The Higgs boson discovery at the Large Hadron Collider in 2012 relied on boosted decision trees. Since then, high energy physics (HEP) has applied modern machine learning (ML) techniques to all stages of the data analysis pipeline, from raw data processing to statistical analysis. The unique requirements of HEP data analysis, the availability of high-quality simulators, the complexity of the data structures (which rarely are image-like), the control of uncertainties expected from scientific measurements, and the exabyte-scale datasets require the development of HEP-specific ML techniques. While these developments proceed at full speed along many paths, the nineteen reviews in this book offer a self-contained, pedagogical introduction to ML models' real-life applications in HEP, written by some of the foremost experts in their area.
This concise book gives a comprehensive introduction to important essential concepts for understanding phenomenological physics of glassy state and glass transition behaviors observed in various dipole glass systems in terms of more familiar terminology from established glass and spin glass models. Important characteristic glass transition behaviors from supercooled liquid will be correlated with the corresponding behaviors of dipole glass systems so that senior undergraduate students, as well as new graduate students, may better understand their science and engineering class lectures on the many varieties of glassy materials and glass transition phenomena.Many good books are available for spin glass and window pane glasses but not for dipole glass, however, several first generation pioneers (including Eric Courtens, Hugo Schmidt, and Robert Blinc) in the field of dipole glass have retired from the active working fronts. Very odd systems of dipole glass behaviors are reported frequently, and so a standard reference is needed that applies the fundamental concepts of dipole glass to make hierarchical connections between different systems very clear. This text aims to fulfill this need.
The Full Event Interpretation and Its Validation on Belle Data
Author: Thomas Keck
This book explores how machine learning can be used to improve the efficiency of expensive fundamental science experiments. The first part introduces the Belle and Belle II experiments, providing a detailed description of the Belle to Belle II data conversion tool, currently used by many analysts. The second part covers machine learning in high-energy physics, discussing the Belle II machine learning infrastructure and selected algorithms in detail. Furthermore, it examines several machine learning techniques that can be used to control and reduce systematic uncertainties. The third part investigates the important exclusive B tagging technique, unique to physics experiments operating at the Υ resonances, and studies in-depth the novel Full Event Interpretation algorithm, which doubles the maximum tag-side efficiency of its predecessor. The fourth part presents a complete measurement of the branching fraction of the rare leptonic B decay “B→tau nu”, which is used to validate the algorithms discussed in previous parts.
To be Published in the Proc[eedings] of the Fifth Workshop on Software Engineering, Artificial Intelligence and Expert Systems for High Energy and Nuclear Physics, Lausanne, Switzerland, Sep[tember] 2 - 6, 1996
This book is the first of its kind that provides a comprehensive overview and insightful analyses of Chinese business culture, behavioral patterns, and mind games from an insider's perspective. It traces the underlying causes of these patterns and games in the context of Chinese philosophy, history, culture, political and economic systems, and regional features. It aims to cover all information essential to understanding the fundamental issues when an international business person conducts business in China or communicate with the Chinese community. It also presents a collection of real cases to illustrate and substantiate theoretical analyses and factual explanations in combination with plenty of useful practical advice and how-to tips.Published by Cengage Learning Asia and marketed by World Scientific Publishing Co.
This book presents high-quality research papers that demonstrate how emerging technologies in the field of intelligent systems can be used to effectively meet global needs. The respective papers highlight a wealth of innovations and experimental results, while also addressing proven IT governance, standards and practices, and new designs and tools that facilitate rapid information flows to the user. The book is divided into five major sections, namely: “Advances in High Performance Computing”, “Advances in Machine and Deep Learning”, “Advances in Networking and Communication”, “Advances in Circuits and Systems in Computing” and “Advances in Control and Soft Computing”.
Originally written in 1964, this famous text is a study of the classical theory of charged particles. Many applications treat electrons as point particles. At the same time, there is a widespread belief that the theory of point particles is beset with various difficulties such as an infinite electrostatic self-energy, a rather doubtful equation of motion which admits physically meaningless solutions, violation of causality and others. The classical theory of charged particles has been largely ignored and has been left in an incomplete state since the discovery of quantum mechanics. Despite the great efforts of men such as Lorentz, Abraham, Poincaré, and Dirac, it is usually regarded as a “lost cause”. But thanks to progress made just a few years ago, the author is able to resolve the various problems and to complete this unfinished theory successfully.
18th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2005, Bari, Italy, June 22-24, 2005, Proceedings
Author: Floriana Esposito
“Intelligent systems are those which produce intelligent o?springs.” AI researchers have been focusing on developing and employing strong methods that are capable of solving complex real-life problems. The 18th International Conference on Industrial & Engineering Applications of Arti?cial Intelligence & Expert Systems (IEA/AIE 2005) held in Bari, Italy presented such work performed by many scientists worldwide. The Program Committee selected long papers from contributions presenting more complete work and posters from those reporting ongoing research. The Committee enforced the rule that only original and unpublished work could be considered for inclusion in these proceedings. The Program Committee selected 116 contributions from the 271 subm- ted papers which cover the following topics: arti?cial systems, search engines, intelligent interfaces, knowledge discovery, knowledge-based technologies, na- ral language processing, machine learning applications, reasoning technologies, uncertainty management, applied data mining, and technologies for knowledge management. The contributions oriented to the technological aspects of AI and the quality of the papers are witness to a research activity clearly aimed at consolidating the theoretical results that have already been achieved. The c- ference program also included two invited lectures, by Katharina Morik and Roberto Pieraccini. Manypeoplecontributedindi?erentwaystothesuccessoftheconferenceand to this volume. The authors who continue to show their enthusiastic interest in applied intelligence research are a very important part of our success. We highly appreciate the contribution of the members of the Program Committee, as well as others who reviewed all the submitted papers with e?ciency and dedication.
The idea is to represent how A I enabled method can benefit various scientific domains, including Photonics, High Energy Physics, Quantum Informatics, Radiology, Hydrodynamics, Fluid Dynamics, Natural Language Processing The key feature of the conference is to promote research which can be reproduced by reviewing process It will be featured For that we ensure to provide access to the data used in the research Three sections are the following (1) Main Scientific results section, (2) Students section (3) Workshops and tutorials
These proceedings comprise current statistical issues in analyzing data in particle physics, astrophysics and cosmology, as discussed at the PHYSTAT05 conference in Oxford. This is a continuation of the popular PHYSTAT series; previous meetings were held at CERN (2000), Fermilab (2000), Durham (2002) and Stanford (2003).In-depth discussions on topical issues are presented by leading statisticians and research workers in their relevant fields. Included are invited reviews and contributed research papers presenting the latest, state-of-the-art techniques.
Fermi National Accelerator Laboratory (Batavia, IL)
ACAT 2000, October 16-20, 2000, Fermi National Accelerator Laboratory : Artificial Intelligence Innovative Software Algorithms and Tools, Symbolic Problem Solving and Large Scale Computing in High Energy Physics, Astrophysics, Accelerator Physics and Nuclear Physics
Author: Fermi National Accelerator Laboratory (Batavia, IL)
The volume of these proceedings is devoted to a wide variety of items, both in theory and experiment, of particle physics such as electroweak theory, fundamental symmetries, tests of the standard model and beyond, neutrino and astroparticle physics, hadron physics, gravitation and cosmology, physics at the present and future accelerator. Contents: Neutrino PhysicsPhysics at Accelerators and Studies in SM and BeyondAstroparticle Physics and CosmologyCP Violation and Rare DecaysHadron PhysicsNew Developments in Quantum Field TheoryProblems of Intelligentsia Readership: Advanced undergraduates and graduate students, and professionals, both experimentalists and theoreticians, working in particle physics and high energy physics, gravitation and cosmology.
5th International Conference, IEA/AIE-92, Paderborn, Germany, June 9-12, 1992. Proceedings
Author: Fevzi Belli
Publisher: Springer Science & Business Media
This volume contains the 5 invited papers and 72 selected papers that were presented at the Fifth International Conference on Industrial and Engineering Applications of Artificial Intelligence. This is the first IEA/AIE conference to take place outside the USA: more than 120 papers were received from 23 countries, clearly indicating the international character of the conference series. Each paper was reviewed by at least three referees. The papers are grouped into parts on: CAM, reasoning and modelling, pattern recognition, software engineering and AI/ES, CAD, vision, verification and validation, neural networks, machine learning, fuzzy logic and control, robotics, design and architecture, configuration, finance, knowledge-based systems, knowledge representation, knowledge acquisition and language processing, reasoning and decision support, intelligent interfaces/DB and tutoring, fault diagnosis, planning and scheduling, and data/sensor fusion.
“The US National Science Foundation (NSF) Research Experiences for Undergraduates (REU) program in mathematics is now 25 years old, and it is a good time to think about what it has achieved, how it has changed, and where this idea will go next.”This was the premise of the conference held at Mt. Holyoke College during 21-22 June, 2013, and this circle of ideas is brought forward in this volume. The conference brought together diverse points of view, from NSF administrators, leaders of university-wide honors programs, to faculty who had led REUs, recent PhDs who are expected to lead them soon, and students currently in an REU themselves. The conversation was so varied that it justifies a book-length attempt to capture all that was suggested, reported, and said. Among the contributors are Ravi Vakil (Stanford), Haynes Miller (MIT), and Carlos Castillo-Chavez (Arizona, President's Obama Committee on the National Medal of Science 2010-2012).This book should serve not only as a collection of speakers' notes, but also as a source book for anyone interested in teaching mathematics and in the possibility of incorporating research-like experiences in mathematics classes at any level, as well as designing research experiences for undergraduates outside of the classroom.