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.
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).
A unique and comprehensive presentation on modern particle physics which stores the background knowledge on the big open questions beyond the standard model, as the existence of the Higgs-boson, or the nature of Dark Matter and Dark Energy.
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.
Looking for the real state of play in computational many-particle physics? Look no further. This book presents an overview of state-of-the-art numerical methods for studying interacting classical and quantum many-particle systems. A broad range of techniques and algorithms are covered, and emphasis is placed on their implementation on modern high-performance computers. This excellent book comes complete with online files and updates allowing readers to stay right up to date.
Proceedings of the Third IDPASC School, Santiago de Compostela, Spain, January 21 -- February 2, 2013
Author: Carlos Merino
This volume gathers the content of the courses held at the Third IDPASC School, which took place in San Martiño Pinario, Hospederia and Seminario Maior, in the city of Santiago de Compostela, Galiza, Spain, from January 21st to February 2nd, 2013. This school is the annual joint program of the International Doctorate Network in Particle Physics, Astrophysics, and Cosmology (IDPASC). The purpose of the school series is to present doctoral students from different universities and laboratories in Europe and beyond with a broad range of the latest results and current state of the art in the fields of Particle Physics, Astrophysics, and Cosmology, and to further introduce them to both the questions now posed by the potentials of physics and to challenges connected with current and future experiments – in particular, with the newly available energy ranges. Following these guidelines, the content of this third edition of the IDPASC School was jointly planned by the Academic Council and by the network’s International Committee, whose members ensure every year its timely formulation, keeping up with the constant evolution of these fields. The program covers a balanced range of the latest developments in these fields worldwide, with courses offered by internationally acknowledged physicists on the Basic Features of Hadronic Processes, Quantum Chromodynamics, Physics and Technology of ALICE, LHCb Physics-Parity Violation, the Higgs System in and beyond the Standard Model, Higgs Searches at the LHC, Theory and Experiments with Cosmic Rays, Numerical Methods and Data Analysis in Particle Physics, Theoretical Cosmology, and AdS/CFT Correspondence. Most of these courses were complemented by practical and discussion sessions.
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 taken from 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).
The first edition of this classic book has become the authoritative reference for physicists desiring to master the finer points of statistical data analysis. This second edition contains all the important material of the first, much of it unavailable from any other sources. In addition, many chapters have been updated with considerable new material, especially in areas concerning the theory and practice of confidence intervals, including the important Feldman-Cousins method. Both frequentist and Bayesian methodologies are presented, with a strong emphasis on techniques useful to physicists and other scientists in the interpretation of experimental data and comparison with scientific theories. This is a valuable textbook for advanced graduate students in the physical sciences as well as a reference for active researchers.