Artificial Intelligence For High Energy Physics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Intelligence For High Energy Physics write by Paolo Calafiura. This book was released on 2022-01-05. Artificial Intelligence For High Energy Physics available 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.
Deep Learning For Physics Research
Deep Learning For Physics Research - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Learning For Physics Research write by Martin Erdmann. This book was released on 2021-06-25. Deep Learning For Physics Research available 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.
The Principles of Deep Learning Theory
The Principles of Deep Learning Theory - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook The Principles of Deep Learning Theory write by Daniel A. Roberts. This book was released on 2022-05-26. The Principles of Deep Learning Theory available in PDF, EPUB and Kindle. This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
Statistical Analysis Techniques in Particle Physics
Statistical Analysis Techniques in Particle Physics - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Statistical Analysis Techniques in Particle Physics write by Ilya Narsky. This book was released on 2013-10-24. Statistical Analysis Techniques in Particle Physics available in PDF, EPUB and Kindle. Modern analysis of HEP data needs advanced statistical tools to separate signal from background. This is the first book which focuses on machine learning techniques. It will be of interest to almost every high energy physicist, and, due to its coverage, suitable for students.
An Introduction to the Physics of High Energy Accelerators
An Introduction to the Physics of High Energy Accelerators - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook An Introduction to the Physics of High Energy Accelerators write by D. A. Edwards. This book was released on 2008-11-20. An Introduction to the Physics of High Energy Accelerators available 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.
