From Complex to Simple

Interdisciplinary Stochastic Models

Nonfiction, Science & Nature, Science, Physics, Mathematical Physics, Other Sciences, Applied Sciences, General Physics
Cover of the book From Complex to Simple by Dan A. Mazilu, Irina Mazilu, H. Thomas Williams, Morgan & Claypool Publishers
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Author: Dan A. Mazilu, Irina Mazilu, H. Thomas Williams ISBN: 9781643271194
Publisher: Morgan & Claypool Publishers Publication: August 24, 2018
Imprint: IOP Concise Physics Language: English
Author: Dan A. Mazilu, Irina Mazilu, H. Thomas Williams
ISBN: 9781643271194
Publisher: Morgan & Claypool Publishers
Publication: August 24, 2018
Imprint: IOP Concise Physics
Language: English

This book presents simple interdisciplinary stochastic models meant as a gentle introduction to the field of non-equilibrium statistical physics. It focuses on the analysis of two-state models with cooperative effects, which are versatile enough to be applied to many physical and social systems. The book also explores a variety of mathematical techniques to solve the master equations that govern these models: matrix theory, empty-interval methods, mean field theory, a quantum approach, and mapping onto classical Ising models. The models discussed are at the confluence of nanophysics, biology, mathematics, and the social sciences and provide a pedagogical path toward understanding the complex dynamics of particle self-assembly with the tools of statistical physics.

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This book presents simple interdisciplinary stochastic models meant as a gentle introduction to the field of non-equilibrium statistical physics. It focuses on the analysis of two-state models with cooperative effects, which are versatile enough to be applied to many physical and social systems. The book also explores a variety of mathematical techniques to solve the master equations that govern these models: matrix theory, empty-interval methods, mean field theory, a quantum approach, and mapping onto classical Ising models. The models discussed are at the confluence of nanophysics, biology, mathematics, and the social sciences and provide a pedagogical path toward understanding the complex dynamics of particle self-assembly with the tools of statistical physics.

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