Statistical mechanics, structure of matter Foundations of equilibrium statistical mechanics Theorem
Gibbs–Bogoliubov inequality
Builds on Canonical ensembleJensen's inequalityExpected value
Statement
Let be a -finite measure space and let . Let be measurable with and . Let be the expected value under the canonical ensemble , and assume . Let and be the free energies. Then with equality if and only if is constant almost everywhere for the measure .
Remarks
Proof idea: , and Jensen's inequality for the convex function gives . Taking of both sides gives the claim. The same inequality holds for Hermitian matrices, with and ; this is the Peierls–Bogoliubov inequality. Example: in mean-field theory one takes to be a sum of independent single-site terms with free parameters. Minimizing the right side over these parameters gives the best such upper bound on . It gives a variational principle: , attained at .
Going deeper
For a student
This inequality is the rigorous basis of mean-field and variational approximations, such as the Curie–Weiss treatment of the Ising model. It is equivalent to the nonnegativity of the Kullback–Leibler divergence between the trial ensemble and the true canonical ensemble. It is also the finite-volume form of the Gibbs variational principle, which characterizes Gibbs measures as maximizers of entropy minus energy.
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
- Canonical ensemble concept
- Convex function definition
- Expected value concept
- Jensen's inequality statement
- Gibbs–Bogoliubov inequality statement
Further reading
About this page
| Tag | WR3RBEH4QQ |
|---|---|
| URI | m2://WR3RBEH4QQ |
| Kind | statement, theorem |
| Writing | W0 stub |
| MSC | 82B05, 82B10, 82B03 |
| Status | This copy of the site has no build data. Run m2 status WR3RBEH4QQ. |
| About | Canonical ensemble |
| Uses | Canonical ensemble, Jensen's inequality, Expected value |
| Changed | 3 November 2026 |
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