Relative Entropy on Euclidean Space: the Gibbs Inequality, a Variational Criterion for Finite Relative Entropy, and Closed Sublevel Sets under Weak Convergence
lemmaProbabilitylem:relative-entropy-gibbs-closed-2026aFor probability measures on , relative entropy dominates the Donsker-Varadhan functional int h dnu - log int dgamma for bounded Borel h (Gibbs inequality); conversely a uniform bound on this functional over bounded Lipschitz h implies finite relative entropy with the same bound, so the sublevel sets of relative entropy are closed under weak convergence.
In the setting of Probability Measures on Euclidean Space and Random Vectors: Standing Notation, let be a natural number with and let . Finite relative entropy with respect to and are those of that definition, for the measurable space ; weak convergence is taken in the metric space ; is the exponential function and the natural logarithm. A function is called bounded Lipschitz if it is bounded and Lipschitz with a constant for and the absolute-value metric. For a bounded Borel and , is integrable with respect to by Probability Measures on Euclidean Space and Random Vectors: Standing Notation §measures, and, being a positive real number by claim 1 below, we write
1. (The exponential moment)¶ For every bounded Borel the function is Borel and bounded, and is a positive real number.
2. (Gibbs inequality)¶ Let have finite relative entropy with respect to . Then for every bounded Borel ; in particular .
3. (Variational criterion)¶ Let and be such that for every bounded Lipschitz . Then has finite relative entropy with respect to , and .
4. (Closed sublevel sets)¶ Let , let , and let be a sequence in such that each has finite relative entropy with respect to with , and . Then has finite relative entropy with respect to , and .
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