Eigenvalue Bounds for Symmetric Markov Chains on Multislices With Applications

We consider random walks on ``balanced multislices'' of any ``grid'' that respects the ``symmetries'' of the grid, and show that a broad class of such walks are good spectral expanders. (A grid is a set of points of the form $\mathcal{S}^n$ for finite $\mathcal{S}$, and a balanced multi-slice is the subset that contains an equal number of coordinates taking every value in $\mathcal{S}$. A walk respects symmetries if the probability of going from $u = (u_1,\ldots,u_n)$ to $v = (v_1,\ldots,v_n)$ is invariant under simultaneous permutations of the coordinates of $u$ and $v$.) Our main theorem shows that, under some technical conditions, every such walk where a single step leads to an almost $\mathcal{O}(1)$-wise independent distribution on the next state, conditioned on the previous state, satisfies a non-trivially small singular value bound. We give two applications of our theorem to error-correcting codes: (1) We give an analog of the Ore-DeMillo-Lipton-Schwartz-Zippel lemma for polynomials, and junta-sums, over balanced multislices. (2) We also give a local list-correction algorithm for $d$-junta-sums mapping an arbitrary grid $\mathcal{S}^n$ to an Abelian group, correcting from a near-optimal $(\frac{1}{|\mathcal{S}|^{d}} - \varepsilon)$ fraction of errors for every $\varepsilon > 0$, where a $d$-junta-sum is a sum of (arbitrarily many) $d$-juntas (and a $d$-junta is a function that depends on only $d$ of the $n$ variables). Our proofs are obtained by exploring the representation theory of the symmetric group and merging it with some careful spectral analysis.