Jet Substructure Without Trees
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Jet Substructure Without Trees
We present an alternative approach to identifying and characterizing jet substructure. An angular correlation function is introduced that can be used to extract angular and mass scales within a jet without reference to a clustering algorithm. This procedure gives rise to a number of useful jet observables. As an application, we construct a top quark tagging algorithm that is competitive with existing methods. In preparation for the LHC, the past several years have seen extensive work on various aspects of collider searches. With the excellent resolution of the ATLAS and CMS detectors as a catalyst, one area that has undergone significant development is jet substructure physics. The use of jet substructure techniques, which probe the fine-grained details of how energy is distributed in jets, has two broad goals. First, measuring more than just the bulk properties of jets allows for additional probes of QCD. For example, jet substructure measurements can be compared against precision perturbative QCD calculations or used to tune Monte Carlo event generators. Second, jet substructure allows for additional handles in event discrimination. These handles could play an important role at the LHC in discriminating between signal and background events in a wide variety of particle searches. For example, Monte Carlo studies indicate that jet substructure techniques allow for efficient reconstruction of boosted heavy objects such as the W{sup {+-}} and Z° gauge bosons, the top quark, and the Higgs boson.
Quark-gluon Plasma 6
This book, the sixth volume in a series on Quark-Gluon Plasma (QGP) research, offers updated reviews on theoretical developments and phenomenological understanding of the hot and dense matter formed in high-energy heavy-ion collisions. Authored by leading experts in the field, it delves into how these advancements help shed light on the recent data emerging from the experiments conducted at the Relativistic Heavy Ion Collider (RHIC) and the Large Hadron Collider (LHC). Despite setbacks caused by the COVID-19 pandemic, the book explores a multitude of recent progresses, including insights into jet measurements, study of hydrodynamization in QGP, flow measurements in large and small systems, spin polarization and chiral magnetic effect in relativistic heavy-ion collisions. Additionally, the book features a timely review of the QCD phase diagram in light of the new data collected at the Beam Energy Scan program at RHIC. Furthermore, it includes a chapter on the growing role of machine learning in analyzing and interpretating complex data. Written carefully with detailed analyses and expert reviews, Quark-Gluon Plasma 6 stands as an invaluable reference for individuals engaged in the field.
Advances in Jet Substructure at the LHC
This book introduces the reader to the field of jet substructure, starting from the basic considerations for capturing decays of boosted particles in individual jets, to explaining state-of-the-art techniques. Jet substructure methods have become ubiquitous in data analyses at the LHC, with diverse applications stemming from the abundance of jets in proton-proton collisions, the presence of pileup and multiple interactions, and the need to reconstruct and identify decays of highly-Lorentz boosted particles. The last decade has seen a vast increase in our knowledge of all aspects of the field, with a proliferation of new jet substructure algorithms, calculations and measurements which are presented in this book. Recent developments and algorithms are described and put into the larger experimental context. Their usefulness and application are shown in many demonstrative examples and the phenomenological and experimental effects influencing their performance are discussed. A comprehensive overview is given of measurements and searches for new phenomena performed by the ATLAS and CMS Collaborations. This book shows the impressive versatility of jet substructure methods at the LHC.