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Understanding Type Ia Supernovae Through Their Host Galaxies Using the SDSS-II Supernova Survey

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Understanding Type Ia Supernovae Through Their Host Galaxies Using the SDSS-II Supernova Survey University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 2013 Understanding Type Ia Supernovae Through Their Host Galaxies Using the SDSS-II Supernova Survey Ravi Ryan Gupta University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/edissertations Part of the Astrophysics and Astronomy Commons, and the Physics Commons Recommended Citation Gupta, Ravi Ryan, "Understanding Type Ia Supernovae Through Their Host Galaxies Using the SDSS-II Supernova Survey" (2013). Publicly Accessible Penn Dissertations. 758. https://repository.upenn.edu/edissertations/758 This paper is posted at ScholarlyCommons. https://repository.upenn.edu/edissertations/758 For more information, please contact [email protected]. Understanding Type Ia Supernovae Through Their Host Galaxies Using the SDSS- II Supernova Survey Abstract The recent discovery of the accelerating expansion of the Universe and thus the existence of dark energy was made possible by the study of Type Ia supernovae. These thermonuclear explosions of white dwarfs are excellent standardizable candles that can be seen out to great distances and used to constrain cosmological parameters. However, in an era when modern surveys are discovering hundreds of Type Ia supernovae and upcoming surveys plan to find thousands more, we are no longer limited by statistics, but are now being limited by systematic uncertainties in supernova cosmology. Among these systematic uncertainties are the nature of the supernova progenitor and the effect of the environment on the progenitor. An excellent way to probe these systematics is through the study of the galaxies that host Type Ia supernovae. Correlations have been found between supernova properties and the physical properties of their host galaxies such as mass, metallicity, and star formation rate. In this dissertation, I use supernovae from the full three-year Sloan Digital Sky Survey II (SDSS-II) Supernova Survey and multi- wavelength photometry of their host galaxies to find videncee of a correlation between supernova luminosities and the age of their hosts, a possible proxy for progenitor age. I also detail a method of host galaxy identification, tested and applied ot the many thousands of SDSS-II supernova candidates, which will be published in the upcoming final data eleaser of the Supernova Survey. In addition, I present work in which I compute the luminosity functions for Type Ia supernovae and their host galaxies. This work and continuing work in this vein can help shed light on the nature of dark energy and improve the utility of Type Ia supernovae as cosmological distance indicators. Degree Type Dissertation Degree Name Doctor of Philosophy (PhD) Graduate Group Physics & Astronomy First Advisor Masao Sako Keywords Galaxies, Observational Cosmology, Supernovae Subject Categories Astrophysics and Astronomy | Physics This dissertation is available at ScholarlyCommons: https://repository.upenn.edu/edissertations/758 UNDERSTANDING TYPE IA SUPERNOVAE THROUGH THEIR HOST GALAXIES USING THE SDSS-II SUPERNOVA SURVEY Ravi Ryan Gupta A DISSERTATION in Physics and Astronomy Presented to the Faculties of the University of Pennsylvania in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy 2013 Supervisor of Dissertation Masao Sako, Associate Professor of Physics and Astronomy Graduate Group Chairperson A. T. Charlie Johnson, Professor of Physics and Astronomy Dissertation Committee James Aguirre, Assistant Professor of Physics and Astronomy Mariangela Bernardi, Associate Professor of Physics and Astronomy Adam Lidz, Assistant Professor of Physics and Astronomy Elliot Lipeles, Assistant Professor of Physics and Astronomy Dedication For Mom and Pop, who made many sacrifices to open as many doors for me as possible, and who encouraged me to pursue my interests, whatever they may be. From them I learned the importance of education, working hard, and trying my best, no matter what. And for my girlfriend, Kelly, who has been a constant source of support, care, and love despite being 3810.4 kilometers away. ii Acknowledgments First, I would like to begin by thanking my advisor, Masao Sako, whose teachings, guid- ance, and mentorship are not limited to my time here at Penn. As an undergraduate at Stanford, I had the privilege of working with Masao, who was a postdoctoral research fellow there at the time. From him I have learned early on the basic tools necessary to do research, from Unix computing and shell scripting to data analysis and thinking like a scientist. I am also indebted to my officemates and colleagues who, over the years, have become good friends. They have always taken the time to teach or better explain things to me, and I have learned an incredible amount from them all. Therefore, thanks to fellow Sako Group members Chris D’Andrea, Jennifer Mosher, John Fischer, and Rachel Cane with whom I’ve discussed many supernova-related and computer-related issues over the years. Thanks also to C. Jonathan MacDonald for his programming insights, and to Mariangela Bernardi, Ravi Sheth, and Alan Meert, whose expertise in the field of galaxies has been invaluable. My years here at Penn have been some of the most enjoyable of my life. For this I must thank, in addition to those previously mentioned, Annemarie Exarhos, Phil Korngut, Josh Kunkle, Andrés Plazas, and Liz Hines. I have benefited greatly from being a part of the Sloan Digital Sky Survey II Supernova Survey and the Dark Energy Survey Supernova Survey. In particular, I would like to thank John Marriner of Fermilab and Richard Kessler of the University of Chicago for their help and guidance in several key aspects of research presented in this dissertation. iii Additionally, I would like to acknowledge my grade school teachers Robin Dickerson, Steve Gouger, Reg Hendrickson, and Joseph Vanderway for their part in piquing my interest in the sciences. I would also like to thank Duane Doty of the California State University, Northridge who helped me solve the “chicken or the egg” research dilemma by giving me a chance and allowing me to work with him even though, as a college freshman, I had no prior research experience. During my later college years, I was thankful to have the opportunity to get a head start on astrophysics research under the supervision of Steven Kahn at Stanford University and his postdoctoral researchers at the time: Masao, John Peterson, and Ming Feng Gu. Finally, I thank my committee members James Aguirre, Mariangela Bernardi, Adam Lidz, and Elliot Lipeles for their help and patience. iv ABSTRACT UNDERSTANDING TYPE IA SUPERNOVAE THROUGH THEIR HOST GALAXIES USING THE SDSS-II SUPERNOVA SURVEY Ravi Ryan Gupta Masao Sako The recent discovery of the accelerating expansion of the Universe and thus the existence of dark energy was made possible by the study of Type Ia supernovae. These thermonu- clear explosions of white dwarfs are excellent standardizable candles that can be seen out to great distances and used to constrain cosmological parameters. However, in an era when modern surveys are discovering hundreds of Type Ia supernovae and upcoming sur- veys plan to find thousands more, we are no longer limited by statistics, but are now being limited by systematic uncertainties in supernova cosmology. Among these systematic un- certainties are the nature of the supernova progenitor and the effect of the environment on the progenitor. An excellent way to probe these systematics is through the study of the galaxies that host Type Ia supernovae. Correlations have been found between supernova properties and the physical properties of their host galaxies such as mass, metallicity, and star formation rate. In this dissertation, I use supernovae from the full three-year Sloan Digital Sky Survey II (SDSS-II) Supernova Survey and multi-wavelength photometry of their host galaxies to find evidence of a correlation between supernova luminosities and the age of their hosts, a possible proxy for progenitor age. I also detail a method of host galaxy identification, tested and applied to the many thousands of SDSS-II supernova candidates, which will be published in the upcoming final data release of the Supernova Survey. In addition, I present work in which I compute the luminosity functions for Type Ia supernovae and their host galaxies. This work and continuing work in this vein can help shed light on the nature of dark energy and improve the utility of Type Ia supernovae as cosmological distance indicators. v Contents Dedication ii Acknowledgments iii Abstract v List of Tables viii List of Figures ix 1 Introduction 1 1.1 Cosmology and the Expanding Universe . .1 1.1.1 Expansion History . .2 1.1.2 Magnitudes and Distance Moduli . .3 1.1.3 A Census of the Universe . .5 1.2 Type Ia Supernovae . .6 1.2.1 Classification and Progenitors . .7 1.2.2 Standardizable Candles . .8 1.2.3 Evidence for Acceleration . 11 1.3 Supernovae in the Sloan Digital Sky Survey . 13 1.4 Type Ia Supernova–Host Galaxy Correlations . 17 1.4.1 Environmental Dependencies on SN Luminosities . 17 1.4.2 Correlations with Hubble Residuals . 18 1.4.3 The Era of Systematics . 24 2 Multi-wavelength Properties of Type Ia Supernova Host Galaxies 26 2.1 Introduction . 26 2.2 Data . 28 2.2.1 Supernova Sample and Light Curve Analysis . 28 2.2.2 SDSS Host Galaxy Identification . 29 2.2.3 Host Matching and Galaxy Photometry . 29 2.3 Methods . 31 2.3.1 SN Distance Modulus and Hubble Residuals . 31 vi 2.3.2 Galaxy Model Fitting . 32 2.3.3 Derived Galaxy Properties . 34 2.4 Results . 35 2.4.1 Host Galaxy Properties . 35 2.4.2 Correlations with SN Fit Parameters . 37 2.4.3 Linear Trends with Hubble Residuals . 39 2.4.4 SDSS Co-add vs. Single-Frame Photometry . 42 2.5 Discussion . 44 3 Identifying Host Galaxies and Deriving Their Physical Properties 48 3.1 Introduction .
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