A1 Refereed original research article in a scientific journal
The Complete Spitzer Survey of Stellar Structure in Galaxies (CS4G)
Authors: Sanchez-Alarcón, P. M.; Salo, H.; Knapen, J. H.; Comerón, S.; Román, J.; Watkins, A. E.; Buta, R. J.; Laine, S.; Falcón-Ramirez, J. M.; Anetjärvi, M.; Athanassoula, E.; Bosma, A.; Gadotti, D. A.; Hinz, J. L.; Ho, L. C.; Holwerda, B. W.; Janz, J.; Kim, T.; Koda, J.; Laine, J.; Laurikainen, E.; Madore, B. F.; Menéndez-Delmestre, K.; Peletier, R. F.; Querejeta, M.; Ruokanen, A.; Sheth, K.; Zaritsky, D.
Publisher: EDP SCIENCES S A
Publishing place: LES ULIS CEDEX A
Publication year: 2025
Journal: Astronomy and Astrophysics
Journal name in source: ASTRONOMY & ASTROPHYSICS
Journal acronym: ASTRON ASTROPHYS
Article number: A38
Volume: 697
Number of pages: 18
ISSN: 0004-6361
eISSN: 1432-0746
DOI: https://doi.org/10.1051/0004-6361/202451641
Web address : https://doi.org/10.1051/0004-6361/202451641
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/498708578
Context. The Spitzer Survey of Stellar Structure in Galaxies (S4G), together with its Early Type Galaxy (ETG) extension, stands as the most extensive dataset of deep uniform mid-infrared (mid-IR; 3.6 and 4.5 μm) imaging for a sample of 2817 nearby (d < 40 Mpc) galaxies. However, the velocity criterion used to select the original sample results in an additional 422 galaxies without H I detection that should have been included in the S4G on the basis of their optical recession velocities.
Aims. In order to create a complete magnitude-, size-, and volume-limited sample of nearby galaxies, we collected 3.6 μm and i-band images using archival data from different surveys and complemented it with new observations for the missing galaxies. Since most, but not all, of these galaxies have a Hubble type in Hyperleda THL > 0, we denote the sample of these additional galaxies as disc galaxy (DG) extension. We present the Complete Spitzer Survey of Stellar Structure in Galaxies (CS4G), encompassing a sample of 3239 galaxies (S4G+ETG+DG) with consistent imaging, surface brightness profiles, photometric parameters, and revised morphological classification.
Methods. Following the original strategy of the S4G survey, we produced masks, surface brightness profiles, and curves of growth using masked 3.6 μm and i-band images. From these profiles, we derived the integrated quantities, including total magnitude, stellar mass, concentration parameter, and galaxy size, converting between optical i-band and 3.6 μm. We also re-measured these parameters for the S4G and ETG to create a homogenous sample. We present new morphologically revised T-types, and we showcase mid-IR scaling relations for the stellar mass, galaxy size, concentration index, and morphological type.
Results. Our new masking procedure increases the number of pixels masked out by a factor of five, improving the masking of fainter regions over previous S4G data. Our photometric parameters from i-band imaging yield measurements consistent with the original sample (S4G) and its ETG extension in the 3.6 μm band. The new DG extension consists of galaxies with a wide morphological range (−5 < THL < 10) and a mass range of 6 < log(M⋆/M⊙) < 11. The galaxies in the DG sample have an average mass of log(M⋆/M⊙) = 9.21, an average galaxy isophotal radius at 25.5 mag arcsec−2 of R25.5 = 7.1 kpc, and an average concentration index of C82 = 2.92.
Conclusions. We completed the S4G sample by incorporating 422 galaxies into the original dataset. The new galaxies constitute 15% of the total previous sample (S4G+ETG), but in the lower-mass range (M⋆ < 109 M⊙), and the disc galaxy extension increases the sample by 36%. The CS4G includes at least 99.94% of the complete sample of nearby galaxies, meeting the original selection criteria based on a comparison with the NED database. We make the images and surface brightness profiles available to the community together with the conjunct catalogue of the whole CS4G dataset with consistent photometric measurements for 3239 galaxies. The CS4G will enable a wide set of investigations into galaxy structure and evolution, and it will complement the optical, near-IR, and mid-IR imaging that will obtained in the coming years with Euclid, Rubin, Roman, and other research projects.
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Funding information in the publication:
This work is based in part on observations made with the Spitzer Space Telescope, which was operated by the Jet Propulsion Laboratory, California Institute of Technology under a contract with NASA. Based on observations collected at the European Organisation for Astronomical Research in the southern hemisphere under ESO programme 0103.B-0586(A). Based on observations made with the Liverpool Telescope operated on the island of La Palma by Liverpool John Moores University in the Spanish Observatorio del Roque de los Muchachos of the Instituto de Astrofisica de Canarias with financial support from the UK Science and Technology Facilities Council. We acknowledge support from the Agencia Estatal de Investigación del Ministerio de Ciencia, Innovación y Universidades (MCIU/AEI) under the grants “The structure and evolution of galaxies and their outer regions” and the European Regional Development Fund (ERDF) with references PID2019-105602GBI00/10.13039/501100011033 and PID2022-136505NB-I00/10.13039/501100011033. Co-funded by the European Union (MSCA Doctoral Network EDUCADO, GA 101119830 and Widening Participation, ExGal-Twin, GA 101158446). SC acknowledges funding from the State Research Agency (AEI) of the Spanish Ministry of Science, Innovation, and Universities under the grant “The relic galaxy NGC 1277 as a key to understanding massive galaxies at cosmic noon” with reference PID2023-149139NB-I00. J.R. acknowledges financial support from the Spanish Ministry of Science and Innovation through the project PID2022-138896NB-C55. AEW acknowledges support from the STFC [grant number ST/X001318/1]. This work was authored by an employee of Caltech/IPAC under contract No. 80GSFC21R0032 with the National Aeronautics and Space Administration. LCH was supported by the National Science Foundation of China (11991052, 12233001), the National Key R&D Program of China (2022YFF0503401), and the China Manned Space Project (CMS-CSST-2021-A04, CMS-CSST-2021-A06). TK acknowledges support from the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. RS-2023-00240212) and the NRF grant funded by the Korean government (MSIT) (No. 2022R1A4A3031306). EA and AB gratefully acknowledge financial support from the CNES (Centre National d’Études Spatiales, France). DAG was supported by STFC grants ST/T000244/1 and ST/X001075/1. JK acknowledges support from NSF through grant AST-2006600. We acknowledge the usage of the HyperLeda database (http://leda.univ-lyon1.fr). This research has made use of the NASA/IPAC Extragalactic Database (NED), which is operated by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. This research has made use of the SIMBAD database, operated at CDS, Strasbourg, France. Funding for the Sloan Digital Sky Survey V has been provided by the Alfred P. Sloan Foundation, the Heising–Simons Foundation, the National Science Foundation, and the Participating Institutions. SDSS acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. SDSS telescopes are located at Apache Point Observatory, funded by the Astrophysical Research Consortium and operated by New Mexico State University, and at Las Campanas Observatory, operated by the Carnegie Institution for Science. The SDSS web site is www.sdss.org. SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration, including Caltech, The Carnegie Institution for Science, Chilean National Time Allocation Committee (CNTAC) ratified researchers, The Flatiron Institute, the Gotham Participation Group, Harvard University, Heidelberg University, The Johns Hopkins University, L’Ecole polytechnique fédérale de Lausanne (EPFL), Leibniz-Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), MaxPlanck-Institut für Extraterrestrische Physik (MPE), Nanjing University, National Astronomical Observatories of China (NAOC), New Mexico State University, The Ohio State University, Pennsylvania State University, Smithsonian Astrophysical Observatory, Space Telescope Science Institute (STScI), the Stellar Astrophysics Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Illinois at Urbana-Champaign, University of Toronto, University of Utah, University of Virginia, Yale University, and Yunnan University. The DESI Legacy Imaging Surveys consist of three individual and complementary projects: the Dark Energy Camera Legacy Survey (DECaLS), the Beijing-Arizona Sky Survey (BASS), and the Mayall z-band Legacy Survey (MzLS). DECaLS, BASS and MzLS together include data obtained, respectively, at the Blanco telescope, Cerro Tololo Inter-American Observatory, NSF’s NOIRLab; the Bok telescope, Steward Observatory, University of Arizona; and the Mayall telescope, Kitt Peak National Observatory, NOIRLab. NOIRLab is operated by the Association of Universities for Research in Astronomy (AURA) under a cooperative agreement with the National Science Foundation. Pipeline processing and analyses of the data were supported by NOIRLab and the Lawrence Berkeley National Laboratory (LBNL). Legacy Surveys also uses data products from the Near-Earth Object Wide-field Infrared Survey Explorer (NEOWISE), a project of the Jet Propulsion Laboratory/California Institute of Technology, funded by the National Aeronautics and Space Administration. Legacy Surveys was supported by: the Director, Office of Science, Office of High Energy Physics of the U.S. Department of Energy; the National Energy Research Scientific Computing Center, a DOE Office of Science User Facility; the U.S. National Science Foundation, Division of Astronomical Sciences; the National Astronomical Observatories of China, the Chinese Academy of Sciences and the Chinese National Natural Science Foundation. LBNL is managed by the Regents of the University of California under contract to the U.S. Department of Energy. The complete acknowledgements can be found at https://www.legacysurvey.org/acknowledgment/. Software: This work made use of Astropy (http://www.astropy.org) a community-developed core Python package and an ecosystem of tools and resources for astronomy (Astropy Collaboration 2013, 2018, 2022); Photutils, an Astropy package for detection and photometry of astronomical sources (Bradley et al. 2022); Matplotlib (Hunter 2007); NumPy (Harris et al. 2020); SciPy (Virtanen et al. 2020); Pandas (The pandas development team 2020); TOPCAT (Taylor 2005); SExtractor (Bertin & Arnouts 1996); Swarp (Bertin 2010); and SAO Image DS9 (Joye & Mandel 2003).
