Many high-energy collider experiments (including the current Large Hadron Collider at CERN) involve the collision of hadrons. Hadrons are composite particles consisting of partons (quarks and gluons), and this means that in any hadron-hadron collision there will typically be multiple collisions of the constituents — i.e. multiple parton interactions (MPI). Understanding the nature of the MPI is important in terms of searching for new physics in the products of the scatters, and also in its own right to gain a greater understanding of hadron structure. This book aims at providing a pedagogical introduction and a comprehensive review of different research lines linked by an involvement of MPI phenomena. It is written by pioneers as well as young leading scientists, and reviews both experimental findings and theoretical developments, discussing also the remaining open issues.

This book features up-to-date technology applications to radiation detection. It synthesises several techniques of and approaches to radiation detection, covering a wide range of applications and addressing a large audience of experts and students.Many of the talks are in fact reviews of particular topics often not covered in standard books and other conferences, for instance, the medical physics section. To present these medical physics talks is crucial, since a large fraction of the community in medical physics are from the particle physics community. The same feature is true for astroparticle and space physics, which are relatively new fields.This book is unique in its scope. Except for IEEE, there is no other conference in the world that presents such a wide coverage of advanced technology applied to particle physics. However, unlike IEEE, more room is made in the book for reviews and general talks.

This volume is a collection of review articles on the most outstanding topics in heavy flavour physics. All the authors have made significant contributions to this field. The book reviews in detail the theoretical structure of heavy flavour physics within the Standard Model and its confrontation with existing experimental data.The physics of the top quark and of the Higgs play an important role in this volume. Beginning with radiative electroweak corrections and their impressive tests at LEP and hadron colliders, the book summarizes the present status of quark mixing, CP violation and rare decays. The dynamics of exclusive D- and B-meson decays, the τ-lepton physics and the newly discovered heavy quark symmetries are discussed in detail. The impact of strong interactions on weak decays is clearly visible in many articles. The physics of heavy flavours at LEP, HERA and hadron colliders constitutes an important part of the book. Another significant topic is the possible role of heavy flavours in the spontaneous symmetry breaking of gauge symmetries. Finally the most recent advances in lattice calculations of the properties of heavy flavours and the lattice studies of the dynamics of heavy flavours are presented.

Presents observational and theoretical papers from world experts addressing the important role in astrophysics of massive stars.

Progress in the application of machine learning (ML) to the physical and life sciences has been rapid. A decade ago, the method was mainly of interest to those in computer science departments, but more recently ML tools have been developed that show significant potential across wide areas of science. There is a growing consensus that ML software, and related areas of artificial intelligence, may, in due course, become as fundamental to scientific research as computers themselves. Yet a perception remains that ML is obscure or esoteric, that only computer scientists can really understand it, and that few meaningful applications in scientific research exist. This book challenges that view. With contributions from leading research groups, it presents in-depth examples to illustrate how ML can be applied to real chemical problems. Through these examples, the reader can both gain a feel for what ML can and cannot (so far) achieve, and also identify characteristics that might make a problem in physical science amenable to a ML approach. This text is a valuable resource for scientists who are intrigued by the power of machine learning and want to learn more about how it can be applied in their own field.