期刊
ASTROPHYSICAL JOURNAL
卷 891, 期 2, 页码 -出版社
IOP PUBLISHING LTD
DOI: 10.3847/1538-4357/ab75e1
关键词
High energy astrophysics; Black holes; Relativistic fluid dynamics; Compact radiation sources; Computational methods
资金
- US Department of Energy through the Los Alamos National Laboratory
- National Nuclear Security Administration of U.S. Department of Energy [89233218CNA000001]
- Laboratory Directed Research and Development program of Los Alamos National Laboratory [20170527ECR, 20180716PRD2]
We present a conservative numerical method for radiation magnetohydrodynamics with frequency-dependent full transport in stationary spacetimes. This method is stable and accurate for both large and small optical depths and radiation pressures. The radiation stress-energy tensor is evolved in flux-conservative form, and closed with a swarm of samples that each transport a multigroup representation of the invariant specific intensity along a null geodesic. In each zone, the enclosed samples are used to efficiently construct a Delaunay triangulation of the unit sphere in the comoving frame, which in turn is used to calculate the Eddington tensor, average source terms, and adaptively refine the sample swarm. Radiation four-forces are evaluated in the moment sector in a semi-implicit fashion. The radiative transfer equation is solved in invariant form deterministically for each sample. Since each sample carries a discrete representation of the full spectrum, the cost of evaluating the transport operator is independent of the number of frequency groups, representing a significant reduction of algorithmic complexity for transport in frequency-dependent problems. The major approximation we make in this work is performing scattering in an angle-averaged way. Local adaptivity in samples also makes this scheme more amenable to nonuniform meshes than a traditional Monte Carlo method. We describe the method and present results on a suite of test problems. We find that Method of Characteristics Moment Closure converges at least as similar to N-1, rather than the canonical Monte Carlo N-1/2, where N is the number of samples per zone.
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