Log-Sobolev KLS conjecture

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Let μ\mu be a log-concave probability measure on Rn\mathbb R^n, and let ∥f∥ψ2(μ)\|f\|_{\psi_2(\mu)} denote the sub-Gaussian Orlicz norm defined by the best constant CC such that

μ(∣f∣≥r)≤2exp⁡(−r2C2).\mu(|f|\geq r)\leq 2\exp\left(-\frac{r^2}{C^2}\right).

Let DnD_n be the largest log-Sobolev constant among log-concave measures satisfying ∥x⋅θ∥ψ2(μ)≤1\|x\cdot\theta\|_{\psi_2(\mu)}\leq 1 for every direction θ\theta.

Log-Sobolev KLS conjecture.

Dn=O(1).D_n=O(1).

Equivalently, in the log-concave setting, the log-Sobolev constant should be bounded by the largest squared ψ2\psi_2-norm of a linear function. This is presented as the log-Sobolev analogue of the KLS conjecture; the source does not specify whether it has been resolved.

References

Primary source

Bo'az Klartag and Joseph Lehec, “Isoperimetric inequalities in high-dimensional convex sets”, arXiv:2406.01324 (2024).

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