Expanders Meet Reed-Muller: Easy Instances of Noisy k-XOR
Jaros{\l}aw B{\l}asiok, Paul Lou, Alon Rosen, Madhu Sudan

TL;DR
This paper constructs explicit graphs with near-optimal expansion where noisy $k$-XOR is solvable in polynomial time, challenging previous conjectures linking expansion to computational hardness.
Contribution
It combines pseudorandomness and coding theory to show that high expansion does not necessarily imply computational hardness in noisy XOR problems.
Findings
Polynomial-time solvability at constant noise rate $rac{1}{3}$ for specific graph families.
Explicit graph families with $M = 2^{O( ext{log}^2 N)}$, $k = ( ext{log} N)^{O(1)}$, and high expansion.
Extension to polynomial-time algorithms at noise rate $ ext{N}^{-c}$ under Reed-Muller code conjectures.
Abstract
In the noisy -XOR problem, one is given and must distinguish between uniform and , where is the adjacency matrix of a -left-regular bipartite graph with variables and constraints, is random, and is noise with rate . Lower bounds in restricted computational models such as Sum-of-Squares and low-degree polynomials are closely tied to the expansion of , leading to conjectures that expansion implies hardness. We show that such conjectures are false by constructing an explicit family of graphs with near-optimal expansion for which noisy -XOR is solvable in polynomial time. Our construction combines two powerful directions of work in pseudorandomness and coding theory that have not been previously put together. Specifically, our graphs are based on the lossless expanders of Guruswami, Umans and…
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