Agreement testing theorems on layered set systems

TL;DR

This paper develops a new framework for agreement testing on layered set systems, extending previous high-dimensional expansion results to broader classes including matroids and Grassmann posets, with a novel random walk technique.

Contribution

It introduces a layered subset framework and a complement random walk, broadening agreement testing applicability beyond simplicial complexes and low-degree polynomials.

Findings

Agreement tests for high dimensional expanders in all dimensions.

Extension of agreement testing to matroids and neighborhood complexes.

Introduction of the complement random walk with superior expansion properties.

Abstract

We introduce a framework of layered subsets, and give a sufficient condition for when a set system supports an agreement test. Agreement testing is a certain type of property testing that generalizes PCP tests such as the plane vs. plane test. Previous work has shown that high dimensional expansion is useful for agreement tests. We extend these results to more general families of subsets, beyond simplicial complexes. These include - Agreement tests for set systems whose sets are faces of high dimensional expanders. Our new tests apply to all dimensions of complexes both in case of two-sided expansion and in the case of one-sided partite expansion. This improves and extends an earlier work of Dinur and Kaufman (FOCS 2017) and applies to matroids, and potentially many additional complexes. - Agreement tests for set systems whose sets are neighborhoods of vertices in a high dimensional expander. This family resembles the expander neighborhood family used in the gap-amplification proof of the PCP theorem. This set system is quite natural yet does not sit in a simplicial complex, and demonstrates some versatility in our proof technique. - Agreement tests on families of subspaces (also known as the Grassmann poset). This extends the classical low degree agreement tests beyond the setting of low degree polynomials. Our analysis relies on a new random walk on simplicial complexes which we call the ``complement random walk'' and which may be of independent interest. This random walk generalizes the non-lazy random walk on a graph to higher dimensions, and has significantly better expansion than previously-studied random walks on simplicial complexes.