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A High-Performance, Catalog-Driven Approach to Light Curve Extraction for Wide-Field

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A High-Performance, Catalog-Driven Approach to Light Curve Extraction for Wide-Field A High-Performance, Catalog-Driven Approach to Light Curve Extraction for Wide-Field Photometric Surveys By Robert J. Siverd Jr. Dissertation Submitted to the Faculty of the Graduate School of Vanderbilt University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY in Astrophysics August 9, 2019 Nashville, Tennessee Approved: Keivan G. Stassun, Ph.D. Andreas Berlind, Ph.D. David Weintraub, Ph.D. Joshua Pepper, Ph.D. ACKNOWLEDGMENTS I’d like to offer special thanks to Dr. Keivan Stassun for the years of advice, supervision, and encouragement without which I could not have come this far. I wish to extend this gratitude to Dr. Andreas Berlind, Dr. Joshua Pepper, and Dr. David Weintraub who have invested significant time and energy to help me reach this far and for helping me develop as a scientist. I am also extremely grateful for the loving support of family and friends (Mom, Dad, Veronica, and Amanda especially) that has helped keep me going through this years-long journey. I couldn’t have done it without you! This project makes use of data from the KELT survey, including support from The Ohio State University, Vanderbilt University, and Lehigh University, along with the KELT follow-up collaboration. Construction of KELT-N was supported by the National Aeronau- tics and Space Administration under grant No. NNG04GO70G issued through the Origins of Solar Systems program. KELT-South is hosted by the South African Astronomical Ob- servatory and we are grateful for their ongoing support and assistance. This work uses observations made at the South African Astronomical Observatory (SAAO). This work includes data taken at The McDonald Observatory of The Univer- sity of Texas at Austin. This work makes use of observations from the LCOGT network. The TRES and KeplerCam observations were obtained with partial support from the Ke- pler Mission through NASA Cooperative Agreement NNX11AB99A with the Smithsonian Astrophysical Observatory. This work has made use of NASA’s Astrophysics Data System, the Extrasolar Planet Encyclopedia at exoplanet.eu [Schneider et al., 2011], the NASA Exoplanet Archive, the Exoplanet Orbit Database at exoplanets.org, the SIMBAD database operated at CDS, Stras- bourg, France, and the VizieR catalogue access tool, CDS, Strasbourg, France. We make use of Filtergraph, an online data visualization tool developed at Vander- ii bilt University through the Vanderbilt Initiative in Data-intensive Astrophysics (VIDA). We acknowledge with thanks the variable star observations from the AAVSO International Database contributed by observers worldwide and used in this research. This research was made possible through the use of the AAVSO Photometric All-Sky Survey (APASS), funded by the Robert Martin Ayers Sciences Fund and NSF AST-1412587. We also used data products from the Widefield Infrared Survey Explorer, which is a joint project of the University of California, Los Angeles; the Jet Propulsion Laborato- ry/California Institute of Technology, which is funded by the National Aeronautics and Space Administration; 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 the National Aeronautics and Space Administration and the National Science Foundation; and the European Space Agency (ESA) mission Gaia (http://www.cosmos.esa.int/gaia), processed by the Gaia Data Processing and Anal- ysis Consortium (DPAC, http://www.cosmos.esa.int/web/gaia/dpac/consortium). Funding for the DPAC has been provided by national institutions, in particular the institutions par- ticipating in the Gaia Multilateral Agreement. MINERVA is a collaboration among the Harvard-Smithsonian Center for Astrophysics, The Pennsylvania State University, the Uni- versity of Montana, and the University of New South Wales. MINERVA is made possible by generous contributions from its collaborating institutions and Mt. Cuba Astronomical Foundation, The David & Lucile Packard Foundation, National Aeronautics and Space Administration (EPSCOR grant NNX13AM97A), The Australian Research Council (LIEF grant LE140100050), and the National Science Foundation (grants 1516242 and 1608203). Any opinions, findings, and conclusions or recommendations expressed are those of the au- thor and do not necessarily reflect the views of the National Science Foundation. This work was partially supported by funding from the Center for Exoplanets and Habitable Worlds. The Center for Exoplanets and Habitable Worlds is supported by the Pennsylvania State University, the Eberly College of Science, and the Pennsylvania Space Grant Consortium. iii TABLE OF CONTENTS Page ACKNOWLEDGMENTS . ii LIST OF TABLES . viii LIST OF FIGURES . ix LIST OF ABBREVIATIONS . xi Chapter 1 Introduction . .1 2 KELT-1b: a Strongly Irradiated, Highly Inflated, Short Period, 27 Jupiter-Mass Companion Transiting a Mid-F Star . .4 2.1 Introduction . .4 2.2 The KELT-North Survey . 12 2.2.1 KELT-North Instrumentation and Survey Strategy . 12 2.2.2 KELT-North Pipeline . 20 2.2.3 KELT-North Candidate Selection . 21 2.3 Observations . 25 2.3.1 KELT-North Photometry, Candidate Identification, and Vetting Overview 25 2.3.2 Previous Identification of the Photometric Candidate by HATNet . 27 2.3.3 Spectroscopy from FLWO/TRES . 30 2.3.4 Follow-Up Photometry . 34 2.3.4.1 Peter van de Kamp Observatory (PvdKO) . 36 2.3.4.2 University of Louisville Moore Observatory (ULMO) . 36 2.3.4.3 Hereford Arizona Observatory (HAO) . 40 2.3.4.4 FLWO/KeplerCam . 41 2.3.4.5 Las Cumbres Observatory Global Telescope Network (LCOGT) 41 2.3.5 Keck Adaptive Optics Imaging . 42 2.4 Evidence Against a Blend Scenario . 45 2.5 Characterization of the Star, Companion, and Orbit . 47 2.5.1 Properties of the Host Star . 47 2.5.2 System Properties Derived from a Joint Fit . 53 2.5.3 System Ephemeris and Transit Timing Variations . 58 2.5.4 Secondary Eclipse Limits . 60 2.6 Discussion . 62 2.6.1 Brown Dwarf or Supermassive Planet? KELT-1b and the Brown Dwarf Desert . 64 2.6.1.1 Comparison Sample of Transiting Exoplanets, Brown Dwarfs, and Low-mass Stellar Companions . 65 2.6.2 Tides, Synchronization, and Kozai Emplacement . 70 2.6.3 Comparison to Theoretical Models of Brown Dwarfs . 74 2.6.4 Prospects for Follow Up . 78 iv 2.7 Summary . 80 3 Observations of the M82 SN with the Kilodegree Extremely Little Telescope . 81 3.1 Introduction . 81 3.2 Data and Methods . 82 3.2.1 Data . 83 3.2.2 Dark and Flat Calibration . 84 3.2.3 Gradient Correction and Cloud Removal . 85 3.2.4 Image Subtraction . 85 3.2.5 Accurate Photometric Uncertainties . 86 3.2.6 Conversion of Instrumental to Physical Flux Units . 88 3.3 Results . 90 3.3.1 Time of initial explosion . 90 3.3.2 Time of maximum light and total rise time . 91 3.3.3 Secondary bump . 92 3.3.4 Short-Timescale Light Variations . 95 3.4 Conclusions . 97 4 KELT-19Ab: a P∼4.6 Day Hot Jupiter Transiting a Likely Am Star with a Distant Stellar Companion . 98 4.1 Introduction . 98 4.2 Discovery and Follow-Up Observations . 101 4.2.1 KELT-North Observations and Photometry . 101 4.2.2 Photometric Time-series Follow-up . 101 4.2.2.1 KeplerCam . 103 4.2.2.2 WCO . 104 4.2.2.3 Salerno . 104 4.2.2.4 MINERVA . 104 4.2.2.5 MVRC . 105 4.2.2.6 CROW . 105 4.2.3 High-Contrast Imaging . 105 4.2.4 Spectroscopic Follow-up . 111 4.2.4.1 TRES at FLWO . 111 4.2.4.2 HJST at McDonald . 111 4.2.4.3 Radial Velocities . 112 4.2.4.4 Doppler Tomographic Observations . 115 4.2.4.5 Stellar Parameters from Spectra . 116 4.2.4.6 KELT-19A is likely an Am star . 119 4.3 Host Star Properties . 123 4.3.1 SED Analysis . 125 4.3.2 Stellar Models and Age . 127 4.3.3 UVW Space Motion . 128 4.3.4 Global System Fit . 128 4.3.4.1 Light Curve Detrending and Deblending . 129 4.3.4.2 Gaussian and Uniform Priors . 130 v 4.3.4.3 Global Model Configurations . 131 4.3.4.4 Global Model Results . 131 4.3.4.5 Transit Timing Variation Results . 132 4.4 False Positive Analysis . 132 4.5 Discussion . 136 4.5.1 Spin-Orbit Misalignment . 138 4.5.2 Tidal Evolution and Irradiation History . 139 4.6 Conclusion . 140 5 Catalog-Driven Extraction: a New Paradigm for Improved Performance from the KELT Transit Survey . 143 5.1 Introduction . 143 5.2 KELT Photometry and Difference Imaging Primer . 144 5.3 Legacy System Shortcomings . 147 5.3.1 Difficulty in Exploiting Overlapping Fields . 147 5.3.2 Object List Problems: Missing Stars and Erroneous Depths . 149 5.3.2.1 Crowding-Induced Photometry Errors . 149 5.3.2.2 Systematic Depth Errors in Practice . 150 5.4 Catalog-Driven Extraction . 151 5.4.1 CDE Process Overview . 152 5.4.2 KELT Target Catalog: UCAC4 Source Selection . 156 5.4.3 Photometric Zero-Point and Synthetic KELT Magnitudes . 158 5.4.4 Building the CDE Object List . 162 5.4.5 Decoupling Candidate Selection from Observing . 167 5.5 Light Curve Extraction and CDE Data Product Assembly . 168 5.5.1 Difference Image Photometry and Initial Quality Control . 168 5.5.2 Raw Light Curve Generation . 169 5.5.2.1 Extraction of Difference Fluxes . 169 5.5.2.2 Conversion to Magnitudes and Quality Assessment . 169 5.5.2.3 Windowed Median Smoothing . ..
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