powderday: Dust Radiative Transfer for Galaxy Simulations
We present powderday (available at https://github.com/dnarayanan/powderday), a flexible, fast, open-source dust radiative transfer package designed to interface with both idealized and cosmological galaxy formation simulations. powderday builds on fsps stellar population synthesis models, and hyperi...
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creator | Narayanan, Desika Turk, Matthew J. Robitaille, Thomas Kelly, Ashley J. McClellan, B. Connor Sharma, Ray S Garg, Prerak Abruzzo, Matthew Choi, Ena Conroy, Charlie Johnson, Benjamin D. Kimock, Benjamin Li, Qi Lovell, Christopher C. Lower, Sidney Privon, George C. Roberts, Jonathan Sethuram, Snigdaa Snyder, Gregory F. Thompson, Robert Wise, John H. |
description | We present powderday (available at https://github.com/dnarayanan/powderday), a flexible, fast, open-source dust radiative transfer package designed to interface with both idealized and cosmological galaxy formation simulations. powderday builds on fsps stellar population synthesis models, and hyperion dust radiative transfer, and employs yt to interface between different software packages. We include our stellar population synthesis modeling on the fly, allowing significant flexibility in the assumed stellar physics and nebular line emission. The dust content follows either simple observationally motivated prescriptions (i.e., constant dust-to-metals ratios, or dust-to-gas ratios that vary with metallicity), direct modeling from galaxy formation simulations that include dust physics, as well as a novel approach that includes the dust content via learning-based algorithms from the simba cosmological galaxy formation simulation. Active galactic nuclei (AGNs) can additionally be included via a range of prescriptions. The output of these models are broadband (912 -1 mm) spectral energy distributions (SEDs), as well as filter-convolved monochromatic images. powderday is designed to eliminate last-mile efforts by researchers that employ different hydrodynamic galaxy formation models and seamlessly interfaces with gizmo, arepo, gasoline, changa, and enzo. We demonstrate the capabilities of the code via three applications: a model for the star formation rate-infrared luminosity relation in galaxies (including the impact of AGNs), the impact of circumstellar dust around AGB stars on the mid-infrared emission from galaxy SEDs, and the impact of galaxy inclination angle on dust attenuation laws. |
doi_str_mv | 10.3847/1538-4365/abc487 |
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Connor ; Sharma, Ray S ; Garg, Prerak ; Abruzzo, Matthew ; Choi, Ena ; Conroy, Charlie ; Johnson, Benjamin D. ; Kimock, Benjamin ; Li, Qi ; Lovell, Christopher C. ; Lower, Sidney ; Privon, George C. ; Roberts, Jonathan ; Sethuram, Snigdaa ; Snyder, Gregory F. ; Thompson, Robert ; Wise, John H.</creator><creatorcontrib>Narayanan, Desika ; Turk, Matthew J. ; Robitaille, Thomas ; Kelly, Ashley J. ; McClellan, B. Connor ; Sharma, Ray S ; Garg, Prerak ; Abruzzo, Matthew ; Choi, Ena ; Conroy, Charlie ; Johnson, Benjamin D. ; Kimock, Benjamin ; Li, Qi ; Lovell, Christopher C. ; Lower, Sidney ; Privon, George C. ; Roberts, Jonathan ; Sethuram, Snigdaa ; Snyder, Gregory F. ; Thompson, Robert ; Wise, John H.</creatorcontrib><description>We present powderday (available at https://github.com/dnarayanan/powderday), a flexible, fast, open-source dust radiative transfer package designed to interface with both idealized and cosmological galaxy formation simulations. powderday builds on fsps stellar population synthesis models, and hyperion dust radiative transfer, and employs yt to interface between different software packages. We include our stellar population synthesis modeling on the fly, allowing significant flexibility in the assumed stellar physics and nebular line emission. The dust content follows either simple observationally motivated prescriptions (i.e., constant dust-to-metals ratios, or dust-to-gas ratios that vary with metallicity), direct modeling from galaxy formation simulations that include dust physics, as well as a novel approach that includes the dust content via learning-based algorithms from the simba cosmological galaxy formation simulation. Active galactic nuclei (AGNs) can additionally be included via a range of prescriptions. The output of these models are broadband (912 -1 mm) spectral energy distributions (SEDs), as well as filter-convolved monochromatic images. powderday is designed to eliminate last-mile efforts by researchers that employ different hydrodynamic galaxy formation models and seamlessly interfaces with gizmo, arepo, gasoline, changa, and enzo. We demonstrate the capabilities of the code via three applications: a model for the star formation rate-infrared luminosity relation in galaxies (including the impact of AGNs), the impact of circumstellar dust around AGB stars on the mid-infrared emission from galaxy SEDs, and the impact of galaxy inclination angle on dust attenuation laws.</description><identifier>ISSN: 0067-0049</identifier><identifier>EISSN: 1538-4365</identifier><identifier>DOI: 10.3847/1538-4365/abc487</identifier><language>eng</language><publisher>Saskatoon: The American Astronomical Society</publisher><subject>Active galactic nuclei ; Algorithms ; Astronomical models ; Astronomy software ; Asymptotic giant branch stars ; Attenuation ; Broadband ; Circumstellar dust ; Cosmic dust ; Dust ; Emission ; Galactic evolution ; Galaxies ; Galaxy evolution ; Galaxy luminosities ; Gasoline ; Image filters ; Inclination angle ; Infrared emissions ; Luminosity ; Machine learning ; Metallicity ; Open source software ; Physics ; Radiative transfer ; Radiative transfer simulations ; Simulation ; Source code ; Star & galaxy formation ; Star formation ; Star formation rate ; Stellar models ; Stellar physics ; Synthesis</subject><ispartof>The Astrophysical journal. Supplement series, 2021-01, Vol.252 (1), p.12</ispartof><rights>2021. The American Astronomical Society. All rights reserved.</rights><rights>Copyright IOP Publishing Jan 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c446t-94851f86aaec12686f6c32b06cfde02b119c79bd5717f023733ae8a2867d4a863</citedby><cites>FETCH-LOGICAL-c446t-94851f86aaec12686f6c32b06cfde02b119c79bd5717f023733ae8a2867d4a863</cites><orcidid>0000-0002-9280-7594 ; 0000-0002-1590-8551 ; 0000-0002-5294-0198 ; 0000-0002-6040-8281 ; 0000-0002-8131-6378 ; 0000-0002-3160-7679 ; 0000-0003-3474-1125 ; 0000-0002-8642-1329 ; 0000-0003-4422-8595 ; 0000-0002-4226-304X ; 0000-0003-1173-8847 ; 0000-0002-7064-4309 ; 0000-0001-8350-4535 ; 0000-0003-3850-4469 ; 0000-0001-7964-5933</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.3847/1538-4365/abc487/pdf$$EPDF$$P50$$Giop$$H</linktopdf><link.rule.ids>314,780,784,27924,27925,38868,38890,53840,53867</link.rule.ids><linktorsrc>$$Uhttps://iopscience.iop.org/article/10.3847/1538-4365/abc487$$EView_record_in_IOP_Publishing$$FView_record_in_$$GIOP_Publishing</linktorsrc></links><search><creatorcontrib>Narayanan, Desika</creatorcontrib><creatorcontrib>Turk, Matthew J.</creatorcontrib><creatorcontrib>Robitaille, Thomas</creatorcontrib><creatorcontrib>Kelly, Ashley J.</creatorcontrib><creatorcontrib>McClellan, B. Connor</creatorcontrib><creatorcontrib>Sharma, Ray S</creatorcontrib><creatorcontrib>Garg, Prerak</creatorcontrib><creatorcontrib>Abruzzo, Matthew</creatorcontrib><creatorcontrib>Choi, Ena</creatorcontrib><creatorcontrib>Conroy, Charlie</creatorcontrib><creatorcontrib>Johnson, Benjamin D.</creatorcontrib><creatorcontrib>Kimock, Benjamin</creatorcontrib><creatorcontrib>Li, Qi</creatorcontrib><creatorcontrib>Lovell, Christopher C.</creatorcontrib><creatorcontrib>Lower, Sidney</creatorcontrib><creatorcontrib>Privon, George C.</creatorcontrib><creatorcontrib>Roberts, Jonathan</creatorcontrib><creatorcontrib>Sethuram, Snigdaa</creatorcontrib><creatorcontrib>Snyder, Gregory F.</creatorcontrib><creatorcontrib>Thompson, Robert</creatorcontrib><creatorcontrib>Wise, John H.</creatorcontrib><title>powderday: Dust Radiative Transfer for Galaxy Simulations</title><title>The Astrophysical journal. Supplement series</title><addtitle>APJS</addtitle><addtitle>Astrophys. J. Suppl</addtitle><description>We present powderday (available at https://github.com/dnarayanan/powderday), a flexible, fast, open-source dust radiative transfer package designed to interface with both idealized and cosmological galaxy formation simulations. powderday builds on fsps stellar population synthesis models, and hyperion dust radiative transfer, and employs yt to interface between different software packages. We include our stellar population synthesis modeling on the fly, allowing significant flexibility in the assumed stellar physics and nebular line emission. The dust content follows either simple observationally motivated prescriptions (i.e., constant dust-to-metals ratios, or dust-to-gas ratios that vary with metallicity), direct modeling from galaxy formation simulations that include dust physics, as well as a novel approach that includes the dust content via learning-based algorithms from the simba cosmological galaxy formation simulation. Active galactic nuclei (AGNs) can additionally be included via a range of prescriptions. The output of these models are broadband (912 -1 mm) spectral energy distributions (SEDs), as well as filter-convolved monochromatic images. powderday is designed to eliminate last-mile efforts by researchers that employ different hydrodynamic galaxy formation models and seamlessly interfaces with gizmo, arepo, gasoline, changa, and enzo. 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Connor ; Sharma, Ray S ; Garg, Prerak ; Abruzzo, Matthew ; Choi, Ena ; Conroy, Charlie ; Johnson, Benjamin D. ; Kimock, Benjamin ; Li, Qi ; Lovell, Christopher C. ; Lower, Sidney ; Privon, George C. ; Roberts, Jonathan ; Sethuram, Snigdaa ; Snyder, Gregory F. ; Thompson, Robert ; Wise, John H.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c446t-94851f86aaec12686f6c32b06cfde02b119c79bd5717f023733ae8a2867d4a863</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Active galactic nuclei</topic><topic>Algorithms</topic><topic>Astronomical models</topic><topic>Astronomy software</topic><topic>Asymptotic giant branch stars</topic><topic>Attenuation</topic><topic>Broadband</topic><topic>Circumstellar dust</topic><topic>Cosmic dust</topic><topic>Dust</topic><topic>Emission</topic><topic>Galactic evolution</topic><topic>Galaxies</topic><topic>Galaxy evolution</topic><topic>Galaxy luminosities</topic><topic>Gasoline</topic><topic>Image filters</topic><topic>Inclination angle</topic><topic>Infrared emissions</topic><topic>Luminosity</topic><topic>Machine learning</topic><topic>Metallicity</topic><topic>Open source software</topic><topic>Physics</topic><topic>Radiative transfer</topic><topic>Radiative transfer simulations</topic><topic>Simulation</topic><topic>Source code</topic><topic>Star & galaxy formation</topic><topic>Star formation</topic><topic>Star formation rate</topic><topic>Stellar models</topic><topic>Stellar physics</topic><topic>Synthesis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Narayanan, Desika</creatorcontrib><creatorcontrib>Turk, Matthew J.</creatorcontrib><creatorcontrib>Robitaille, Thomas</creatorcontrib><creatorcontrib>Kelly, Ashley J.</creatorcontrib><creatorcontrib>McClellan, B. 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The dust content follows either simple observationally motivated prescriptions (i.e., constant dust-to-metals ratios, or dust-to-gas ratios that vary with metallicity), direct modeling from galaxy formation simulations that include dust physics, as well as a novel approach that includes the dust content via learning-based algorithms from the simba cosmological galaxy formation simulation. Active galactic nuclei (AGNs) can additionally be included via a range of prescriptions. The output of these models are broadband (912 -1 mm) spectral energy distributions (SEDs), as well as filter-convolved monochromatic images. powderday is designed to eliminate last-mile efforts by researchers that employ different hydrodynamic galaxy formation models and seamlessly interfaces with gizmo, arepo, gasoline, changa, and enzo. 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subjects | Active galactic nuclei Algorithms Astronomical models Astronomy software Asymptotic giant branch stars Attenuation Broadband Circumstellar dust Cosmic dust Dust Emission Galactic evolution Galaxies Galaxy evolution Galaxy luminosities Gasoline Image filters Inclination angle Infrared emissions Luminosity Machine learning Metallicity Open source software Physics Radiative transfer Radiative transfer simulations Simulation Source code Star & galaxy formation Star formation Star formation rate Stellar models Stellar physics Synthesis |
title | powderday: Dust Radiative Transfer for Galaxy Simulations |
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