Stochastic thermodynamics has emerged as a comprehensive theoretical framework for a large class of non-equilibrium systems including molecular motors, biochemical reaction networks, colloidal particles in time-dependent laser traps, and bio-polymers under external forces. This book introduces the topic in a systematic way, beginning with a dynamical perspective on equilibrium statistical physics. Key concepts like the identification of work, heat and entropy production along individual stochastic trajectories are then developed and shown to obey various fluctuation relations beyond the well-established linear response regime. Representative applications are then discussed, including simple models of molecular motors, small chemical reaction networks, active particles, stochastic heat engines and information machines involving Maxwell demons. This book is ideal for graduate students and researchers of physics, biophysics, and physical chemistry, with an interest in non-equilibrium phenomena.

Includes simple, representative applications, demonstrating how to apply theoretical concepts to real, physical systems
Data from key experiments illustrates the interplay between theory and experimental work
Covers advanced topics, including thermodynamically consistent coarse-graining, the path-integral representation of stochastic dynamics, underdamped systems, large deviation theory for extreme fluctuations, martingales, information geometry and the optimization of processes