRS