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Cambridge University Press

Chaos and Coarse Graining in Statistical Mechanics

Chaos and Coarse Graining in Statistical Mechanics

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While statistical mechanics describe the equilibrium state of systems with many degrees of freedom, and dynamical systems explain the irregular evolution of systems with few degrees of freedom, new tools are needed to study the evolution of systems with many degrees of freedom. This book presents the basic aspects of chaotic systems, with emphasis on systems composed by huge numbers of particles. Firstly, the basic concepts of chaotic dynamics are introduced, moving on to explore the role of ergodicity and chaos for the validity of statistical laws, and ending with problems characterized by the presence of more than one significant scale. Also discussed is the relevance of many degrees of freedom, coarse graining procedure, and instability mechanisms in justifying a statistical description of macroscopic bodies. Introducing the tools to characterize the non asymptotic behaviors of chaotic systems, this text will interest researchers and graduate students in statistical mechanics and chaos.

Author: Patrizia Castiglione, Massimo Falcioni, Annick Lesne
Publisher: Cambridge University Press
Published: 08/21/2008
Pages: 280
Binding Type: Hardcover
Weight: 1.49lbs
Size: 9.80h x 7.00w x 0.70d
ISBN: 9780521895934

About the Author
Castiglione, Patrizia: - Patrizia Castiglione is a Researcher at the Institut des Nanosciences de Paris. Her main research topics are dynamical systems theory, quantum and classic chaos, turbulence, and the physics of colours applied to the study of artwork.Falcioni, Massimo: - Massimo Falcioni is a Researcher at the University of Rome 'Sapienza'. His research focuses on elementary particle physics, dynamical systems and statistical mechanics.Lesne, Annick: - Annick Lesne is a Researcher at the Institut des Hautes Etudes Scientifiques. Her research lies in renormalization methods for dynamical systems, non equilibrium statistical physics, and applications of dynamical systems theory and statistical mechanics to biological systems.
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