A log-Sobolev inequality for the multislice, with applications

TL;DR

This paper establishes a sharp log-Sobolev inequality for the multislice Markov chain, leading to significant results in isoperimetry, expansion, and combinatorial theorems within the multislice setting.

Contribution

It introduces a new sharp log-Sobolev inequality for the multislice and derives multiple combinatorial and isoperimetric consequences.

Findings

Sharp bound on the log-Sobolev constant for the multislice.

Derived KKL, Friedgut Junta, and Nisan--Szegedy theorems for the multislice.

Implications for small-set expansion and isoperimetry in the multislice.

Abstract

Let $\kappa \in \mathbb{N}_+^\ell$ satisfy $\kappa_1 + \dots + \kappa_\ell = n$ and let $\mathcal{U}_\kappa$ denote the "multislice" of all strings $u$ in $[\ell]^n$ having exactly $\kappa_i$ coordinates equal to $i$, for all $i \in [\ell]$. Consider the Markov chain on $\mathcal{U}_\kappa$, where a step is a random transposition of two coordinates of $u$. We show that the log-Sobolev constant $\rho_\kappa$ for the chain satisfies $$(\rho_\kappa)^{-1} \leq n \sum_{i=1}^{\ell} \tfrac{1}{2} \log_2(4n/\kappa_i),$$ which is sharp up to constants whenever $\ell$ is constant. From this, we derive some consequences for small-set expansion and isoperimetry in the multislice, including a KKL Theorem, a Kruskal--Katona Theorem for the multislice, a Friedgut Junta Theorem, and a Nisan--Szegedy Theorem.