Crooks fluctuation theorem 2026-10-14
For a system coupled to a thermal reservoir at fixed temperature , prepare the forward process in the initial canonical ensemble and the reverse process in the final control parameter's canonical ensemble. Reverse the protocol, assume microscopic reversibility and matching path probability support, and count as work done on the system. With Helmholtz free energy difference and ,The final forward distribution need not already be in thermal equilibrium. Its reverse preparation is prescribed equilibrium preparation, rather than the actual forward final distribution used in finite trajectory entropy production. Thus the paired path logarithm is dissipated work in thermal units, not automatically the instantaneous total stochastic entropy production at the end of an arbitrary driven protocol. [ref]
The Entropy Production Fluctuation Theorem and the Nonequilibrium Work Relation for Free Energy Differences by Gavin E. Crooks. Crooks, 1999, Eqs. (5)–(7), (9)–(11): reversal, equilibrium weights and work relation
[ref]Entropy production along a stochastic trajectory and an integral fluctuation theorem by Udo Seifert. Seifert, 2005, Eq. (19) and following paragraph: actual final distribution versus final equilibrium distribution
Gavin E. Crooks 2026-10-13
Jarzynski equality 2026-10-14
Integrating the Crooks fluctuation theorem over work and using normalization of the reverse probability distribution givesConsequently Jensen's inequality gives . Some realizations may nevertheless have . This is a work relation with equilibrium endpoint preparations, while the integral fluctuation theorem for total entropy production uses the actual final forward distribution. [ref]
The Entropy Production Fluctuation Theorem and the Nonequilibrium Work Relation for Free Energy Differences by Gavin E. Crooks. Crooks, 1999, Eq. (3) and derivation from Eqs. (10)–(11)
Microscopic reversibility 2026-10-05
For an equilibrium process, a path and its physically time-reversed path have equal probability after including their equilibrium starting weights. Conditional on their endpoints, this meansThis is the path version of detailed balance. A time-even order parameter is read backward without changing sign, while a transport flux changes sign. The Onsager--Machlup path probability implements this reversal in a coarse-grained stochastic description.