Statistical Physics And Information Theory

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Quantum Information Theory And Quantum Statistics

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Author : Dénes Petz
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-20

Quantum Information Theory And Quantum Statistics written by Dénes Petz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-20 with Science categories.

This concise and readable book addresses primarily readers with a background in classical statistical physics and introduces quantum mechanical notions as required. Conceived as a primer to bridge the gap between statistical physics and quantum information, it emphasizes concepts and thorough discussions of the fundamental notions and prepares the reader for deeper studies, not least through a selection of well chosen exercises.

Information Physics And Computation

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Author : Marc Mézard
language : en
Publisher: Oxford University Press
Release Date : 2009-01-22

Information Physics And Computation written by Marc Mézard and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-22 with Computers categories.

A very active field of research is emerging at the frontier of statistical physics, theoretical computer science/discrete mathematics, and coding/information theory. This book sets up a common language and pool of concepts, accessible to students and researchers from each of these fields.

From Statistical Physics To Statistical Inference And Back

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Author : P. Grassberger
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

From Statistical Physics To Statistical Inference And Back written by P. Grassberger and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.

Physicists, when modelling physical systems with a large number of degrees of freedom, and statisticians, when performing data analysis, have developed their own concepts and methods for making the `best' inference. But are these methods equivalent, or not? What is the state of the art in making inferences? The physicists want answers. More: neural computation demands a clearer understanding of how neural systems make inferences; the theory of chaotic nonlinear systems as applied to time series analysis could profit from the experience already booked by the statisticians; and finally, there is a long-standing conjecture that some of the puzzles of quantum mechanics are due to our incomplete understanding of how we make inferences. Matter enough to stimulate the writing of such a book as the present one. But other considerations also arise, such as the maximum entropy method and Bayesian inference, information theory and the minimum description length. Finally, it is pointed out that an understanding of human inference may require input from psychologists. This lively debate, which is of acute current interest, is well summarized in the present work.

Geometric Structures Of Statistical Physics Information Geometry And Learning

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Author : Frédéric Barbaresco
language : en
Publisher: Springer Nature
Release Date : 2021-06-27

Geometric Structures Of Statistical Physics Information Geometry And Learning written by Frédéric Barbaresco and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-27 with Mathematics categories.

Machine learning and artificial intelligence increasingly use methodological tools rooted in statistical physics. Conversely, limitations and pitfalls encountered in AI question the very foundations of statistical physics. This interplay between AI and statistical physics has been attested since the birth of AI, and principles underpinning statistical physics can shed new light on the conceptual basis of AI. During the last fifty years, statistical physics has been investigated through new geometric structures allowing covariant formalization of the thermodynamics. Inference methods in machine learning have begun to adapt these new geometric structures to process data in more abstract representation spaces. This volume collects selected contributions on the interplay of statistical physics and artificial intelligence. The aim is to provide a constructive dialogue around a common foundation to allow the establishment of new principles and laws governing these two disciplines in a unified manner. The contributions were presented at the workshop on the Joint Structures and Common Foundation of Statistical Physics, Information Geometry and Inference for Learning which was held in Les Houches in July 2020. The various theoretical approaches are discussed in the context of potential applications in cognitive systems, machine learning, signal processing.

E T Jaynes

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Author : Edwin T. Jaynes
language : en
Publisher: Springer Science & Business Media
Release Date : 1989-04-30

E T Jaynes written by Edwin T. Jaynes and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989-04-30 with Language Arts & Disciplines categories.

The first six chapters of this volume present the author's 'predictive' or information theoretic' approach to statistical mechanics, in which the basic probability distributions over microstates are obtained as distributions of maximum entropy (Le. , as distributions that are most non-committal with regard to missing information among all those satisfying the macroscopically given constraints). There is then no need to make additional assumptions of ergodicity or metric transitivity; the theory proceeds entirely by inference from macroscopic measurements and the underlying dynamical assumptions. Moreover, the method of maximizing the entropy is completely general and applies, in particular, to irreversible processes as well as to reversible ones. The next three chapters provide a broader framework - at once Bayesian and objective - for maximum entropy inference. The basic principles of inference, including the usual axioms of probability, are seen to rest on nothing more than requirements of consistency, above all, the requirement that in two problems where we have the same information we must assign the same probabilities. Thus, statistical mechanics is viewed as a branch of a general theory of inference, and the latter as an extension of the ordinary logic of consistency. Those who are familiar with the literature of statistics and statistical mechanics will recognize in both of these steps a genuine 'scientific revolution' - a complete reversal of earlier conceptions - and one of no small significance.

Information Theory And Quantum Physics

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Author : Herbert S. Green
language : en
Publisher: Springer Science & Business Media
Release Date : 2000

Information Theory And Quantum Physics written by Herbert S. Green and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.

In this book, H. S. Green, a former student of Max Born and well known as an author in physics and in philosophy of science, presents an individual and modern approach to theoretical physics and related fundamental problems. Starting from first principles, the links between physics and information science are unveiled step by step: modern information theory and the classical theory of the Turing machine are combined to create a new interpretation of quantum computability, which is then applied to field theory, gravitation and submicroscopic measurement theory and culminates in a detailed examination of the role of the conscious observer in physical measurements. The result is a highly readable book that unifies a wide range of scientific knowledge and is essential reading for all scientists and philosophers of science interested in the interpretation and the implications of the interaction between information science and basic physical theories.

Molecular Dynamics Simulations In Statistical Physics Theory And Applications

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Author : Hiqmet Kamberaj
language : en
Publisher: Springer Nature
Release Date : 2020-03-20

Molecular Dynamics Simulations In Statistical Physics Theory And Applications written by Hiqmet Kamberaj and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-20 with Science categories.

This book presents computer simulations using molecular dynamics techniques in statistical physics, with a focus on macromolecular systems. The numerical methods are introduced in the form of computer algorithms and can be implemented in computers using any desired computer programming language, such as Fortran 90, C/C++, and others. The book also explains how some of these numerical methods and their algorithms can be implemented in the existing computer programming software of macromolecular systems, such as the CHARMM program. In addition, it examines a number of advanced concepts of computer simulation techniques used in statistical physics as well as biological and physical systems. Discussing the molecular dynamics approach in detail to enhance readers understanding of the use of this method in statistical physics problems, it also describes the equations of motion in various statistical ensembles to mimic real-world experimental conditions. Intended for graduate students and research scientists working in the field of theoretical and computational biophysics, physics and chemistry, the book can also be used by postgraduate students of other disciplines, such as applied mathematics, computer sciences, and bioinformatics. Further, offering insights into fundamental theory, it as a valuable resource for expert practitioners and programmers and those new to the field.

Statistical Physics Of Spin Glasses And Information Processing

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Author : Hidetoshi Nishimori
language : en
Publisher: Clarendon Press
Release Date : 2001

Statistical Physics Of Spin Glasses And Information Processing written by Hidetoshi Nishimori and has been published by Clarendon Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Computers categories.

Spin glasses are magnetic materials. Statistical mechanics, a subfield of physics, has been a powerful tool to theoretically analyse various unique properties of spin glasses. A number of new analytical techniques have been developed to establish a theory of spin glasses. Surprisingly, these techniques have turned out to offer new tools and viewpoints for the understanding of information processing problems, including neural networks, error-correcting codes, image restoration, and optimization problems. This book is one of the first publications of the past ten years that provide a broad overview of this interdisciplinary field. Most of the book is written in a self-contained manner, assuming only a general knowledge of statistical mechanics and basic probability theory. It provides the reader with a sound introduction to the field and to the analytical techniques necessary to follow its most recent developments

Statistical Physics Of Particles

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Author : Mehran Kardar
language : en
Publisher: Cambridge University Press
Release Date : 2007-06-07

Statistical Physics Of Particles written by Mehran Kardar and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-06-07 with Science categories.

Statistical physics has its origins in attempts to describe the thermal properties of matter in terms of its constituent particles, and has played a fundamental role in the development of quantum mechanics. Based on lectures taught by Professor Kardar at MIT, this textbook introduces the central concepts and tools of statistical physics. It contains a chapter on probability and related issues such as the central limit theorem and information theory, and covers interacting particles, with an extensive description of the van der Waals equation and its derivation by mean field approximation. It also contains an integrated set of problems, with solutions to selected problems at the end of the book and a complete set of solutions is available to lecturers on a password protected website at www.cambridge.org/9780521873420. A companion volume, Statistical Physics of Fields, discusses non-mean field aspects of scaling and critical phenomena, through the perspective of renormalization group.

Concentration Of Measure Inequalities In Information Theory Communications And Coding

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Author : Maxim Raginsky
language : en
Publisher:
Release Date : 2014

Concentration Of Measure Inequalities In Information Theory Communications And Coding written by Maxim Raginsky and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014 with Computers categories.

Concentration of Measure Inequalities in Information Theory, Communications, and Coding focuses on some of the key modern mathematical tools that are used for the derivation of concentration inequalities, on their links to information theory, and on their various applications to communications and coding.