What is a Fluctuation Theorem?
No\'e Cuneo, Vojkan Jak\v{s}i\'c, Claude-Alain Pillet, Armen Shirikyan

TL;DR
This book offers a comprehensive review of Fluctuation Relations and Theorems in nonequilibrium statistical mechanics, emphasizing their theoretical foundations, universal symmetry properties, and applications to chaotic dynamics.
Contribution
It provides a unified probabilistic framework for Fluctuation Relations applicable to both deterministic and stochastic systems, including new insights into chaotic dynamics.
Findings
Universal fluctuation relation for time-reversal invariant systems
General formulation of Fluctuation Theorems for various dynamical systems
Application of the framework to concrete physical models
Abstract
This book provides a modern review of Fluctuation Relations and Fluctuation Theorems in nonequilibrium statistical mechanics. It focuses on the pioneering perspectives of Gallavotti and Cohen, according to which a fluctuation theorem describes the statistics of the deviations of entropy production from its expected value. For time-reversal invariant systems, these fluctuations obey a universal (i.e., model-independent) symmetry called the fluctuation relation. The probabilistic framework introduced in the first part of the book allows for a very general formulation of Fluctuation Relations and Theorems for both deterministic and stochastic dynamical systems. The authors further explore models of physical interest, illustrating this framework by concrete applications. The second part of the book focuses on chaotic dynamics. The formulation of two general Fluctuation Theorems, followed by…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Thermodynamics and Statistical Mechanics · Statistical Mechanics and Entropy · Complex Systems and Dynamics
