This Ph.D. thesis is a search for physics beyond the standard model (SM) of particle physics, which successfully describes the interactions and properties of all known elementary particles. However, no particle exists in the SM that can account for the dark matter, which makes up about one quarter of the energy-mass content of the universe. Understanding the nature of dark matter is one goal of the CERN Large Hadron Collider (LHC). The extension of the SM with supersymmetry (SUSY) is considered a promising possibilities to explain dark matter. The nominated thesis describes a search for SUSY using data collected by the CMS experiment at the LHC. It utilizes a final state consisting of a photon, a lepton, and a large momentum imbalance probing a class of SUSY models that has not yet been studied extensively. The thesis stands out not only due to its content that is explained with clarity but also because the author performed more or less all aspects of the thesis analysis by himself, from data skimming to limit calculations, which is extremely rare, especially nowadays in the large LHC collaborations.

This thesis represents one of the most comprehensive and in-depth studies of the use of Lorentz-boosted hadronic final state systems in the search for signals of Supersymmetry conducted to date at the Large Hadron Collider. A thorough assessment is performed of the observables that provide enhanced sensitivity to new physics signals otherwise hidden under an enormous background of top quark pairs produced by Standard Model processes. This is complemented by an ingenious analysis optimization procedure that allowed for extending the reach of this analysis by hundreds of GeV in mass of these hypothetical new particles. Lastly, the combination of both deep, thoughtful physics analysis with the development of high-speed electronics for identifying and selecting these same objects is not only unique, but also revolutionary. The Global Feature Extraction system that the author played a critical role in bringing to fruition represents the first dedicated hardware device for selecting these Lorentz-boosted hadronic systems in real-time using state-of-the-art processing chips and embedded systems.

The project reported here was a search for new super symmetric particles in proton-proton collisions at the LHC. It has produced some of the world’s best exclusion limits on such new particles. Furthermore, dedicated simulation studies and data analyses have also yielded essential input to the upgrade activities of the CMS collaboration, both for the Phase-1 pixel detector upgrade and for the R&D studies in pursuit of a Phase-2 end cap calorimeter upgrade.

This book discusses searches for Dark Matter at the CERN’s LHC, the world’s most powerful accelerator. It introduces the relevant theoretical framework and includes an in-depth discussion of the Effective Field Theory approach to Dark Matter production and its validity, as well as an overview of the formalism of Simplified Dark Matter models. Despite overwhelming astrophysical evidence for Dark Matter and numerous experimental efforts to detect it, the nature of Dark Matter still remains a mystery and has become one of the hottest research topics in fundamental physics. Two searches for Dark Matter are presented, performed on data collected with the ATLAS experiment. They analyze missing-energy final states with a jet or with top quarks. The analyses are explained in detail, and the outcomes and their interpretations are discussed, also in view of the precedent analysis of theoretical approaches. Given its depth of coverage, the book represents an excellent reference guide for all physicists interested in understanding the theoretical and experimental considerations relevant to Dark Matter searches at the LHC.

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