Stochastic analysis of Beckner's and related functional inequalities

Abstract

Beckner's inequality is a family of inequalities that interpolates the two fundamental functional inequalities, the logarithmic Sobolev and Poincar\'e's inequalities. It is parametrized by exponent p∈ (1,2] and it implies the logarithmic Sobolev inequality as p 1 and agrees with Poincar\'e's inequality when p=2. In this paper, employing a stochastic method, we prove an improvement of Beckner's inequality under the Gaussian measure when 4/3 p<2; in particular, when p=3/2, the error bound is expressed in terms of the entropy functional. A similar reasoning to the derivation of the improvement also enables us to obtain a H\"older-type inequality that holds among the entropy, variance and related functionals.

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