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Solar System Small-Body Demographics with the Palomar Transient Factory Survey

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Solar System Small-Body Demographics with the Palomar Transient Factory Survey Solar System Small-Body Demographics with the Palomar Transient Factory Survey Thesis by Adam Waszczak In Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy California Institute of Technology Pasadena, California 2015 (Defended May 15th, 2015) ii c 2015 Adam Waszczak All Rights Reserved iii Acknowledgements Working on the Palomar Transient Factory (PTF) team at Caltech has been an enriching and exciting experience, one that I will always look back upon as a valuable component in my development as a professional. I first and foremost thank my advisor, Prof. Shri Kulkarni (PI of the PTF project), for having actively reached out to me in early 2010|via phone, months before I even arrived at Caltech|inviting me to come onboard as a new graduate student. Even though I knew little to nothing of planetary science at the time, he managed to convey to me the rich and rewarding science potential of this project, all of which and more proved to be true during my time working for him. Thanks to Eran Ofek for having taken the time during my first year (and his busy postdoc) to teach me the basics of PTF and MATLAB|none of my research would have been possible without his mentoring and inspiration. I thank him and Oded Aharonson for hosting my visit to Israel in 2012. Thanks to the scientists and staff at Palomar Observatory, Caltech Optical Obser- vatories & IPAC for supporting PTF|with special thanks to Russ Laher and Frank Masci for their technical support of PTF's asteroid science. Thanks to Prof. Tom Prince for his appreciable amount of advising, his genuine interest in NEAs and his dedication to PTF. Thanks to the Keck Institute for Space Studies (KISS) at Caltech for its financial support and for involving me in several of its stimulating workshops. I would also like to acknowledge funding from JPL internal research and development. Thanks to Rex Chang, Prof. Wing Ip and the others at NCU for hosting my visit to Taiwan in 2014, and for their continued work helping to bolster PTF's reputation iv within the field of planetary science. Thanks to Yi, Mansi and Eric for letting me be lead observer on nearly thirty Palomar 200-inch observing runs! It was a pleasure operating that beautiful telescope and contributing to the PTF team's efforts beyond my own science. Thanks to Brian Bue, Umaa Rebbapragada, Frank Masci and David Levitan for introducing me to the methods of machine learning, making the career in data science I intend on pursuing possible. Thanks to the staff of the Planetary Science department and GPS Division for making my time at Caltech productive and my work life enjoyable. Thanks to my fellow planetary grad students Josh Kammer, Peter Gao, Masha Klescheva, Miki Nakajima, Mike Wong, Henry Ngo, Danielle Piskorz, Patrick Fischer and all the rest for the good times we've had both in the office and out. Thanks to Mike Line, Alex Lockwood, Konstantin Batygin and Ajay Limaye for showing me just how much fun planetary science, Caltech, and Pasadena in general could be|beginning with my very first visit to the department in 2009 as a prospec- tive student through to the time you graduated. I'll always miss the `used food' at F&E and long islands at BC you introduced me to. Thanks to my parents and family for supporting me from the beginning, as I never would have made it to Caltech without you. Lastly, dearest thanks to my loving fianc´eeKelley for enduring the New York to LA long-distance relationship for the past three years while I finished my PhD. I look forward to moving back to the East Coast and our marriage and life together! v Abstract Observational studies of our solar system's small-body populations (asteroids and comets) offer insight into the history of our planetary system, as these minor planets represent the left-over building blocks from its formation. The Palomar Transient Factory (PTF) survey began in 2009 as the latest wide-field sky-survey program to be conducted on the 1.2-meter Samuel Oschin telescope at Palomar Observatory. Though its main science program has been the discovery of high-energy extragalactic sources (such as supernovae), during its first five years PTF has collected nearly five million observations of over half a million unique solar system small bodies. This thesis begins to analyze this vast data set to address key population-level science topics, including: the detection rates of rare main-belt comets and small near-Earth asteroids, the spin and shape properties of asteroids as inferred from their lightcurves, the applicability of this visible light data to the interpretation of ultraviolet asteroid observations, and a comparison of the physical properties of main-belt and Jovian Trojan asteroids. Future sky-surveys would benefit from application of the analyti- cal techniques presented herein, which include novel modeling methods and unique applications of machine-learning classification. The PTF asteroid small-body data produced in the course of this thesis work should remain a fertile source of solar system science and discovery for years to come. vi Contents Acknowledgements iii Abstract v List of Figures xi List of Tables xxx 1 Introduction 1 2 Main-Belt Comets 7 2.1 Introduction . .7 2.2 Raw transient data . 11 2.2.1 Survey overview . 11 2.2.2 Candidate-observation quality filtering . 12 2.2.3 Sample quality assessment . 14 2.3 Known-object extraction . 15 2.3.1 Implementation of kd-tree indexing . 15 2.3.2 Matching ephemerides against the kd-tree . 16 2.3.3 Summary of known small bodies detected . 17 2.3.4 Overlap of PTF with the WISE and SDSS data sets . 19 2.4 Unknown-object extraction . 22 2.4.1 Previous and ongoing PTF small-body discovery work . 23 2.4.2 A custom discovery algorithm for main-belt objects . 24 2.4.3 Summary of objects discovered . 27 vii 2.5 Extended-object analysis: Approach . 28 2.5.1 Definition of the extendedness parameter µ ........... 28 2.5.2 Systematic (non-cometary) variation in µ ............ 29 2.5.3 Formalism for interpreting µ ................... 30 2.5.4 A model-µ to describe inert objects . 31 2.5.5 Defining a visually-screenable sample . 33 2.6 Extended-object analysis: Results . 35 2.6.1 A new quasi-Hilda comet: 2011 CR42 .............. 36 2.7 Statistical interpretation . 41 2.7.1 Bayesian formalism . 41 2.7.2 Active MBCs in the entire main-belt . 42 2.7.3 Active MBCs in the outer main-belt . 43 2.7.4 Active MBCs in the low-inclination outer main-belt . 44 2.7.5 Active MBCs among low-i outer main-belt objects observed near perihelion (−45◦ < ν < 45◦)................ 45 2.7.6 Active MBCs in the sub-5 km diameter population . 45 2.7.7 Active MBCs among low-albedo (WISE-sampled) objects . 46 2.7.8 Active MBCs among C-type (SDSS-sampled) objects . 47 2.8 Conclusion . 47 2.8.1 Summary . 47 2.8.2 Comparison to previous work . 49 2.8.3 Future work: Photometric (absolute magnitude) variation as a function of orbital anomaly . 50 3 Small Near-Earth Asteroids 51 3.1 Introduction . 51 3.2 Overview of the PTF survey . 56 3.2.1 Technical and operational characteristics . 56 3.2.2 Previous solar system science with PTF . 57 3.2.3 Real-time data reduction at IPAC . 57 viii 3.2.4 Detections of known streaking NEAs . 58 3.3 Streak-detection process . 60 3.3.1 Object detection with findStreaks ............... 60 3.3.1.1 Algorithm . 60 3.3.1.2 Completeness and contamination . 64 3.3.2 Machine-learned classification . 68 3.3.2.1 Overview . 68 3.3.2.2 Implementation and training . 71 3.3.2.3 Post-training performance . 74 3.3.3 Web-based screening interface . 75 3.4 Follow-up and reporting of discoveries . 78 3.4.1 Target-of-opportunity (ToO) requests . 78 3.4.2 Initial NEA discoveries . 79 3.4.3 Blind real-time recovery of known NEAs . 82 3.4.4 Unconfirmed discoveries . 82 3.4.5 Artificial satellites . 84 3.5 De-biased detection rate . 85 3.6 Scaling laws for streaked asteroid detection . 87 4 Asteroid Lightcurves 91 4.1 Introduction . 91 4.1.1 Asteroid rotation . 91 4.1.2 Asteroid phase functions . 95 4.2 Observations . 97 4.2.1 Overview of the PTF survey . 97 4.2.2 This work's data set . 98 4.3 Lightcurve model . 101 4.3.1 Rotation component . 101 4.3.1.1 Intra-opposition constraint . 101 4.3.1.2 Second-order Fourier series . 102 ix 4.3.2 Phase-function component . 103 4.3.2.1 Two-parameter Shevchenko model . 104 4.3.2.2 Lumme-Bowell G model . 107 4.3.2.3 Muinonen et al. G12 model . 108 4.3.2.4 Multi-parameter Hapke model . 109 4.4 Lightcurve-fitting algorithm . 110 4.4.1 Linear phase-function parameters . 112 4.4.2 Nonlinear phase-function parameters . 116 4.4.3 Comments on implementation . 120 4.5 Reliability of fitted rotation periods . 121 4.5.1 Known-period subsample . 122 4.5.2 Machine learning . 127 4.5.2.1 Classifier training . 131 4.5.2.2 Classifier cross-validation . 135 4.5.2.3 Machine-vetted lightcurves . 138 4.5.3 Manual screening . 139 4.5.4 Asteroids with multiple fitted periods . 140 4.6 Preliminary lightcurve-based demographics .
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