Hunting for Supersymmetry and Dark Matter at the Electroweak Scale

HUNTING FOR SUPERSYMMETRY AND DARK MATTER AT THE ELECTROWEAK SCALE By SEBASTIAN MACALUSO A dissertation submitted to the School of Graduate Studies Rutgers, The State University of New Jersey In partial fulfillment of the requirements For the degree of Doctor of Philosophy Graduate Program in Physics and Astronomy Written under the direction of David Shih And approved by New Brunswick, New Jersey October, 2018 ABSTRACT OF THE DISSERTATION Hunting for Supersymmetry and Dark Matter at the Electroweak Scale By SEBASTIAN MACALUSO Dissertation Director: Professor David Shih In this thesis, we study models of physics beyond the Standard Model (SM) at the electroweak scale and their phenomenology, motivated by naturalness and the nature of dark matter. Moreover, we introduce analyses and techniques relevant in searches at the Large Hadron Collider (LHC). We start by applying computer vision with deep learning to build a boosted top jets tagger at the LHC that outperforms previous state-of-the-art classifiers by a factor of ∼ 2{3 or more in background rejection, over a wide range of tagging efficiencies. Next, we define a cut and count based analysis for supersymmetric top quarks at LHC Run II capable of probing the line in the mass plane where there is just enough phase space to produce an on-shell top quark from the stop decay. We also implement a comprehensive reinterpretation of the 13 TeV ATLAS and CMS searches with the first ∼ 15 fb−1 of data and derive constraints on various simplified models of natural supersymmetry. We discuss how these constraints affect the fine-tuning of the electroweak scale. Finally, we show how a simple extension of the minimal supersymmetric SM, consisting of a dark sector, can explain the dark matter relic abundance and the Higgs mass in a natural way. ii Preface This thesis is the result of my graduate studies at the New High Energy Theory Center at Rutgers University, under the direction of professor David Shih. This thesis is organized as follows: chapter one contains a brief review of background topics related to the work developed in this thesis, such as the hierarchy problem and thermal dark matter. Chapters two, three, four and five consist of research on the subject that I performed with my collaborators under the supervision of my advisor. Finally, chapter six contains conclusions and outlook. All published papers can be conveniently accessed at http://arxiv.org/. iii Acknowledgements My journey through graduate school at the New High Energy Theory Center (NHETC) at Rutgers University has been an incredible learning experience about physics and life in general. I am grateful to many people who have helped and supported me over the years and without them this process would not have been possible. In the first place, I am deeply grateful to my advisor, David Shih. I was fortunate to work on mainstream and really interesting topics, thanks to David. Most of the physics I learned during graduate school was thanks to David and this happened in different ways, many times directly from him and others from working on problems and ideas during our projects. He showed me how to work rigorously and always pay attention to details. Additionally, I would like to point out that David always kept his office door open for me, always had time to answer my questions and always carefully listened to my ideas and contributions during discussions. I am extremely thankful to him for sharing his ideas and projects with me, for his advice, for the large amount of time he has dedicated to teaching and discussing with me during all these years, and for supporting me every time I wanted to try some new approach or direction. The latter resulted in implementing multiple new packages or writing our own code during our projects together, among other things. Finally, I am very grateful for David's patience and support at moments when things did not go as planned. At various times throughout my studies I had the opportunity to learn from other mentors in addition to David. I am really grateful to Matt Buckley for the physics I learned during our discussions and collaboration, for sharing his ideas with me and for his continuous support and advice throughout all my time at Rutgers. I am also particularly thankful to Scott Thomas for the physics discussions we had, especially in the early stages of my graduate studies and for pointing me in the right direction when I asked for help with a physics problem. I also want to thank Brock Tweedie and Angelo Monteux. I had the iv fortune to collaborate with Brock during my first project and I am immensely grateful for his patience and guidance during my learning process and for teaching me how to design and perform a collider physics analysis. I also learned from Angelo and was lucky to have multiple discussions with him and a really fruitful collaboration. Moreover, I am grateful to Michael Park for his guidance during my first project and my initial attempts to use the relevant computational packages. Finally, I would like to thank Aria Basirnia for his support as well as all the physics I learned from him from our collaboration and multiple discussions during the time we spent together at Rutgers. I want to thank Eva Halkiadakis and John Paul Chou for physics discussions and helping me understand physics at LHC. I am also thankful to Alejandro Gomez Espinosa, Savvas Kyriacou, Marco Farina, Anthony DiFranzo, Pietro Longhi, Daniel Brennan, and especially Daniel Egana-Ugrinovic, Pouya Asadi and David Feld for all our discussions, collaborations, support and friendship. Moreover, I want to thank my Licenciatura thesis advisor Martin Schvellinger. He guided me in my early stages and spent a lot of time teaching me physics, and shared his ideas and enthusiasm for physics with me. His continuous support has been particularly important for my career in physics. I am very grateful for the constant support provided by the NHETC all these years and also by the Physics Department during my initial years at Rutgers. In addition, I am thankful for the funding for summer schools and trips; they were very important for my academic training. In particular, I am grateful to Daniel Friedan and Ronald Gilman for making sure I had a successful time during my graduate studies. I am also thankful to Shirley Hinds, Diane Soyak and Christina Pettola for the many times they helped me solve an administrative problem. I have been fortunate to have some wonderful friends during this time. Among them, I am especially grateful to Adrian, Kostas, and Juani who supported me in numerous ways during all these years. Last but not least, my deepest gratitude to my family, who had to live with the conse- quences of my decision to pursue my studies in a distant place from home. Thanks for the unconditional and constant support. v Dedication To my parents, for the unconditional and constant support vi Table of Contents Abstract ii Preface iii Acknowledgements iv Dedication vi Table of Contents vii 1 Introduction 1 1.1 The Large Hadron Collider . 2 1.1.1 CMS experiment . 3 1.1.2 Higgs boson and its discovery at LHC . 5 1.1.3 Top quarks and their collider phenomenology . 7 1.2 Hierarchy Problem . 11 1.2.1 Higgs mass in the MSSM . 12 1.3 Dark Matter . 17 1.3.1 Neutralino dark matter . 19 1.4 Description of the content of each chapter . 22 2 Pulling Out All the Tops with Computer Vision and Deep Learning 24 2.1 Introduction . 25 2.2 Methodology . 29 2.3 Improvements to the neural network . 32 vii 2.3.1 Loss function . 33 2.3.2 Optimizer algorithm . 33 2.3.3 Architecture . 35 2.4 Image preprocessing . 36 2.5 Other improvements . 38 2.5.1 Sample size . 38 2.5.2 Color . 39 2.6 Final comparison . 40 2.7 Outlook of this chapter . 45 3 Revealing Compressed Stops Using High-Momentum Recoils 48 3.1 Introduction . 49 3.2 Proposed analysis and predicted coverage . 52 3.3 Discussion and Outlook of this chapter . 60 4 Cornering Natural SUSY at LHC Run II and Beyond 63 4.1 Introduction and Summary . 64 4.2 Recasted searches and methodology . 70 4.3 Overview of simplified models . 73 4.4 Results . 76 4.4.1 Vanilla SUSY . 77 4.4.2 Effective SUSY . 78 4.4.3 RPV and HV/Stealth SUSY . 80 4.4.4 RPV Effective SUSY . 82 4.4.5 Summary of results and further implications . 82 4.5 Conclusions of this chapter and Future Directions . 85 4.5.1 Projections to 300 fb−1 and 3 ab−1 ................... 85 4.5.2 Future directions for model building . 87 5 Dark Matter and the Higgs in Natural SUSY 90 5.1 Introduction and Summary . 91 viii 5.2 The Model . 97 5.3 DM Direct Detection through the h and Z Portals . 100 5.4 Higgs mass and Fine-Tuning . 102 5.5 The need for mostly-singlet DM . 105 5.6 DM annihilation in the mostly-singlet regime . 107 5.6.1 DM annihilation to fermions . 109 5.6.2 DM annihilation to bosons . 110 5.6.3 Total annihilation cross section . 110 5.7 Putting it all together . 112 5.7.1 Plots in the ML-MS plane . 112 5.7.2 Projecting onto the thermal relic contour . 114 5.8 Outlook of this chapter . 116 5.8.1 UV considerations . 116 5.8.2 LHC Phenomenology . 117 5.8.3 Future directions . 119 6 Conclusions and outlook 121 Appendices A Validating our DeepTop implementation 125 B Validating our HEPTopTaggerV2 implementation 127 C Importance of the merge requirement 129 D Event Generation 131 E Recasting Details and Validation 133 E.0.1 ATLAS Same-sign Lepton/Three Lepton .

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