This will be a required acquisition text for academic libraries. More than ten years after its discovery, still relatively little is known about the top quark, the heaviest known elementary particle. This extensive survey summarizes and reviews top-quark physics based on the precision measurements at the Fermilab Tevatron Collider, as well as examining in detail the sensitivity of these experiments to new physics. Finally, the author provides an overview of top quark physics at the Large Hadron Collider.

This thesis presents a search for long-lived particles decaying into displaced electrons and/or muons with large impact parameters. This signature provides unique sensitivity to the production of theoretical lepton-partners, sleptons. These particles are a feature of supersymmetric theories, which seek to address unanswered questions in nature. The signature searched for in this thesis is difficult to identify, and in fact, this is the first time it has been probed at the Large Hadron Collider (LHC). It covers a long-standing gap in coverage of possible new physics signatures. This thesis describes the special reconstruction and identification algorithms used to select leptons with large impact parameters and the details of the background estimation. The results are consistent with background, so limits on slepton masses and lifetimes in this model are calculated at 95% CL, drastically improving on the previous best limits from the Large Electron Positron Collider (LEP).

This practical guide covers the essential tasks in statistical data analysis encountered in high energy physics and provides comprehensive advice for typical questions and problems. The basic methods for inferring results from data are presented as well as tools for advanced tasks such as improving the signal-to-background ratio, correcting detector effects, determining systematics and many others. Concrete applications are discussed in analysis walkthroughs. Each chapter is supplemented by numerous examples and exercises and by a list of literature and relevant links. The book targets a broad readership at all career levels - from students to senior researchers. An accompanying website provides more algorithms as well as up-to-date information and links. * Free solutions manual available for lecturers at www.wiley-vch.de/supplements/

This volume comprises six well-versed contributed chapters devoted to report the latest fi ndings on the applications of machine learning for big data analytics. Big data is a term for data sets that are so large or complex that traditional data processing application software is inadequate to deal with them. The possible challenges in this direction include capture, storage, analysis, data curation, search, sharing, transfer, visualization, querying, updating and information privacy. Big data analytics is the process of examining large and varied data sets - i.e., big data - to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions. This volume is intended to be used as a reference by undergraduate and post graduate students of the disciplines of computer science, electronics and telecommunication, information science and electrical engineering. THE SERIES: FRONTIERS IN COMPUTATIONAL INTELLIGENCE The series Frontiers In Computational Intelligence is envisioned to provide comprehensive coverage and understanding of cutting edge research in computational intelligence. It intends to augment the scholarly discourse on all topics relating to the advances in artifi cial life and machine learning in the form of metaheuristics, approximate reasoning, and robotics. Latest research fi ndings are coupled with applications to varied domains of engineering and computer sciences. This field is steadily growing especially with the advent of novel machine learning algorithms being applied to different domains of engineering and technology. The series brings together leading researchers that intend to continue to advance the fi eld and create a broad knowledge about the most recent research.

This book attempts to cover the fascinating field of physics of relativistic heavy ions, mainly from the experimentalist's point of view. After the introductory chapter on quantum chromodynamics, basic properties of atomic nuclei, sources of relativistic nuclei, and typical detector set-ups are described in three subsequent chapters. Experimental facts on collisions of relativistic heavy ions are systematically presented in 15 consecutive chapters, starting from the simplest features like cross sections, multiplicities, and spectra of secondary particles and going to more involved characteristics like correlations, various relatively rare processes, and newly discovered features: collective flow, high pT suppression and jet quenching. Some entirely new topics are included, such as the difference between neutron and proton radii in nuclei, heavy hypernuclei, and electromagnetic effects on secondary particle spectra.Phenomenological approaches and related simple models are discussed in parallel with the presentation of experimental data. Near the end of the book, recent ideas about the new state of matter created in collisions of ultrarelativistic nuclei are discussed. In the final chapter, some predictions are given for nuclear collisions in the Large Hadron Collider (LHC), now in construction at the site of the European Organization for Nuclear Research (CERN), Geneva. Finally, the appendix gives us basic notions of relativistic kinematics, and lists the main international conferences related to this field. A concise reference book on physics of relativistic heavy ions, it shows the present status of this field.