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About sixty years ago, the anomalous magnetic response of certain
magnetic alloys drew the attention of theoretical physicists. It
soon became clear that understanding these systems, now called spin
glasses, would give rise to a new branch of statistical physics. As
physical materials, spin glasses were found to be as useless as
they were exotic. They have nevertheless been recognized as
paradigmatic examples of complex systems with applications to
problems as diverse as neural networks, amorphous solids,
biological molecules, social and economic interactions, information
theory and constraint satisfaction problems.This book presents an
encyclopaedic overview of the broad range of these applications.
More than 30 contributions are compiled, written by many of the
leading researchers who have contributed to these developments over
the last few decades. Some timely and cutting-edge applications are
also discussed. This collection serves well as an introduction and
summary of disordered and glassy systems for advanced
undergraduates, graduate students and practitioners interested in
the topic.
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Statistical Physics, Optimization, Inference, and Message-Passing Algorithms - Lecture Notes of the Les Houches School of Physics: Special Issue, October 2013 (Hardcover)
Florent Krzakala, Federico Ricci Tersenghi, Lenka Zdeborova, Riccardo Zecchina, Eric W. Tramel, …
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R1,945
Discovery Miles 19 450
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Ships in 12 - 17 working days
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In the last decade, there have been an increasing convergence of
interest and methods between theoretical physics and fields as
diverse as probability, machine learning, optimization and
compressed sensing. In particular, many theoretical and applied
works in statistical physics and computer science have relied on
the use of message passing algorithms and their connection to
statistical physics of spin glasses. The aim of this book,
especially adapted to PhD students, post-docs, and young
researchers, is to present the background necessary for entering
this fast developing field.
The book teaches a student to model a scientific problem and write
a computer program in C language to solve that problem. To do that,
the book first introduces the student to the basics of C language,
dealing with all syntactical aspects, but without the pedantic
content of a typical programming language manual. Then the book
describes and discusses many algorithms commonly used in scientific
applications (e.g. searching, graphs, statistics, equation solving,
Monte Carlo methods etc.).This important book fills a gap in
current available bibliography. There are many manuals for
programming in C, but they never explain programming technicalities
to solve a given problem. This book illustrates many relevant
algorithms and shows how to translate them in a working computer
program.
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