Chong-Chong HeANU, Benjamin D. WibkingMSU, Mark R. KrumholzANU
{"title":"A novel numerical method for mixed-frame multigroup radiation-hydrodynamics with GPU acceleration implemented in the QUOKKA code","authors":"Chong-Chong HeANU, Benjamin D. WibkingMSU, Mark R. KrumholzANU","doi":"arxiv-2407.18304","DOIUrl":null,"url":null,"abstract":"Mixed-frame formulations of radiation-hydrodynamics (RHD), where the\nradiation quantities are computed in an inertial frame but matter quantities\nare in a comoving frame, are advantageous because they admit algorithms that\nconserve energy and momentum to machine precision and combine more naturally\nwith adaptive mesh techniques, since unlike pure comoving-frame methods they do\nnot face the problem that radiation quantities must change frame every time a\ncell is refined or coarsened. However, implementing multigroup RHD in a\nmixed-frame formulation presents challenges due to the complexity of handling\nfrequency-dependent interactions and the Doppler shift of radiation boundaries.\nIn this paper, we introduce a novel method for multigroup RHD that integrates a\nmixed-frame formulation with a piecewise powerlaw approximation for frequency\ndependence within groups. This approach ensures the exact conservation of total\nenergy and momentum while effectively managing the Lorentz transformation of\ngroup boundaries and evaluation of group-averaged opacities. Our method takes\nadvantage of the locality of matter-radiation coupling, allowing the source\nterm for $N_g$ frequency groups to be handled with simple equations with a\nsparse Jacobian matrix of size $N_g + 1$, which can be inverted with $O(N_g)$\ncomplexity. This results in a computational complexity that scales linearly\nwith $N_g$ and requires no more communication than a pure hydrodynamics update,\nmaking it highly efficient for massively parallel and GPU-based systems. We\nimplement our method in the GPU-accelerated RHD code QUOKKA and demonstrate\nthat it passes a wide range of numerical tests. We demonstrate that the\npiecewise powerlaw method shows significant advantages over traditional opacity\naveraging methods for handling rapidly variable opacities with modest frequency\nresolution.","PeriodicalId":501423,"journal":{"name":"arXiv - PHYS - Space Physics","volume":"96 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Space Physics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2407.18304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Mixed-frame formulations of radiation-hydrodynamics (RHD), where the
radiation quantities are computed in an inertial frame but matter quantities
are in a comoving frame, are advantageous because they admit algorithms that
conserve energy and momentum to machine precision and combine more naturally
with adaptive mesh techniques, since unlike pure comoving-frame methods they do
not face the problem that radiation quantities must change frame every time a
cell is refined or coarsened. However, implementing multigroup RHD in a
mixed-frame formulation presents challenges due to the complexity of handling
frequency-dependent interactions and the Doppler shift of radiation boundaries.
In this paper, we introduce a novel method for multigroup RHD that integrates a
mixed-frame formulation with a piecewise powerlaw approximation for frequency
dependence within groups. This approach ensures the exact conservation of total
energy and momentum while effectively managing the Lorentz transformation of
group boundaries and evaluation of group-averaged opacities. Our method takes
advantage of the locality of matter-radiation coupling, allowing the source
term for $N_g$ frequency groups to be handled with simple equations with a
sparse Jacobian matrix of size $N_g + 1$, which can be inverted with $O(N_g)$
complexity. This results in a computational complexity that scales linearly
with $N_g$ and requires no more communication than a pure hydrodynamics update,
making it highly efficient for massively parallel and GPU-based systems. We
implement our method in the GPU-accelerated RHD code QUOKKA and demonstrate
that it passes a wide range of numerical tests. We demonstrate that the
piecewise powerlaw method shows significant advantages over traditional opacity
averaging methods for handling rapidly variable opacities with modest frequency
resolution.