This book describes the fundamentals of particle detectors as well as their applications. Detector development is an important part of nuclear, particle and astroparticle physics, and through its applications in radiation imaging, it paves the way for advancements in the biomedical and materials sciences. Knowledge in detector physics is one of the required skills of an experimental physicist in these fields. The breadth of knowledge required for detector development comprises many areas of physics and technology, starting from interactions of particles with matter, gas- and solid-state physics, over charge transport and signal development, to elements of microelectronics. The book's aim is to describe the fundamentals of detectors and their different variants and implementations as clearly as possible and as deeply as needed for a thorough understanding. While this comprehensive opus contains all the materials taught in experimental particle physics lectures or modules addressing detector physics at the Master's level, it also goes well beyond these basic requirements. This is an essential text for students who want to deepen their knowledge in this field. It is also a highly useful guide for lecturers and scientists looking for a starting point for detector development work.

This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum stimulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

This book deals with diffraction radiation, which implies the boundary problems of electromagnetic radiation theory. Diffraction radiation is generated when a charged particle moves near a target edge at a distance ( – Lorentz factor, – wave length). Diffraction radiation of non-relativistic particles is widely used to design intense emitters in the cm wavelength range. Diffraction radiation from relativistic charged particles is important for noninvasive beam diagnostics and design of free electron lasers based on Smith-Purcell radiation which is diffraction radiation from periodic structures. Different analytical models of diffraction radiation and results of recent experimental studies are presented in this book. The book may also serve as guide to classical electrodynamics applications in beam physics and electrodynamics. It can be of great use for young researchers to develop skills and for experienced scientists to obtain new results.