Data Analysis Techniques for High-Energy Physics PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Data Analysis Techniques for High-Energy Physics PDF full book. Access full book title Data Analysis Techniques for High-Energy Physics by R. Frühwirth. Download full books in PDF and EPUB format.
Author: R. K. Bock Publisher: Cambridge University Press ISBN: 9780521114370 Category : Science Languages : en Pages : 0
Book Description
High-energy physics - the science of the fundamental particles nature - has become one of the most complex and demanding disciplines of natural science. The observation of particle interactions involves the analysis of large and intricate data samples. The very high cost of these experiments makes the full and correct use of the information imperative. Successful interpretation of the data requires the application of advanced mathematical algorithms and computer techniques in all stages of the analysis. The necessary and available techniques of all steps of the analysis have been assembled in a single book. All four authors have had many years' involvement with high-energy physics experiments at CERN, DESY and other particle accelerators around the world. They have written this book both as an introduction and to inform the reader on the most advanced techniques of data analysis in this field. It will be of great value to people involved in experimental research in particle physics, including beginning graduates, computer electronic engineers and senior academics.
Author: Olaf Behnke Publisher: John Wiley & Sons ISBN: 3527653430 Category : Science Languages : en Pages : 440
Book Description
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: Ilya Narsky Publisher: John Wiley & Sons ISBN: 3527677291 Category : Science Languages : en Pages : 459
Book Description
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.
Author: Luca Lista Publisher: Springer ISBN: 3319628402 Category : Science Languages : en Pages : 257
Book Description
This concise set of course-based notes provides the reader with the main concepts and tools needed to perform statistical analyses of experimental data, in particular in the field of high-energy physics (HEP). First, the book provides an introduction to probability theory and basic statistics, mainly intended as a refresher from readers’ advanced undergraduate studies, but also to help them clearly distinguish between the Frequentist and Bayesian approaches and interpretations in subsequent applications. More advanced concepts and applications are gradually introduced, culminating in the chapter on both discoveries and upper limits, as many applications in HEP concern hypothesis testing, where the main goal is often to provide better and better limits so as to eventually be able to distinguish between competing hypotheses, or to rule out some of them altogether. Many worked-out examples will help newcomers to the field and graduate students alike understand the pitfalls involved in applying theoretical concepts to actual data. This new second edition significantly expands on the original material, with more background content (e.g. the Markov Chain Monte Carlo method, best linear unbiased estimator), applications (unfolding and regularization procedures, control regions and simultaneous fits, machine learning concepts) and examples (e.g. look-elsewhere effect calculation).
Author: Claude A. Pruneau Publisher: Cambridge University Press ISBN: 1108267882 Category : Science Languages : en Pages :
Book Description
A comprehensive guide to data analysis techniques for physical scientists, providing a valuable resource for advanced undergraduate and graduate students, as well as seasoned researchers. The book begins with an extensive discussion of the foundational concepts and methods of probability and statistics under both the frequentist and Bayesian interpretations of probability. It next presents basic concepts and techniques used for measurements of particle production cross-sections, correlation functions, and particle identification. Much attention is devoted to notions of statistical and systematic errors, beginning with intuitive discussions and progressively introducing the more formal concepts of confidence intervals, credible range, and hypothesis testing. The book also includes an in-depth discussion of the methods used to unfold or correct data for instrumental effects associated with measurement and process noise as well as particle and event losses, before ending with a presentation of elementary Monte Carlo techniques.
Author: Louis Lyons Publisher: Cambridge University Press ISBN: 1316101630 Category : Science Languages : en Pages :
Book Description
This book, written by a non-statistician for non-statisticians, emphasises the practical approach to those problems in statistics which arise regularly in data analysis situations in nuclear and high-energy physics experiments. Rather than concentrating on formal proofs of theorems, an abundant use of simple examples illustrates the general ideas which are presented, showing the reader how to obtain the maximum information from the data in the simplest manner. Possible difficulties with the various techniques, and pitfalls to be avoided, are also discussed. Based on a series of lectures given by the author to both students and staff at Oxford, this common-sense approach to statistics will enable nuclear physicists to understand better how to do justice to their data in both analysis and interpretation.
Author: Glen Cowan Publisher: Oxford University Press ISBN: 0198501560 Category : Mathematics Languages : en Pages : 218
Book Description
This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental data. Although most of the examples are takenfrom particle physics, the material is presented in a sufficiently general way as to be useful to people from most branches of the physical sciences. The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques,statistical tests, and methods of parameter estimation. The last three chapters are somewhat more specialized than those preceding, covering interval estimation, characteristic functions, and the problem of correcting distributions for the effects of measurement errors (unfolding).
Author: William R. Leo Publisher: Springer Science & Business Media ISBN: 3642579205 Category : Science Languages : en Pages : 385
Book Description
A treatment of the experimental techniques and instrumentation most often used in nuclear and particle physics experiments as well as in various other experiments, providing useful results and formulae, technical know-how and informative details. This second edition has been revised, while sections on Cherenkov radiation and radiation protection have been updated and extended.
Author: R. Frühwirth
Author: R. Frühwirth
Author: R. K. Bock
Author: Olaf Behnke
Author: Ilya Narsky
Author: Luca Lista
Author: Claude A. Pruneau
Author: Rudolf Frühwirth
Author: Louis Lyons
Author: Glen Cowan
Author: William R. Leo