Overview

The first comprehensive graduate-level introduction to stochastic thermodynamicsStochastic thermodynamics is a well-defined subfield of statistical physics that aims to interpret thermodynamic concepts for systems, ranging in size from a few to hundreds of nanometers, the behavior of which is inherently random due to thermal fluctuations. This growing field therefore describes the nonequilibrium dynamics of small systems, such as artificial nanodevices and biological molecular machines, which are of increasing scientific and technological relevance.This textbook provides an up-to-date pedagogical introduction to stochastic thermodynamics, guiding readers from basic concepts in statistical physics, probability theory, and thermodynamics to the most recent developments in the field. Gradually building up to more advanced material, the authors consistently prioritize simplicity and clarity over exhaustiveness and focus on the development of readers' physical insight over mathematical formalism. This approach allows the reader to grow as the book proceeds, helping interested young scientists to enter the field with less effort and to contribute to its ongoing vibrant development. Chapters provide exercises to complement and reinforce learning.Appropriate for graduate students in physics and biophysics, as well as researchers, Stochastic Thermodynamics serves as an excellent initiation to this rapidly evolving field.Emphasizes a pedagogical approach to the subjectHighlights connections with the thermodynamics of informationPays special attention to molecular biophysics applicationsPrivileges physical intuition over mathematical formalismSolutions manual available on request for instructors adopting the book in a course

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Luca Peliti is deputy director of the Santa Marinella Research Institute and professor emeritus of statistical mechanics at the University of Naples Federico II. He is the author of Statistical Mechanics in a Nutshell (Princeton). Simone Pigolotti is associate professor at the Okinawa Institute of Science and Technology, where he leads the Biological Complexity Unit.

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