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| RADMC-3D | |
|---|---|
| Name | RADMC-3D |
| Title | RADMC-3D |
| Programming language | Python, Fortran |
| Operating system | Unix-like, Microsoft Windows, macOS |
RADMC-3D is a three-dimensional radiative transfer code designed for astrophysical dust and line transfer simulations. It is widely used in computational astrophysics for modeling spectral energy distributions, images, and polarization from protoplanetary disks, star-forming regions, and active galactic nuclei. The code has been applied in conjunction with observational facilities and theoretical frameworks to interpret continuum and molecular-line data.
RADMC-3D is a Monte Carlo and ray-tracing radiative transfer tool employed in studies connected to European Southern Observatory, Atacama Large Millimeter/submillimeter Array, Hubble Space Telescope, James Webb Space Telescope, and Very Large Array observations. Researchers using RADMC-3D commonly collaborate across institutions such as Harvard–Smithsonian Center for Astrophysics, Max Planck Institute for Astronomy, California Institute of Technology, National Radio Astronomy Observatory, and Institute of Astronomy, Cambridge. The code interfaces with hydrodynamics outputs from projects like Athena (software), PLUTO (code), ZEUS-MP, and FLASH (software), facilitating synthetic observation production for comparison with datasets from missions including Spitzer Space Telescope, Chandra X-ray Observatory, and GALEX.
RADMC-3D supports continuum radiative transfer, molecular line transfer, and polarized scattering calculations used in analyses similar to those undertaken by teams at Max Planck Institute for Astrophysics, Leiden Observatory, University of Cambridge, University of Toronto, and University of California, Berkeley. Capabilities include thermal Monte Carlo photon propagation, anisotropic scattering treatment applied in studies by European Space Agency groups, ray-tracing image synthesis compatible with instruments at Submillimeter Array, SOFIA, and Keck Observatory, and non-LTE line excitation computations comparable to work from Max Planck Institute for Extraterrestrial Physics. The package also handles dust opacities from opacity libraries used by researchers at Jet Propulsion Laboratory, Cornell University, and University of Michigan.
The codebase combines Python (programming language) front-end scripting with performance-critical modules in Fortran (programming language), following practices seen in projects like NumPy integrations and scientific workflows from SciPy. Its input/output formats interoperate with community standards such as FITS and mesh outputs from grid generators used in collaborations with CERN-linked computational groups. Parallelization strategies reflect approaches employed by OpenMP and MPI-based applications developed at Lawrence Livermore National Laboratory and Argonne National Laboratory. The software architecture supports Cartesian, spherical, and cylindrical coordinates used in modeling analogous to simulations by European Space Research and Technology Centre teams.
RADMC-3D has been used to model protoplanetary disks in studies related to ALMA observations, to synthesize images for comparison with surveys from Herschel Space Observatory, and to interpret polarization signatures explored by groups at Max Planck Institute for Solar System Research. Other applications include modeling circumstellar envelopes in investigations linked to European Southern Observatory programs, producing synthetic spectra for stellar atmosphere comparisons relevant to Kepler (spacecraft) follow-up, and generating molecular-line cubes underpinning analyses by teams at Institut de Radioastronomie Millimétrique and National Astronomical Observatory of Japan. The code supports research spanning from early-universe galaxy studies common at Space Telescope Science Institute to compact-object accretion flow modeling pursued at Kavli Institute for Theoretical Physics.
RADMC-3D development has been supported by collaborations among groups at Stockholm University, Uppsala University, Max Planck Institute for Astronomy, and other academic centers. The user community exchanges examples and issues via forums and version-control practices similar to those used by projects hosted on platforms utilized by GitHub, Inc. users, with contributions following contribution models familiar to members of American Astronomical Society meetings and workshops at International Astronomical Union. Educational use and community tutorials mirror outreach efforts performed by institutions like European Southern Observatory and Space Telescope Science Institute.
Installation typically requires a Python (programming language) environment, Fortran compilers akin to those distributed by GNU Project, and libraries comparable to NumPy, SciPy, and FFT packages used in computational astrophysics at Princeton University and University of Chicago. The code runs on platforms common in research groups at National Center for Supercomputing Applications and computing clusters administered at Pawsey Supercomputing Centre and Barcelona Supercomputing Center. Users often employ package management and environment tools inspired by workflows at Anaconda (company) and cluster scheduling systems like those used at Lawrence Berkeley National Laboratory.
Tutorials and example use-cases are provided by educators and researchers affiliated with Uppsala University, Stockholm University, Max Planck Institute for Astronomy, University of Cambridge, and outreach teams at European Southern Observatory. Example workflows demonstrate producing spectral energy distributions consistent with analyses by Harvard–Smithsonian Center for Astrophysics teams, generating synthetic ALMA images following procedures from Leiden Observatory workshops, and performing polarized-scattering calculations like those in studies at University of California, Santa Cruz. Community-created notebooks and scripts echo pedagogical materials distributed at Society of Industrial and Applied Mathematics-hosted events.
Category:Astrophysics software