The Palomar Transient Factory Core-collapse Supernova Host-galaxy Sample. I. Host-galaxy Distribution Functions and Environment Dependence of Core-collapse Supernovae

Creators: Schulze, Steve; Yaron, Ofer; Sollerman, Jesper; Leloudas, Giorgos; Gal, Amit; Wright, Angus H.; Lunnan, Ragnhild; Gal-Yam, Avishay; Ofek, Eran O.; Perley, Daniel A.; Filippenko, Alexei V.; Kasliwal, Mansi M.; Kulkarni, Shri R.; Neill, James D.; Nugent, Peter E.; Quimby, Robert M.; Sullivan, Mark; Strothjohann, Nora Linn; Arcavi, Iair; Ben-Ami, Sagi; Bianco, Federica; Bloom, Joshua S.; De, Kishalay; Fraser, Morgan; Fremling, Christoffer U.; Horesh, Assaf; Johansson, Joel; Kelly, Patrick L.; Knežević, Nikola; Knežević, Sladjana; Maguire, Kate; Nyholm, Anders; Papadogiannakis, Semeli; Petrushevska, Tanja; Rubin, Adam; Yan, Lin; Yang, Yi; Adams, Scott M.; Bufano, Filomena; Clubb, Kelsey I.; Foley, Ryan J.; Green, Yoav; Harmanen, Jussi; Ho, Anna Y. Q.; Hook, Isobel M.; Hosseinzadeh, Griffin; Howell, D. Andrew; Kong, Albert K. H.; Kotak, Rubina; Matheson, Thomas; McCully, Curtis; Milisavljevic, Dan; Pan, Yen-Chen; Poznanski, Dovi; Shivvers, Isaac; van Velzen, Sjoert; Verbeek, Kars K.

Abstract

Several thousand core-collapse supernovae (CCSNe) of different flavors have been discovered so far. However, identifying their progenitors has remained an outstanding open question in astrophysics. Studies of SN host galaxies have proven to be powerful in providing constraints on the progenitor populations. In this paper, we present all CCSNe detected between 2009 and 2017 by the Palomar Transient Factory. This sample includes 888 SNe of 12 distinct classes out to redshift z ≈ 1. We present the photometric properties of their host galaxies from the far-ultraviolet to the mid-infrared and model the host-galaxy spectral energy distributions to derive physical properties. The galaxy mass function of Type Ic, Ib, IIb, II, and IIn SNe ranges from 10⁵ to 10^(11.5) M_⊙, probing the entire mass range of star-forming galaxies down to the least-massive star-forming galaxies known. Moreover, the galaxy mass distributions are consistent with models of star-formation-weighted mass functions. Regular CCSNe are hence direct tracers of star formation. Small but notable differences exist between some of the SN classes. Type Ib/c SNe prefer galaxies with slightly higher masses (i.e., higher metallicities) and star formation rates than Type IIb and II SNe. These differences are less pronounced than previously thought. H-poor superluminous supernovae (SLSNe) and SNe Ic-BL are scarce in galaxies above 10¹⁰ M_⊙. Their progenitors require environments with metallicities of < 0.4 and < 1 solar, respectively. In addition, the hosts of H-poor SLSNe are dominated by a younger stellar population than all other classes of CCSNe. Our findings corroborate the notion that low metallicity and young age play an important role in the formation of SLSN progenitors.

Additional Information

© 2021. The American Astronomical Society. Received 2020 August 13; revised 2021 April 15; accepted 2021 April 21; published 2021 August 10. We thank the referee for a careful reading of the manuscript and for helpful comments that improved this paper. We thank Nino Cucchiara, Thomas de Jaeger, Harald Ebeling, David Levitan, Bruce Margon, Jon Mauerhan, Jacob Rex, David Sand, Jeffrey M. Silverman, Vicky Toy, and Brad Tucker for performing some of the observations, and Ido Irani and Maryam Modjaz for valuable discussions. I.A. is a CIFAR Azrieli Global Scholar in the Gravity and the Extreme Universe Program and acknowledges support from that program, from the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation program (grant agreement 852097), from the Israel Science Foundation (grants 2108/18 and 2752/19), from the United States—Israel Binational Science Foundation (BSF), and from the Israeli Council for Higher Education Alon Fellowship. J.S.B. was partially supported by a Gordon and Betty Moore Foundation Data-Driven Discovery grant. The UCSC team is supported in part by National Aeronautics and Space Administration (NASA) grant NNG17PX03C, the Gordon & Betty Moore Foundation, the Heising-Simons Foundation, and by a fellowship from the David and Lucile Packard Foundation to R. J. Foley. A.V.F. acknowledges support from the US National Science Foundation (NSF), the Christopher R. Redlich Fund, the TABASGO Foundation, and the U.C. Berkeley Miller Institute for Basic Research in Science (in which he is a Miller Senior Fellow). M.F. is supported by a Royal Society—Science Foundation Ireland University Research Fellowship. A.G.-Y.'s research is supported by the EU via ERC grant 725161, the ISF GW excellence center, an IMOS space infrastructure grant and BSF/Transformative and GIF grants, as well as The Benoziyo Endowment Fund for the Advancement of Science, the Deloro Institute for Advanced Research in Space and Optics, The Veronika A. Rabl Physics Discretionary Fund, Paul and Tina Gardner, Yeda-Sela and the WIS-CIT joint research grant; A.G.-Y. is the recipient of the Helen and Martin Kimmel Award for Innovative Investigation. A.Y.Q.H. was supported by an NSF Graduate Research Fellowship under grant DGE1144469 and by the GROWTH project funded by the NSF under PIRE grant 1545949. D.A.H., G.H., and C.M. were supported by NSF grant AST-1313484. M.M.K. acknowledges support by the GROWTH (Global Relay of Observatories Watching Transients Happen) project funded by the NSF under PIRE Grant No. 1545949. S.K. was supported by the Ministry of Education, Science and Technological Development of the Republic of Serbia through contract 451-03-68/2020/14/20002 made with the Astronomical Observatory of Belgrade. G.L. is supported by a research grant (19054) from VILLUM FONDEN. R.L. is supported by a Marie Skłodowska-Curie Individual Fellowship within the Horizon 2020 European Union (EU) Framework Programme for Research and Innovation (H2020-MSCA-IF-2017-794467). K.M. acknowledges funding from EU H2020 ERC grant 758638. T.P. acknowledges the financial support from the Slovenian Research Agency (grants I0-0033, P1-0031, J1-8136, and Z1-1853). S.S. gratefully acknowledges support provided by the Feinberg Graduate School at the Weizmann Institute, Israel. A.H.W. is supported by a European Research Council Consolidator Grant (770935). The Palomar Transient Factory project is a scientific collaboration among the California Institute of Technology, Los Alamos National Laboratory, the University of Wisconsin, Milwaukee, the Oskar Klein Center, the Weizmann Institute of Science, the TANGO Program of the University System of Taiwan, and the Kavli Institute for the Physics and Mathematics of the Universe. LANL participation in iPTF is supported by the US Department of Energy as a part of the Laboratory Directed Research and Development program. This work makes use of data from the Las Cumbres Observatory network. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA; the observatory was made possible by the generous financial support of the W. M. Keck Foundation. Research at Lick Observatory is partially supported by a generous gift from Google. The data presented herein were obtained in part with ALFOSC, which is provided by the Instituto de Astrofísica de Andalucía (IAA) under a joint agreement with the University of Copenhagen and NOTSA. The Cerro Tololo Inter-American Observatory and the National Optical Astronomy Observatory are operated by the Association of Universities for Research in Astronomy (AURA) under cooperative agreement with the NSF. We thank the staff of the various observatories at which data were obtained for their excellent assistance. Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the US Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High-Performance Computing at the University of Utah. The SDSS website is www.sdss.org. SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration, including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, the Chilean Participation Group, the French Participation Group, the Harvard-Smithsonian Center for Astrophysics, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU)/University of Tokyo, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional/MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University. The Pan-STARRS1 Surveys (PS1) have been made possible through contributions of the Institute for Astronomy, the University of Hawaii, the PanSTARRS Project Office, the Max-Planck Society and its participating institutes, the Max Planck Institute for Astronomy, Heidelberg, and the Max Planck Institute for Extraterrestrial Physics, Garching, The Johns Hopkins University, Durham University, the University of Edinburgh, Queen's University Belfast, the Harvard-Smithsonian Center for Astrophysics, the Las Cumbres Observatory Global Telescope Network Incorporated, the National Central University of Taiwan, the Space Telescope Science Institute, NASA under grant NNX08AR22G issued through the Planetary Science Division of the NASA Science Mission Directorate, the NSF under grant AST-1238877, the University of Maryland, and Eötvös Loránd University (ELTE). This publication makes use of data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by NASA and the NSF. This publication also makes use of data products from the Wide-field Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles, and the Jet Propulsion Laboratory/California Institute of Technology, funded by NASA. The LBNL Physics Division is supported by the US Department of Energy Office of Science High Energy Physics. The National Energy Research Scientific Computing Center, which is supported by the Office of Science of the US Department of Energy under Contract DE-AC02-05CH11231, provided staff, computational resources, and data storage for this project. The Computational HEP program in the Department of Energy's Science Office of High Energy Physics provided resources through the "Cosmology Data Repository" project (grant #KA2401022). Software: Astropy v3.2.3 (Astropy Collaboration et al. 2013; 2018), Flexible Stellar Population Synthesis (FSPS; Conroy et al. 2009), High Order Transform of Psf ANd Template Subtraction v5.1.11 (Hotpants; Becker 2015), IRAF (Tody 1986), LAMBDAR (Wright et al. 2016), Prospector v0.3 (Leja et al. 2017), python-fsps (Foreman-Mackey et al. 2014) scikit-learn v0.21.2 (Pedregosa et al. 2011), Software for Calibrating AstroMetry and Photometry (SCAMP; Bertin 2006) v2.0.4, Source Extractor v2.19.5 (Bertin & Arnouts 1996), Supernova Identification v5.0 (Blondin & Tonry 2007), Superfit v3.5 (Howell et al. 2005).

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