Artificial Intelligence For High Energy Physics PDF Download
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Author | : Paolo Calafiura |
Publisher | : World Scientific |
Total Pages | : 829 |
Release | : 2022-01-05 |
Genre | : Science |
ISBN | : 9811234043 |
Download Artificial Intelligence For High Energy Physics Book in PDF, ePub and Kindle
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.
Author | : Volker Knecht |
Publisher | : CRC Press |
Total Pages | : 147 |
Release | : 2022-08-29 |
Genre | : Computers |
ISBN | : 1000643832 |
Download AI for Physics Book in PDF, ePub and Kindle
Written in accessible language without mathematical formulas, this short book provides an overview of the wide and varied applications of artificial intelligence (AI) across the spectrum of physical sciences. Focusing in particular on AI's ability to extract patterns from data, known as machine learning (ML), the book includes a chapter on important machine learning algorithms and their respective applications in physics. It then explores the use of ML across a number of important sub-fields in more detail, ranging from particle, molecular and condensed matter physics, to astrophysics, cosmology and the theory of everything. The book covers such applications as the search for new particles and the detection of gravitational waves from the merging of black holes, and concludes by discussing what the future may hold.
Author | : Daniel A. Roberts |
Publisher | : Cambridge University Press |
Total Pages | : 473 |
Release | : 2022-05-26 |
Genre | : Computers |
ISBN | : 1316519333 |
Download The Principles of Deep Learning Theory Book in PDF, ePub and Kindle
This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
Author | : Martin Erdmann |
Publisher | : World Scientific |
Total Pages | : 340 |
Release | : 2021-06-25 |
Genre | : Science |
ISBN | : 9811237476 |
Download Deep Learning For Physics Research Book in PDF, ePub and Kindle
A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter optimization is sufficient to jump-start deep learning. Adopting a pragmatic approach, basic and advanced applications in physics research are described. Also offered are simple hands-on exercises for implementing deep networks for which python code and training data can be downloaded.
Author | : Denis Perret-gallix |
Publisher | : World Scientific |
Total Pages | : 802 |
Release | : 1992-09-04 |
Genre | : Science |
ISBN | : 981455426X |
Download New Computing Techniques In Physics Research Ii - Proceedings Of The Second International Workshop On Software Engineering Artificial Intelligence And Expert Systems In High Energy And Nuclear Physics Book in PDF, ePub and Kindle
A vivid example of the growing need for frontier physics experiments to make use of frontier technology is in the field of Artificial Intelligence (AI) and related themes.By AI we are referring here to the use of computers to deal with complex objects in an environment based on specific rules (Symbolic Manipulation), to assist groups of developers in the design, coding and maintenance of large packages (Software Engineering), to mimic human reasoning and strategy with knowledge bases to make a diagnosis of equipment (Expert Systems) or to implement a model of the brain to solve pattern recognition problems (Neural Networks). These techniques, developed some time ago by AI researchers, are confronted by down-to-earth problems arising in high-energy and nuclear physics. However, similar situations exist in other 'big sciences' such as space research or plasma physics, and common solutions can be applied.The magnitude and complexity of the experiments on the horizon for the end of the century clearly call for the application of AI techniques. Solutions are sought through international collaboration between research and industry.
Author | : K H Becks |
Publisher | : World Scientific |
Total Pages | : 684 |
Release | : 1994-02-04 |
Genre | : |
ISBN | : 9814551708 |
Download New Computing Techniques In Physics Research Iii - Proceedings Of The 3rd International Workshop On Software Engineering, Ai And Expert Systems For High Energy And Nuclear Physics Book in PDF, ePub and Kindle
No basic or applied physics research can be done nowadays without the support of computing systems, ranging from cheap personal computers to large multi-user mainframes. Some research fields like high energy physics would not exist if computers had not been invented. Departing from the more conventional numerical applications, this series of workshops has been initiated to focus on Artificial Intelligence (AI) related developments, such as symbolic manipulation for lengthy and involved algebraic computations, software engineering to assist groups of developers in the design, coding and maintenance of large packages, expert systems to mimic human reasoning and strategy in the diagnosis of equipment or neural networks to implement a model of the brain to solve pattern recognition problems. These techniques, developed some time ago by AI researchers, are confronted by down-to-earth problems arising in high-energy and nuclear physics. All this and more are covered in these proceedings.
Author | : Karl-Heinz Becks |
Publisher | : World Scientific Publishing Company Incorporated |
Total Pages | : 664 |
Release | : 1994 |
Genre | : Science |
ISBN | : 9789810216993 |
Download New Computing Techniques in Physics Research III Book in PDF, ePub and Kindle
Author | : Olaf Behnke |
Publisher | : John Wiley & Sons |
Total Pages | : 452 |
Release | : 2013-08-30 |
Genre | : Science |
ISBN | : 3527653430 |
Download Data Analysis in High Energy Physics Book in PDF, ePub and Kindle
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/
Author | : D. A. Edwards |
Publisher | : John Wiley & Sons |
Total Pages | : 304 |
Release | : 2008-11-20 |
Genre | : Science |
ISBN | : 3527617280 |
Download An Introduction to the Physics of High Energy Accelerators Book in PDF, ePub and Kindle
The first half deals with the motion of a single particle under the influence of electronic and magnetic fields. The basic language of linear and circular accelerators is developed. The principle of phase stability is introduced along with phase oscillations in linear accelerators and synchrotrons. Presents a treatment of betatron oscillations followed by an excursion into nonlinear dynamics and its application to accelerators. The second half discusses intensity dependent effects, particularly space charge and coherent instabilities. Includes tables of parameters for a selection of accelerators which are used in the numerous problems provided at the end of each chapter.
Author | : Akinori Tanaka |
Publisher | : Springer Nature |
Total Pages | : 207 |
Release | : 2021-03-24 |
Genre | : Science |
ISBN | : 9813361085 |
Download Deep Learning and Physics Book in PDF, ePub and Kindle
What is deep learning for those who study physics? Is it completely different from physics? Or is it similar? In recent years, machine learning, including deep learning, has begun to be used in various physics studies. Why is that? Is knowing physics useful in machine learning? Conversely, is knowing machine learning useful in physics? This book is devoted to answers of these questions. Starting with basic ideas of physics, neural networks are derived naturally. And you can learn the concepts of deep learning through the words of physics. In fact, the foundation of machine learning can be attributed to physical concepts. Hamiltonians that determine physical systems characterize various machine learning structures. Statistical physics given by Hamiltonians defines machine learning by neural networks. Furthermore, solving inverse problems in physics through machine learning and generalization essentially provides progress and even revolutions in physics. For these reasons, in recent years interdisciplinary research in machine learning and physics has been expanding dramatically. This book is written for anyone who wants to learn, understand, and apply the relationship between deep learning/machine learning and physics. All that is needed to read this book are the basic concepts in physics: energy and Hamiltonians. The concepts of statistical mechanics and the bracket notation of quantum mechanics, which are explained in columns, are used to explain deep learning frameworks. We encourage you to explore this new active field of machine learning and physics, with this book as a map of the continent to be explored.