PhotoD with LSST: Stellar Photometric Distances Out to the Edge of the Galaxy
As demonstrated with the Sloan Digital Sky Survey (SDSS), Pan-STARRS, and most recently with Gaia data, broadband near-UV to near-IR stellar photometry can be used to estimate distance, metallicity, and interstellar dust extinction along the line of sight for stars in the Galaxy. Anticipating photom...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2025-01-01
|
| Series: | The Astronomical Journal |
| Subjects: | |
| Online Access: | https://doi.org/10.3847/1538-3881/ada3c2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832542179210297344 |
|---|---|
| author | Lovro Palaversa Željko Ivezić Neven Caplar Karlo Mrakovčić Bob Abel Oleksandra Razim Filip Matković Connor Yablonski Toni Šarić Tomislav Jurkić Sandro Campos Melissa DeLucchi Derek Jones Konstantin Malanchev Alex I. Malz Sean McGuire Mario Jurić |
| author_facet | Lovro Palaversa Željko Ivezić Neven Caplar Karlo Mrakovčić Bob Abel Oleksandra Razim Filip Matković Connor Yablonski Toni Šarić Tomislav Jurkić Sandro Campos Melissa DeLucchi Derek Jones Konstantin Malanchev Alex I. Malz Sean McGuire Mario Jurić |
| author_sort | Lovro Palaversa |
| collection | DOAJ |
| description | As demonstrated with the Sloan Digital Sky Survey (SDSS), Pan-STARRS, and most recently with Gaia data, broadband near-UV to near-IR stellar photometry can be used to estimate distance, metallicity, and interstellar dust extinction along the line of sight for stars in the Galaxy. Anticipating photometric catalogs with tens of billions of stars from Rubin's Legacy Survey of Space and Time (LSST), we present a Bayesian model and pipeline that build on previous work and can handle LSST-sized datasets. Likelihood computations utilize MIST/Dartmouth isochrones and priors are derived from TRILEGAL-based simulated LSST catalogs from P. Dal Tio et al. The computation speed is about 10 ms per star on a single core for both optimized grid search and Markov Chain Monte Carlo methods; we show in a companion paper by K. Mrakovčić et al. how to utilize neural networks to accelerate this performance by up to an order of magnitude. We validate our pipeline, named PhotoD (in analogy with photo- z , photometric redshifts of galaxies) using both simulated catalogs and SDSS, DECam, and Gaia photometry. We intend to make LSST-based value-added PhotoD catalogs publicly available via the Rubin Science Platform with every LSST data release. |
| format | Article |
| id | doaj-art-7a3d1a2b3e44417b98b6086ecef378ed |
| institution | Kabale University |
| issn | 1538-3881 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | The Astronomical Journal |
| spelling | doaj-art-7a3d1a2b3e44417b98b6086ecef378ed2025-02-04T08:25:50ZengIOP PublishingThe Astronomical Journal1538-38812025-01-01169311910.3847/1538-3881/ada3c2PhotoD with LSST: Stellar Photometric Distances Out to the Edge of the GalaxyLovro Palaversa0https://orcid.org/0000-0003-3710-0331Željko Ivezić1https://orcid.org/0000-0001-5250-2633Neven Caplar2https://orcid.org/0000-0003-3287-5250Karlo Mrakovčić3https://orcid.org/0009-0009-8154-3827Bob Abel4https://orcid.org/0000-0001-8418-3083Oleksandra Razim5https://orcid.org/0000-0002-3045-0446Filip Matković6https://orcid.org/0009-0002-5858-585XConnor Yablonski7https://orcid.org/0009-0000-0990-8339Toni Šarić8https://orcid.org/0000-0001-8731-8369Tomislav Jurkić9https://orcid.org/0000-0002-4993-2939Sandro Campos10https://orcid.org/0009-0007-9870-9032Melissa DeLucchi11https://orcid.org/0000-0002-1074-2900Derek Jones12https://orcid.org/0009-0006-2411-723XKonstantin Malanchev13https://orcid.org/0000-0001-7179-7406Alex I. Malz14https://orcid.org/0000-0002-8676-1622Sean McGuire15https://orcid.org/0009-0005-8764-2608Mario Jurić16https://orcid.org/0000-0003-1996-9252Ruđer Bošković Institute , Bijenička cesta 54, 10000 Zagreb, CroatiaDIRAC Institute and the Department of Astronomy, University of Washington , 3910 15th Avenue NE, Seattle, WA 98195, USADIRAC Institute and the Department of Astronomy, University of Washington , 3910 15th Avenue NE, Seattle, WA 98195, USAFaculty of Physics, University of Rijeka , Radmile Matejčić 2, 51000 Rijeka, CroatiaOlympic College , 1600 Chester Avenue, Bremerton, WA 98337, USA; DiRAC Institute, University of Washington , Box 351580, Seattle, WA 98195, USARuđer Bošković Institute , Bijenička cesta 54, 10000 Zagreb, CroatiaHvar Observatory, Faculty of Geodesy, University of Zagreb , Kačićeva 26, 10000 Zagreb, CroatiaDIRAC Institute and the Department of Astronomy, University of Washington , 3910 15th Avenue NE, Seattle, WA 98195, USAUniversity of Split—FESB , R. Boškovića 32, 21000 Split, CroatiaFaculty of Physics, University of Rijeka , Radmile Matejčić 2, 51000 Rijeka, CroatiaThe McWilliams Center for Cosmology & Astrophysics, Department of Physics, Carnegie Mellon University , Pittsburgh, PA 15213, USAThe McWilliams Center for Cosmology & Astrophysics, Department of Physics, Carnegie Mellon University , Pittsburgh, PA 15213, USADIRAC Institute and the Department of Astronomy, University of Washington , 3910 15th Avenue NE, Seattle, WA 98195, USAThe McWilliams Center for Cosmology & Astrophysics, Department of Physics, Carnegie Mellon University , Pittsburgh, PA 15213, USAThe McWilliams Center for Cosmology & Astrophysics, Department of Physics, Carnegie Mellon University , Pittsburgh, PA 15213, USAThe McWilliams Center for Cosmology & Astrophysics, Department of Physics, Carnegie Mellon University , Pittsburgh, PA 15213, USADIRAC Institute and the Department of Astronomy, University of Washington , 3910 15th Avenue NE, Seattle, WA 98195, USAAs demonstrated with the Sloan Digital Sky Survey (SDSS), Pan-STARRS, and most recently with Gaia data, broadband near-UV to near-IR stellar photometry can be used to estimate distance, metallicity, and interstellar dust extinction along the line of sight for stars in the Galaxy. Anticipating photometric catalogs with tens of billions of stars from Rubin's Legacy Survey of Space and Time (LSST), we present a Bayesian model and pipeline that build on previous work and can handle LSST-sized datasets. Likelihood computations utilize MIST/Dartmouth isochrones and priors are derived from TRILEGAL-based simulated LSST catalogs from P. Dal Tio et al. The computation speed is about 10 ms per star on a single core for both optimized grid search and Markov Chain Monte Carlo methods; we show in a companion paper by K. Mrakovčić et al. how to utilize neural networks to accelerate this performance by up to an order of magnitude. We validate our pipeline, named PhotoD (in analogy with photo- z , photometric redshifts of galaxies) using both simulated catalogs and SDSS, DECam, and Gaia photometry. We intend to make LSST-based value-added PhotoD catalogs publicly available via the Rubin Science Platform with every LSST data release.https://doi.org/10.3847/1538-3881/ada3c2Distance measureDistance indicatorsStellar distanceExtinctionInterstellar extinctionReddening law |
| spellingShingle | Lovro Palaversa Željko Ivezić Neven Caplar Karlo Mrakovčić Bob Abel Oleksandra Razim Filip Matković Connor Yablonski Toni Šarić Tomislav Jurkić Sandro Campos Melissa DeLucchi Derek Jones Konstantin Malanchev Alex I. Malz Sean McGuire Mario Jurić PhotoD with LSST: Stellar Photometric Distances Out to the Edge of the Galaxy The Astronomical Journal Distance measure Distance indicators Stellar distance Extinction Interstellar extinction Reddening law |
| title | PhotoD with LSST: Stellar Photometric Distances Out to the Edge of the Galaxy |
| title_full | PhotoD with LSST: Stellar Photometric Distances Out to the Edge of the Galaxy |
| title_fullStr | PhotoD with LSST: Stellar Photometric Distances Out to the Edge of the Galaxy |
| title_full_unstemmed | PhotoD with LSST: Stellar Photometric Distances Out to the Edge of the Galaxy |
| title_short | PhotoD with LSST: Stellar Photometric Distances Out to the Edge of the Galaxy |
| title_sort | photod with lsst stellar photometric distances out to the edge of the galaxy |
| topic | Distance measure Distance indicators Stellar distance Extinction Interstellar extinction Reddening law |
| url | https://doi.org/10.3847/1538-3881/ada3c2 |
| work_keys_str_mv | AT lovropalaversa photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT zeljkoivezic photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT nevencaplar photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT karlomrakovcic photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT bobabel photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT oleksandrarazim photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT filipmatkovic photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT connoryablonski photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT tonisaric photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT tomislavjurkic photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT sandrocampos photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT melissadelucchi photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT derekjones photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT konstantinmalanchev photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT aleximalz photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT seanmcguire photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy AT mariojuric photodwithlsststellarphotometricdistancesouttotheedgeofthegalaxy |