Statistical mechanics, structure of matter Rigorous equilibrium theory Theorem
Dobrushin–Lanford–Ruelle equations
Builds on Gibbs measureProbability measureConditional expectationWeak convergence of measures
Statement
Let be a finite set and with the product topology and Borel -algebra. Let be an interaction: runs over finite subsets of , and depends only on the spins in . Assume , and let . For finite and , let be the configuration equal to on and to off . Put and A probability measure on satisfies the DLR equations if, for every finite and every , for -almost every . Here is the -algebra generated by the spins off , and the left side is a conditional probability. Let be the set of these measures, the Gibbs measures for .
- is nonempty, convex and compact for the weak topology.
- For each , every weak limit point of , along cubes , lies in .
- The extreme points of are exactly the measures in that are trivial on the tail -algebra.
Remarks
Proof idea: summability makes continuous, which lets the DLR equations pass to weak limits; compactness of then gives limit points. The kernels are consistent: for , and this is why finite-volume measures with boundary conditions converge to solutions. Example: the Ising model on with and large has two different limits, with all-plus and all-minus boundary conditions, so has more than one element. In dimension one with a translation-invariant finite-range interaction, has exactly one element for every .
Going deeper
For a student
The DLR approach, due to Dobrushin and to Lanford and Ruelle in the late 1960s, separates local rules from global behaviour. The local rules always have solutions, but there can be several, and their number is the mathematical meaning of phase coexistence. Extreme Gibbs measures are the pure phases, and every Gibbs measure is a unique mixture of them. The Dobrushin uniqueness criterion gives a condition for a unique solution, and the Gibbs variational principle characterizes the translation-invariant ones.
Reading path
To understand this page from the ground up, read these 5 pages in order. The foundations come first.
Show the path as a graph
- no evidence level
- Conditional expectation concept
- Gibbs measure concept
- Probability measure concept
- Weak convergence of measures concept
- Dobrushin–Lanford–Ruelle equations statement
Further reading
About this page
| Tag | ETPFR89C87 |
|---|---|
| URI | m2://ETPFR89C87 |
| Kind | statement, theorem |
| Writing | W0 stub |
| MSC | 82B05, 82B20, 60K35 |
| Status | This copy of the site has no build data. Run m2 status ETPFR89C87. |
| About | Gibbs measure |
| Uses | Gibbs measure, Probability measure, Conditional expectation, Weak convergence of measures |
| Changed | 3 November 2026 |
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