Crooks fluctuation theorem
Setup (forward and reverse protocols)
Consider a system with control parameter (e.g. a trap position, field, volume) driven by a time-dependent protocol for .
- Forward (F): start in equilibrium at with inverse temperature (with the temperature ), typically the canonical ensemble .
- Reverse (R): start in equilibrium at and drive with the time-reversed protocol .
For each realization, define the work (see work distribution ). Let and be the corresponding work probability densities (with respect to the relevant probability measure ).
Let denote the equilibrium free-energy difference at the same (see nonequilibrium free-energy difference and Helmholtz free energy ).
Theorem (Crooks)
Under microreversible dynamics (time-reversal symmetric Hamiltonian dynamics, or Markov dynamics satisfying microscopic reversibility such as detailed balance with a heat bath), the work distributions satisfy
Immediate consequences
Crossing point identifies .
The value where satisfies .Jarzynski follows by integration.
Multiply both sides by and integrate over to obtaini.e. Jarzynski’s equality .
Second-law inequality.
Using Jensen’s inequality,consistent with the second law .
Information-theoretic form (dissipation as relative entropy)
At the level of trajectories (paths), Crooks’ theorem is equivalent to a path-space likelihood ratio
so the mean dissipated work is proportional to a relative entropy between forward and reverse path measures.
Practical note
Crooks’ relation underlies statistically efficient estimators of (e.g. Bennett-type methods) built from both and ; see free-energy difference from nonequilibrium work .