Stochastic analysis of Beckner's and related functional inequalities
arXiv:2604.12462
Abstract
Beckner's inequality is a family of inequalities that interpolates the two fundamental functional inequalities, the logarithmic Sobolev and Poincaré's inequalities. It is parametrized by exponent and it implies the logarithmic Sobolev inequality as and agrees with Poincaré's inequality when . In this paper, employing a stochastic method, we prove an improvement of Beckner's inequality under the Gaussian measure when ; in particular, when , 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 Hölder-type inequality that holds among the entropy, variance and related functionals.
27 pages. An unnecessary summation is removed from the last section