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Chiral dynamics provides a rigorous and model-independent methodology for making QCD predictions at the confinement scale. This helps particularly in the testing of the standard model. The workshop reported here was focused on theoretical predictions and the measurements of physical processes, analyzing carefully the phenomenology needed to bridge the gap between the two. Besides the lectures, this volume also contains summaries of the working groups on Â-Â-scattering, ÂN-interaction, photo/electro-pion-production, and on chiral anomaly. This book is a thorough review of the state of the art and it addresses researchers as well as graduate students.
The pion plays an outstanding role in nuclear physics as a generator of the nuclear force and as an important part of the nuclear many-body problem. At the same time, pion beams are used as probes to explore the nucleus and its interactions. As pion physics has matured over the years, a rich and diverse variety of phenomena has been uncovered. The aim of this book is to examine the underlying physical picture behind these phenomena in a systematic and coherent way. The authors emphasize the interplay between physical concepts and experimental facts more than the formal tools, which are presented in a series of appendices. The book is directed towards advanced students as well as research workers.
Our understanding of the fundamental processes of the natural world is based to a large extent on partial differential equations (PDEs). The second edition of Partial Differential Equations provides an introduction to the basic properties of PDEs and the ideas and techniques that have proven useful in analyzing them. It provides the student a broad perspective on the subject, illustrates the incredibly rich variety of phenomena encompassed by it, and imparts a working knowledge of the most important techniques of analysis of the solutions of the equations. In this book mathematical jargon is minimized. Our focus is on the three most classical PDEs: the wave, heat and Laplace equations. Advanced concepts are introduced frequently but with the least possible technicalities. The book is flexibly designed for juniors, seniors or beginning graduate students in science, engineering or mathematics.
This book is designed for advanced undergraduate and graduate students in high energy heavy-ion physics. It is relevant for students who will work on topics being explored at RHIC and the LHC. In the first part, the basic principles of these studies are covered including kinematics, cross sections (including the quark model and parton distribution functions), the geometry of nuclear collisions, thermodynamics, hydrodynamics and relevant aspects of lattice gauge theory at finite temperature. The second part covers some more specific probes of heavy-ion collisions at these energies: high mass thermal dileptons, quarkonium and hadronization. The second part also serves as extended examples of concepts learned in the previous part. Both parts contain examples in the text as well as exercises at the end of each chapter.- Designed for students and newcomers to the field- Focuses on hard probes and QCD- Covers all aspects of high energy heavy-ion physics- Includes worked example problems and exercises
Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.