From Complex to Simple
Interdisciplinary Stochastic Models
Nonfiction, Science & Nature, Science, Physics, Mathematical Physics, Other Sciences, Applied Sciences, General Physics
| 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.
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.
