Description
Book Synopsis: Scientists are increasingly finding themselves engaged in research problems that cross the traditional disciplinary lines of physics, chemistry, biology, materials science, and engineering. Because of its broad scope, statistical mechanics is an essential tool for students and more experienced researchers planning to become active in such an interdisciplinary research environment. Powerful computational methods that are based in statistical mechanics allow complex systems to be studied at an unprecedented level of detail. This book synthesizes the underlying theory of statistical mechanics with the computational techniques and algorithms used to solve real-world problems and provides readers with a solid foundation in topics that reflect the modern landscape of statistical mechanics.
Topics covered include detailed reviews of classical and quantum mechanics, in-depth discussions of the equilibrium ensembles and the use of molecular dynamics and Monte Carlo to sample classical and quantum ensemble distributions, Feynman path integrals, classical and quantum linear-response theory, nonequilibrium molecular dynamics, the Langevin and generalized Langevin equations, critical phenomena, techniques for free energy calculations, machine learning models, and the use of these models in statistical mechanics applications.
The book is structured such that the theoretical underpinnings of each topic are covered side by side with computational methods used for practical implementation of the theoretical concepts.
Details
Looking to embark on groundbreaking research that transcends traditional disciplinary boundaries? Look no further than Statistical Mechanics: Theory and Molecular Simulation. With its comprehensive coverage of physics, chemistry, biology, materials science, and engineering, this book is an indispensable resource for both students and seasoned researchers.
What sets this book apart is its convergence of theory and computational methods. By combining the power of statistical mechanics with advanced algorithms, researchers can now study complex systems with unparalleled precision. Dive into the world of molecular dynamics and Monte Carlo simulations to unravel the mysteries of classical and quantum ensembles.
Delve into the pages to discover topics like Feynman path integrals, linear-response theory, nonequilibrium molecular dynamics, critical phenomena, and free energy calculations. With an emphasis on practical implementation, this book equips you with the tools to tackle real-world problems head-on.
But what truly sets Statistical Mechanics: Theory and Molecular Simulation apart is its forward-thinking approach. With chapters dedicated to machine learning models and their applications in statistical mechanics, this book keeps you at the forefront of cutting-edge research.
Ready to take your research to new heights? Don't miss out on the opportunity to explore the ever-expanding field of statistical mechanics. Grab your copy of Statistical Mechanics: Theory and Molecular Simulation today and become an active part of the interdisciplinary research revolution.
Click here to immerse yourself in the world of statistical mechanics!
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