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A Generalized Central Limit Conjecture for Convex Bodies

Published 28 Sep 2019 in math.FA, math.MG, and math.PR | (1909.13127v1)

Abstract: The central limit theorem for convex bodies says that with high probability the marginal of an isotropic log-concave distribution along a random direction is close to a Gaussian, with the quantitative difference determined asymptotically by the Cheeger/Poincare/KLS constant. Here we propose a generalized CLT for marginals along random directions drawn from any isotropic log-concave distribution; namely, for x,yx,y drawn independently from isotropic log-concave densities p,qp,q, the random variable ⟨x,y⟩\langle x,y\rangle is close to Gaussian. Our main result is that this generalized CLT is quantitatively equivalent (up to a small factor) to the KLS conjecture. Any polynomial improvement in the current KLS bound of n<sup>1/4n<sup>{1/4} in R<sup>n\mathbb{R}<sup>n implies the generalized CLT, and vice versa. This tight connection suggests that the generalized CLT might provide insight into basic open questions in asymptotic convex geometry.

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