Poincaré and Log–Sobolev Inequalities for Mixtures

Author:

Schlichting AndréORCID

Abstract

This work studies mixtures of probability measures on R n and gives bounds on the Poincaré and the log–Sobolev constants of two-component mixtures provided that each component satisfies the functional inequality, and both components are close in the χ 2 -distance. The estimation of those constants for a mixture can be far more subtle than it is for its parts. Even mixing Gaussian measures may produce a measure with a Hamiltonian potential possessing multiple wells leading to metastability and large constants in Sobolev type inequalities. In particular, the Poincaré constant stays bounded in the mixture parameter, whereas the log–Sobolev may blow up as the mixture ratio goes to 0 or 1. This observation generalizes the one by Chafaï and Malrieu to the multidimensional case. The behavior is shown for a class of examples to be not only a mere artifact of the method.

Publisher

MDPI AG

Subject

General Physics and Astronomy

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. An MMSE Lower Bound via Poincaré Inequality;2022 IEEE International Symposium on Information Theory (ISIT);2022-06-26

2. Dimension-free log-Sobolev inequalities for mixture distributions;Journal of Functional Analysis;2021-12

3. Entropy and Information Inequalities;Entropy;2020-03-12

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