PHANGS-HST Catalogs for ∼100,000 Star Clusters and Compact Associations in 38 Galaxies. II. Physical Properties from Decision-tree-based Spectral Energy Distribution Fitting of NUV-U-B-V-I Photometry with Categorical Priors Set by Hα Emission, Cluster Morphology, and Other Auxiliary Information
This paper is the second in a series presenting the catalogs and properties of the largest sample to date of ∼100,000 star clusters and compact associations, in 38 spiral galaxies observed by the PHANGS-HST Treasury survey. Here, we present spectral energy distribution (SED) fitting techniques used...
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| author | David A. Thilker Janice C. Lee Bradley C. Whitmore Daniel Maschmann Kiana Henny Rupali Chandar Daniel A. Dale Sinan Deger Médéric Boquien Aida Wofford Leonardo Úbeda Alessandro Razza Ashley T. Barnes Francesco Belfiore Frank Bigiel Kathryn Grasha Brent Groves Hwihyun Kim Ralf S. Klessen Justus Neumann Francesca Pinna M. Jimena Rodríguez Erik Rosolowsky Eva Schinnerer Thomas G. Williams |
| author_facet | David A. Thilker Janice C. Lee Bradley C. Whitmore Daniel Maschmann Kiana Henny Rupali Chandar Daniel A. Dale Sinan Deger Médéric Boquien Aida Wofford Leonardo Úbeda Alessandro Razza Ashley T. Barnes Francesco Belfiore Frank Bigiel Kathryn Grasha Brent Groves Hwihyun Kim Ralf S. Klessen Justus Neumann Francesca Pinna M. Jimena Rodríguez Erik Rosolowsky Eva Schinnerer Thomas G. Williams |
| author_sort | David A. Thilker |
| collection | DOAJ |
| description | This paper is the second in a series presenting the catalogs and properties of the largest sample to date of ∼100,000 star clusters and compact associations, in 38 spiral galaxies observed by the PHANGS-HST Treasury survey. Here, we present spectral energy distribution (SED) fitting techniques used to compute the age, mass, and reddening for each object. Our decision-tree-based strategy incorporates categorical priors on model age, reddening, and metallicity determined from additional observed parameters: localized H α emission, source morphology, and demographic-specific locations in the UBVI color–color diagram. This approach is implemented to mitigate model degeneracies, particularly between young dusty clusters and old clusters with minimal dust, which can have identical optical colors. Results based on H α narrowband imaging from the ground and from Hubble Space Telescope are intercompared, and contrasted with previous SED-fitting efforts. The fraction of the population that is subject to such priors is ∼14%, and of this subset, ∼63% of old globular clusters (GCs) have ages that change by a factor of 10 or more relative to unconstrained fits with single metallicity ( Z _⊙ ) simple stellar population models. The demographics of the population are examined through age–mass and age–reddening diagrams (for individual galaxies as well as aggregated over the sample), and the GC mass function. We demonstrate relationships between cluster age–mass diagrams and properties of parent galaxies (galaxy morphology and location relative to the galaxy main sequence). We outline continuing efforts to improve the inference of physical properties, including the incorporation of JWST infrared photometry and updated synthesis models. |
| format | Article |
| id | doaj-art-b8ed8ce2c0f2433f9fff92f401f86d24 |
| institution | DOAJ |
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| language | English |
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| spelling | doaj-art-b8ed8ce2c0f2433f9fff92f401f86d242025-08-20T02:58:11ZengIOP PublishingThe Astrophysical Journal Supplement Series0067-00492025-01-012801110.3847/1538-4365/addabbPHANGS-HST Catalogs for ∼100,000 Star Clusters and Compact Associations in 38 Galaxies. II. Physical Properties from Decision-tree-based Spectral Energy Distribution Fitting of NUV-U-B-V-I Photometry with Categorical Priors Set by Hα Emission, Cluster Morphology, and Other Auxiliary InformationDavid A. Thilker0https://orcid.org/0000-0002-8528-7340Janice C. Lee1https://orcid.org/0000-0002-2278-9407Bradley C. Whitmore2https://orcid.org/0000-0002-3784-7032Daniel Maschmann3https://orcid.org/0000-0001-6038-9511Kiana Henny4https://orcid.org/0000-0001-7448-1749Rupali Chandar5https://orcid.org/0000-0003-0085-4623Daniel A. Dale6https://orcid.org/0000-0002-5782-9093Sinan Deger7https://orcid.org/0000-0003-1943-723XMédéric Boquien8https://orcid.org/0000-0003-0946-6176Aida Wofford9https://orcid.org/0000-0001-8289-3428Leonardo Úbeda10https://orcid.org/0000-0001-7130-2880Alessandro Razza11https://orcid.org/0000-0001-7876-1713Ashley T. Barnes12https://orcid.org/0000-0003-0410-4504Francesco Belfiore13https://orcid.org/0000-0002-2545-5752Frank Bigiel14https://orcid.org/0000-0003-0166-9745Kathryn Grasha15https://orcid.org/0000-0002-3247-5321Brent Groves16https://orcid.org/0000-0002-9768-0246Hwihyun Kim17https://orcid.org/0000-0003-4770-688XRalf S. Klessen18https://orcid.org/0000-0002-0560-3172Justus Neumann19https://orcid.org/0000-0002-3289-8914Francesca Pinna20https://orcid.org/0000-0001-5965-3530M. Jimena Rodríguez21https://orcid.org/0000-0002-0579-6613Erik Rosolowsky22https://orcid.org/0000-0002-5204-2259Eva Schinnerer23https://orcid.org/0000-0002-3933-7677Thomas G. Williams24https://orcid.org/0000-0002-0012-2142Department of Physics and Astronomy, The Johns Hopkins University , Baltimore, MD 21218, USA ; dthilker@jhu.eduSpace Telescope Science Institute , 3700 San Martin Drive, Baltimore, MD 21218, USA; Steward Observatory, University of Arizona , Tucson, AZ 85721, USASpace Telescope Science Institute , 3700 San Martin Drive, Baltimore, MD 21218, USASpace Telescope Science Institute , 3700 San Martin Drive, Baltimore, MD 21218, USA; Steward Observatory, University of Arizona , Tucson, AZ 85721, USADepartment of Physics and Astronomy, University of Wyoming , Laramie, WY 82071, USAUniversity of Toledo , 2801 W. Bancroft Street, Mail Stop 111, Toledo, OH 43606, USADepartment of Physics and Astronomy, University of Wyoming , Laramie, WY 82071, USAInstitute of Astronomy, University of Cambridge , Madingley Road, Cambridge CB3 0HA, UK; Kavli Institute for Cosmology Cambridge , Madingley Road, Cambridge CB3 0HA, UKUniversité Côte d’Azur , Observatoire de la Côte d’Azur, CNRS, Laboratoire Lagrange, 06000, Nice, FranceInstituto de Astronomía, Universidad Nacional Autónoma de México , Unidad Académica en Ensenada, Km 103 Carr. TijuanaEnsenada, Ensenada, B.C., C.P. 22860, Mexico; Department of Astronomy and Astrophysics, University of California , San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USASpace Telescope Science Institute , 3700 San Martin Drive, Baltimore, MD 21218, USADepartamento de Astronomía, Universidad de Chile , Camino del Observatorio 1515, Las Condes, Santiago, ChileEuropean Southern Observatory , Karl-Schwarzschild Straße 2, D-85748 Garching bei München, GermanyINAF–Osservatorio Astrofisico di Arcetri , Largo E. Fermi 5, I-50157, Firenze, ItalyArgelander-Institut für Astronomie, Universität Bonn , Auf dem Hügel 71, 53121 Bonn, GermanyResearch School of Astronomy and Astrophysics, Australian National University , Canberra, ACT 2611, Australia; ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D) , AustraliaInternational Centre for Radio Astronomy Research, University of Western Australia , 35 Stirling Highway, Crawley, WA 6009, AustraliaGemini Observatory/NSF’s NOIRLab , 950 N. Cherry Avenue, Tucson, AZ, 85719, USAUniversität Heidelberg , Zentrum für Astronomie, Institut für Theoretische Astrophysik, Albert-Ueberle-Str 2, D-69120 Heidelberg, Germany; Universität Heidelberg , Interdisziplinäres Zentrum für Wissenschaftliches Rechnen, Im Neuenheimer Feld 205, D-69120 Heidelberg, GermanyMax-Planck-Institut für Astronomie , Königstuhl 17, D-69117, Heidelberg, GermanyMax-Planck-Institut für Astronomie , Königstuhl 17, D-69117, Heidelberg, Germany; Instituto de Astrofísica de Canarias , C/ Vía Láctea s/n, E-38205, La Laguna, Spain; Departamento de Astrofísica, Universidad de La Laguna , Av. del Astrofísico Francisco Sánchez s/n, E-38206, La Laguna, SpainSpace Telescope Science Institute , 3700 San Martin Drive, Baltimore, MD 21218, USA; Steward Observatory, University of Arizona , Tucson, AZ 85721, USADepartment of Physics, University of Alberta , Edmonton, AB T6G 2E1, CanadaMax-Planck-Institut für Astronomie , Königstuhl 17, D-69117, Heidelberg, GermanySub-department of Astrophysics, Department of Physics, University of Oxford , Keble Road, Oxford OX1 3RH, UKThis paper is the second in a series presenting the catalogs and properties of the largest sample to date of ∼100,000 star clusters and compact associations, in 38 spiral galaxies observed by the PHANGS-HST Treasury survey. Here, we present spectral energy distribution (SED) fitting techniques used to compute the age, mass, and reddening for each object. Our decision-tree-based strategy incorporates categorical priors on model age, reddening, and metallicity determined from additional observed parameters: localized H α emission, source morphology, and demographic-specific locations in the UBVI color–color diagram. This approach is implemented to mitigate model degeneracies, particularly between young dusty clusters and old clusters with minimal dust, which can have identical optical colors. Results based on H α narrowband imaging from the ground and from Hubble Space Telescope are intercompared, and contrasted with previous SED-fitting efforts. The fraction of the population that is subject to such priors is ∼14%, and of this subset, ∼63% of old globular clusters (GCs) have ages that change by a factor of 10 or more relative to unconstrained fits with single metallicity ( Z _⊙ ) simple stellar population models. The demographics of the population are examined through age–mass and age–reddening diagrams (for individual galaxies as well as aggregated over the sample), and the GC mass function. We demonstrate relationships between cluster age–mass diagrams and properties of parent galaxies (galaxy morphology and location relative to the galaxy main sequence). We outline continuing efforts to improve the inference of physical properties, including the incorporation of JWST infrared photometry and updated synthesis models.https://doi.org/10.3847/1538-4365/addabbOpen star clustersGlobular star clustersGalaxiesGalaxy evolutionSpiral galaxiesInterstellar reddening |
| spellingShingle | David A. Thilker Janice C. Lee Bradley C. Whitmore Daniel Maschmann Kiana Henny Rupali Chandar Daniel A. Dale Sinan Deger Médéric Boquien Aida Wofford Leonardo Úbeda Alessandro Razza Ashley T. Barnes Francesco Belfiore Frank Bigiel Kathryn Grasha Brent Groves Hwihyun Kim Ralf S. Klessen Justus Neumann Francesca Pinna M. Jimena Rodríguez Erik Rosolowsky Eva Schinnerer Thomas G. Williams PHANGS-HST Catalogs for ∼100,000 Star Clusters and Compact Associations in 38 Galaxies. II. Physical Properties from Decision-tree-based Spectral Energy Distribution Fitting of NUV-U-B-V-I Photometry with Categorical Priors Set by Hα Emission, Cluster Morphology, and Other Auxiliary Information The Astrophysical Journal Supplement Series Open star clusters Globular star clusters Galaxies Galaxy evolution Spiral galaxies Interstellar reddening |
| title | PHANGS-HST Catalogs for ∼100,000 Star Clusters and Compact Associations in 38 Galaxies. II. Physical Properties from Decision-tree-based Spectral Energy Distribution Fitting of NUV-U-B-V-I Photometry with Categorical Priors Set by Hα Emission, Cluster Morphology, and Other Auxiliary Information |
| title_full | PHANGS-HST Catalogs for ∼100,000 Star Clusters and Compact Associations in 38 Galaxies. II. Physical Properties from Decision-tree-based Spectral Energy Distribution Fitting of NUV-U-B-V-I Photometry with Categorical Priors Set by Hα Emission, Cluster Morphology, and Other Auxiliary Information |
| title_fullStr | PHANGS-HST Catalogs for ∼100,000 Star Clusters and Compact Associations in 38 Galaxies. II. Physical Properties from Decision-tree-based Spectral Energy Distribution Fitting of NUV-U-B-V-I Photometry with Categorical Priors Set by Hα Emission, Cluster Morphology, and Other Auxiliary Information |
| title_full_unstemmed | PHANGS-HST Catalogs for ∼100,000 Star Clusters and Compact Associations in 38 Galaxies. II. Physical Properties from Decision-tree-based Spectral Energy Distribution Fitting of NUV-U-B-V-I Photometry with Categorical Priors Set by Hα Emission, Cluster Morphology, and Other Auxiliary Information |
| title_short | PHANGS-HST Catalogs for ∼100,000 Star Clusters and Compact Associations in 38 Galaxies. II. Physical Properties from Decision-tree-based Spectral Energy Distribution Fitting of NUV-U-B-V-I Photometry with Categorical Priors Set by Hα Emission, Cluster Morphology, and Other Auxiliary Information |
| title_sort | phangs hst catalogs for ∼100 000 star clusters and compact associations in 38 galaxies ii physical properties from decision tree based spectral energy distribution fitting of nuv u b v i photometry with categorical priors set by hα emission cluster morphology and other auxiliary information |
| topic | Open star clusters Globular star clusters Galaxies Galaxy evolution Spiral galaxies Interstellar reddening |
| url | https://doi.org/10.3847/1538-4365/addabb |
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