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Gibbs Measures On Cayley Trees (Hardcover)
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Gibbs Measures On Cayley Trees (Hardcover)
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The purpose of this book is to present systematically all known
mathematical results on Gibbs measures on Cayley trees (Bethe
lattices).The Gibbs measure is a probability measure, which has
been an important object in many problems of probability theory and
statistical mechanics. It is the measure associated with the
Hamiltonian of a physical system (a model) and generalizes the
notion of a canonical ensemble. More importantly, when the
Hamiltonian can be written as a sum of parts, the Gibbs measure has
the Markov property (a certain kind of statistical independence),
thus leading to its widespread appearance in many problems outside
of physics such as biology, Hopfield networks, Markov networks, and
Markov logic networks. Moreover, the Gibbs measure is the unique
measure that maximizes the entropy for a given expected energy.The
method used for the description of Gibbs measures on Cayley trees
is the method of Markov random field theory and recurrent equations
of this theory, but the modern theory of Gibbs measures on trees
uses new tools such as group theory, information flows on trees,
node-weighted random walks, contour methods on trees, and nonlinear
analysis. This book discusses all the mentioned methods, which were
developed recently.
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