
Statistical mechanics is our tool for deriving the laws that emerge from complex systems. Sethna's text distills the subject to be accessible to those in all realms of science and engineering — avoiding extensive use of quantum mechanics, thermodynamics, and molecular physics. Statistical mechanics explains how bacteria search for food, and how DNA replication is proof-read in biology; optimizes data compression, and explains transitions in complexity in computer science; explains the onset of chaos, and launched random matrix theory in mathematics; addresses extreme events in engineering; and models pandemics and language usage in the social sciences. Sethna's exercises introduce physicists to these triumphs and a hundred others — broadening the horizons of scholars both practicing and nascent. Flipped classrooms and remote learning can now rely on 33 pre-class exercises that test reading comprehension (Emergent vs. fundamental; Weirdness in high dimensions; Aging, entropy and DNA), and 70 in-class activities that illuminate and broaden knowledge (Card shuffling; Human correlations; Crackling noises). Science is awash in information, providing ready access to definitions, explanations, and pedagogy. Sethna's text focuses on the tools we use to create new laws, and on the fascinating simple behavior in complex systems that statistical mechanics explains.
This text investigates how statistical mechanics serves as a foundational tool for deriving emergent laws across diverse complex systems. James P. Sethna, a professor of physics, presents a pedagogical framework that prioritizes accessibility by minimizing reliance on traditional prerequisites like advanced quantum mechanics or molecular physics. The book argues that statistical mechanics provides a universal language for modeling phenomena ranging from biological processes and computer science algorithms to social science trends and engineering challenges.
What You Will Find
Scope Limits
Experts and educators frequently cite this text as a modern, interdisciplinary approach to statistical mechanics that successfully bridges the gap between physics and other scientific domains. Readers often note the effectiveness of the active learning exercises in reinforcing complex concepts for both students and practitioners.
Page Count:
496
Publication Date:
2021-01-01
Publisher:
OUP Oxford
ISBN-10:
0192634534
ISBN-13:
9780192634535
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