Phase Transitions in Combinatorial Optimization Problems: Basics, Algorithms and Statistical Mechanics by Alexander K. Hartmann (PDF)

Description

A concise, comprehensive introduction to the topic of statistical physics of combinatorial optimization, bringing together theoretical concepts and algorithms from computer science with analytical methods from physics. The result bridges the gap between statistical physics and combinatorial optimization, investigating problems taken from theoretical computing, such as the vertex-cover problem, with the concepts and methods of theoretical physics. The authors cover rapid developments and analytical methods that are both extremely complex and spread by word-of-mouth, providing all the necessary basics in required detail. Throughout, the algorithms are shown with examples and calculations, while the proofs are given in a way suitable for graduate students, post-docs, and researchers. Ideal for newcomers to this young, multidisciplinary field.

User’s Reviews

Editorial Reviews: Review “This new book is a concise, comprehensive introduction to the topic of statistical physics of combinatorial optimization, bringing together theoretical concepts and algorithms from computer science with analytical methods from physics.” Metall “A well-balanced, concise yet comprehensive introduction, combining statistical physics and combinatorial optimization.” Zeitschrift für Kristallographie From the Back Cover A concise, comprehensive introduction to the topic of statistical physics of combinatorial optimization, bringing together theoretical concepts and algorithms from computer science with analytical methods from physics. The result bridges the gap between statistical physics and combinatorial optimization, investigating problems taken from theoretical computing, such as the vertex-cover problem, with the concepts and methods of theoretical physics. The authors cover rapid developments and analytical methods that are both extremely complex and spread by word-of-mouth, providing all the necessary basics in required detail. Throughout, the algorithms are shown with examples and calculations, while the proofs are given in a way suitable for graduate students, post-docs, and researchers. Ideal for newcomers to this young, multidisciplinary field. About the Author Alexander K. Hartmann, Ph.D. (1998) from the University of Heidelberg, Diplom (1993) from the University of Duisburg. Since January 2003, Head of the Junior Research group “Complex Ground States of Disordered Systems at the University of Göttingen funded by the Volkswagen Stiftung. 1998-2003, Research Assistant in Prof. Annette Zippelius’ group at the University of Göttingen. 2001, Visiting Scientist at the University of California, Santa Cruz and the Ecole Normale Superieure. His research interests are the computer simulations of spin glasses, random field systems and diluted antiferromagnets, gas atoms inside polymer systems, combinatorial optimization problems, random surfaces and surface sputtering, and biophysics (RNA secondary structures and sequence alignment). Martin Weigt, born 1970 in Berlin, Germany; Ph.D. (1998) from Otto-von-Guericke University, Magdeburg, Diplom (1993) from Humboldt University Berlin. Since 1999, Research Assistant in Prof. Annette Zippelius’ group at the University of Göttingen. In 2000, 2001, and 2002, Visiting Scientist at the International Centre of Theoretical Physics, Trieste, Italy. His research interests are statistical mechanics of disordered systems and application in random combinatorics and theoretical computer science. Read more

Reviews from Amazon users which were colected at the time this book was published on the website:

⭐Lieferung erfolgte schnellVerpackung war gutInhalt wie erwartetinhaltlich ist das Buch eine ausgezeichnete Einführung in Anwendungen von Methoden der statistischen Physik für kombinatorische und graphen-theoretische Algorithmen

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