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Title: Modeling UV Radiation Feedback from Massive Stars. I. Implementation of Adaptive Ray-tracing Method and Tests [Modeling UV Radiation Feedback from Massive Stars: I. Implementation of Adaptive Ray Tracing Algorithm]

Here, we present an implementation of an adaptive ray-tracing (ART) module in the Athena hydrodynamics code that accurately and efficiently handles the radiative transfer involving multiple point sources on a three-dimensional Cartesian grid. We adopt a recently proposed parallel algorithm that uses nonblocking, asynchronous MPI communications to accelerate transport of rays across the computational domain. We validate our implementation through several standard test problems, including the propagation of radiation in vacuum and the expansions of various types of H II regions. Additionally, scaling tests show that the cost of a full ray trace per source remains comparable to that of the hydrodynamics update on up to $$\sim {10}^{3}$$ processors. To demonstrate application of our ART implementation, we perform a simulation of star cluster formation in a marginally bound, turbulent cloud, finding that its star formation efficiency is 12% when both radiation pressure forces and photoionization by UV radiation are treated. We directly compare the radiation forces computed from the ART scheme with those from the M 1 closure relation. Although the ART and M 1 schemes yield similar results on large scales, the latter is unable to resolve the radiation field accurately near individual point sources.
Authors:
ORCiD logo [1] ; ORCiD logo [2] ; ORCiD logo [3] ; ORCiD logo [4]
  1. Seoul National Univ. (Korea, Republic of). Dept. of Physics & Astronomy; Princeton Univ., NJ (United States). Dept. of Astrophysical Sciences
  2. Seoul National Univ. (Korea, Republic of). Dept. of Physics & Astronomy
  3. Princeton Univ., NJ (United States). Dept. of Astrophysical Sciences
  4. Princeton Univ., NJ (United States). Dept. of Astrophysical Sciences; Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Report Number(s):
LLNL-JRNL-737937
Journal ID: ISSN 1538-4357; 888544
Grant/Contract Number:
AC52-07NA27344; NRF-2014; 2017R1A4A1015178; AST-1312006
Type:
Accepted Manuscript
Journal Name:
The Astrophysical Journal (Online)
Additional Journal Information:
Journal Name: The Astrophysical Journal (Online); Journal Volume: 851; Journal Issue: 2; Journal ID: ISSN 1538-4357
Publisher:
Institute of Physics (IOP)
Research Org:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org:
USDOE National Nuclear Security Administration (NNSA); National Research Foundation of Korea (NRF); National Science Foundation (NSF)
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; H ii regions; methods: numerical; radiation: dynamics; radiative transfer; stars: formation
OSTI Identifier:
1466954

Kim, Jeong-Gyu, Kim, Woong-Tae, Ostriker, Eve C., and Skinner, M. Aaron. Modeling UV Radiation Feedback from Massive Stars. I. Implementation of Adaptive Ray-tracing Method and Tests [Modeling UV Radiation Feedback from Massive Stars: I. Implementation of Adaptive Ray Tracing Algorithm]. United States: N. p., Web. doi:10.3847/1538-4357/aa9b80.
Kim, Jeong-Gyu, Kim, Woong-Tae, Ostriker, Eve C., & Skinner, M. Aaron. Modeling UV Radiation Feedback from Massive Stars. I. Implementation of Adaptive Ray-tracing Method and Tests [Modeling UV Radiation Feedback from Massive Stars: I. Implementation of Adaptive Ray Tracing Algorithm]. United States. doi:10.3847/1538-4357/aa9b80.
Kim, Jeong-Gyu, Kim, Woong-Tae, Ostriker, Eve C., and Skinner, M. Aaron. 2017. "Modeling UV Radiation Feedback from Massive Stars. I. Implementation of Adaptive Ray-tracing Method and Tests [Modeling UV Radiation Feedback from Massive Stars: I. Implementation of Adaptive Ray Tracing Algorithm]". United States. doi:10.3847/1538-4357/aa9b80. https://www.osti.gov/servlets/purl/1466954.
@article{osti_1466954,
title = {Modeling UV Radiation Feedback from Massive Stars. I. Implementation of Adaptive Ray-tracing Method and Tests [Modeling UV Radiation Feedback from Massive Stars: I. Implementation of Adaptive Ray Tracing Algorithm]},
author = {Kim, Jeong-Gyu and Kim, Woong-Tae and Ostriker, Eve C. and Skinner, M. Aaron},
abstractNote = {Here, we present an implementation of an adaptive ray-tracing (ART) module in the Athena hydrodynamics code that accurately and efficiently handles the radiative transfer involving multiple point sources on a three-dimensional Cartesian grid. We adopt a recently proposed parallel algorithm that uses nonblocking, asynchronous MPI communications to accelerate transport of rays across the computational domain. We validate our implementation through several standard test problems, including the propagation of radiation in vacuum and the expansions of various types of H II regions. Additionally, scaling tests show that the cost of a full ray trace per source remains comparable to that of the hydrodynamics update on up to $\sim {10}^{3}$ processors. To demonstrate application of our ART implementation, we perform a simulation of star cluster formation in a marginally bound, turbulent cloud, finding that its star formation efficiency is 12% when both radiation pressure forces and photoionization by UV radiation are treated. We directly compare the radiation forces computed from the ART scheme with those from the M1 closure relation. Although the ART and M1 schemes yield similar results on large scales, the latter is unable to resolve the radiation field accurately near individual point sources.},
doi = {10.3847/1538-4357/aa9b80},
journal = {The Astrophysical Journal (Online)},
number = 2,
volume = 851,
place = {United States},
year = {2017},
month = {12}
}