Bøger i Lecture Notes in Physics serien

The first part of this book gives a self-contained and mathematically rigorous exposition of classical conformal symmetry in n dimensions and its quantization in two dimensions. The second part surveys some more advanced topics of conformal field theory.

This open access book bridges a gap between introductory Quantum Field Theory (QFT) courses and state-of-the-art research in scattering amplitudes. It covers the path from basic definitions of QFT to amplitudes, which are relevant for processes in the Standard Model of particle physics. The book begins with a concise yet self-contained introduction to QFT, including perturbative quantum gravity. It then presents modern methods for calculating scattering amplitudes, focusing on tree-level amplitudes, loop-level integrands and loop integration techniques. These methods help to reveal intriguing relations between gauge and gravity amplitudes and are of increasing importance for obtaining high-precision predictions for collider experiments, such as those at the Large Hadron Collider, as well as for foundational mathematical physics studies in QFT, including recent applications to gravitational wave physics.These course-tested lecture notes include numerous exercises with solutions. Requiring only minimal knowledge of QFT, they are well-suited for MSc and PhD students as a preparation for research projects in theoretical particle physics. They can be used as a one-semester graduate level course, or as a self-study guide for researchers interested in fundamental aspects of quantum field theory.

Based on lectures given at a CNRS summer school in France, this book covers many aspects of stellar environments (both observational and theoretical) and offers a broad overview of the field. Finally the chapters of Part III discuss the environments of young or evolved stars, stellar winds, agnetic fields and disks.

This book focuses on one mechanism in black hole physics which has proven to be universal, multifaceted and with a rich phenomenology: rotational superradiance.

This book presents a self-contained introduction to techniques from field theory applied to stochastic and collective dynamics in neuronal networks.

Pitowsky [1] Abstract The basic motivation behind the present text is threefold: To give a new explanation for the emergence of thermodynamics, to investigate the interplay between quantum mechanics and thermodynamics, and to explore possible ext- sions of the common validity range of thermodynamics.

This book provides an introduction to topics in non-equilibrium quantum statistical physics for both mathematicians and theoretical physicists. The quantum kinetic theory developed in the second part is an extension of Boltzmann's classical (non-quantum) kinetic theory of a dilute gas of quantum bosons.

Complex plasmas are dusty plasmas in which the density and electric charges of the dust grains are sufficiently high to induce long-range grain-grain interactions. This book addresses students as well as specialist and nonspecialist researchers with a background in either plasma physics, space sciences or the physics of complex systems.

Introduces various developments in N-body computational astrophysics. This book covers topics such as the classical few-body problem with discussions of resonance, chaos and stability to realistic modeling of star clusters as well as descriptions of codes, algorithms and special hardware for N-body simulations.

The development of telescopes, detectors and satellites has led to a dramatic increase in cosmological data. This book offers the best techniques to extract information from that data and reliable methods to improve our view of the universe.

This book presents the state of the art of quantum cryptography and details how it can be implemented in standard communication infrastructure.

Lectures on LHC Physics

This book offers a detailed guide on the journey towards the minimal supersymmetric standard model down the orbifold road. It takes the viewpoint that the chirality of matter fermions is an essential aspect that orbifold compactification allows to derive from higher-dimensional string theories in a straightforward manner.

Aside from the statement that it should be capable of unifying general relativity and quantum field theory, little is known about the nature of quantum gravity. This book covers non-commutative geometry, space-time discretization and more.

This book provides a comprehensive overview of developments in the field of holographic entanglement entropy. In the first part, the concept of entanglement, and methods for computing it, in quantum field theories is reviewed.

This book contains a selection of lectures from the first Summer School organized by the Center for Functional nanostructures (CFN) at the University of Karlsruhe. The mission of the CFN is to carry out research in the following areas: nanophotonics, nanoelectronics, molecular nanostructures and nanostructured materials.

This volume offers an introduction, in the form of four extensive lectures, to some recent developments in several active topics at the interface between geometry, topology and quantum field theory.

The recent discovery of a type II supernova in the Large Magellanic Cloud provides a rare chance to compare models of stellar evolution and nucleosynthesis directly with observations.

The applications of quantum gravity theory are epoch-making: only such a theory can explain how black holes really behave and where our universe came from. This volume uses accessible models to cover a number of relevant topics including loop quantization.

Introduction to Material Modeling.- Kernel Methods for Quantum Chemistry.- Introduction to Neural Networks.- Building nonparametric n-body force fields using Gaussian process regression.- Machine-learning of atomic-scale properties based on physical principles.- Quantum Machine Learning with Response Operators in Chemical Compound Space.- Physical extrapolation of quantum observables by generalization with Gaussian Processes.- Message Passing Neural Networks.- Learning representations of molecules and materials with atomistic neural networks.- Molecular Dynamics with Neural Network Potentials.- High-Dimensional Neural Network Potentials for Atomistic Simulations.- Construction of Machine Learned Force Fields with Quantum Chemical Accuracy: Applications and Chemical Insights.- Active learning and Uncertainty Estimation.- Machine Learning for Molecular Dynamics on Long Timescales.- Database-driven High-Throughput Calculations and Machine Learning Models for Materials Design.- Polymer Genome: A polymer informatics platform to accelerate polymer discovery.- Bayesian Optimization in Materials Science.- Recommender Systems for Materials Discovery.- Generative Models for Automatic Chemical Design.

This book provides an accessible yet comprehensive description of the application methods of group analysis to integro-differential equations. It offers both fundamental theoretical and algorithmic aspects of these methods and includes instructive examples.

This book is based on Valery Zagrebaev's original papers and lecture materials on nuclear physics with heavy ions, which he prepared and extended through many years for the students of nuclear physics specialties.Th¿ book outlines the main experimental facts on nuclear reactions involving heavy ions at low energies. It focuses on discussions of nuclear physics processes that are a subject of active, modern research and it gives illustrative explanations of these phenomena in the framework of up-to-date theoretical concepts.This textbook is intended for students in physics who have completed a standard course of quantum mechanics and have basic ideas of nuclear physics processes.It is designed as a kind of lifeboat that, at the end of the course, will allow students to navigate the modern scientific literature and to understand the goals and objectives of current, on-going research.

This volume provides an introduction to the state-of-the-art of controlled nanoscale motion in biological and artificial systems. Coverage includes the control and function of protein motors, the physics of non-equilibrium Brownian motion, and the physics and fabrication of synthetic molecular motors.

Distinguishing chaoticity from regularity in deterministic dynamical systems and specifying the subspace of the phase space in which instabilities are expected to occur is of utmost importance in as disparate areas as astronomy, particle physics and climate dynamics.   To address these issues there exists a plethora of methods for chaos detection and predictability. The most commonly employed technique for investigating chaotic dynamics, i.e. the computation of Lyapunov exponents, however, may suffer a number of problems and drawbacks, for example when applied to noisy experimental data.   In the last two decades, several novel methods have been developed for the fast and reliable determination of the regular or chaotic nature of orbits, aimed at overcoming the shortcomings of more traditional techniques. This set of lecture notes and tutorial reviews serves as an introduction to and overview of modern chaos detection and predictability techniquesfor graduate students and non-specialists.   The book covers theoretical and computational aspects of traditional methods to calculate Lyapunov exponents, as well as of modern techniques like the Fast (FLI), the Orthogonal (OFLI) and the Relative (RLI) Lyapunov Indicators, the Mean Exponential Growth factor of Nearby Orbits (MEGNO), the Smaller (SALI) and the Generalized (GALI) Alignment Index and the ¿0-1¿ test for chaos.

The aim of this book is to provide background materials such as string theory, black holes, nuclear physics, condensed-matter physics, and nonequilibrium physics as well as key applications of the AdS/CFT duality in a single volume.