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The Orthogonal Vectors Conjecture and Non-Uniform Circuit Lower Bounds

Ryan Williams

2024Year
2Citations
2Top-tier citations

Abstract

A line of work has shown how nontrivial uniform algorithms for analyzing circuits can be used to derive non-uniform circuit lower bounds. We show how the non-existence of nontrivial circuit-analysis algorithms can also imply non-uniform circuit lower bounds. Our connections yield new win-win circuit lower bounds, and suggest a potential approach to refuting the Orthogonal Vectors Conjecture in theO(log⁡n)O(\log n)-dimensional case, which would be sufficient for refuting the Strong Exponential Time Hypothesis (SETH). For example, we show that at least one of the following holds: • There is anε>0\varepsilon>0such that for infinitely manynn, read-once 2-DNFs onnnvariables cannot be simulated by non-uniform2εn2^{\varepsilon n}-size depth-two exact threshold circuits. It is already a notorious open problem to prove that the classENPE^{N P}does not have polynomial-size depth-two exact threshold circuits, so such a lower bound would be a significant advance in low-depth circuit complexity. In fact, a stronger lower bound holds in this case: the2n×2n2^n \times 2^nDisjointness Matrix (well-studied in communication complexity) cannot be expressed by a linear combination of2o(n)2^{o(n)}structured matrices that we call “equality matrices”. • For everyc≥1c \geq 1and everyε>0\varepsilon>0, Orthogonal Vectors onnnvectors inclog⁡nc \log ndimensions can be solved inn1+εn^{1+\varepsilon}uniform deterministic time. This case would provide a strong refutation of the Orthogonal Vectors conjecture, and of SETH: for example, CNF-SAT onnnvariables andO(n)O(n)clauses could be solved in2n/2+o(n)2^{n / 2+o(n)}time. Moreover, this case would imply non-uniform circuit lower bounds for the classENPE^{NP}, against Valiant series-parallel circuits. Inspired by this connection, we give evidence from SAT/SMT solvers that the first item (in particular, the Disjointness lower bound) may be false in its full generality. In particular, we present a systematic approach to solving Orthogonal Vectors via constant-sized decompositions of the Disjointness Matrix, which already yields interesting new algorithms. For example, using a linear combination of 6 equality matrices that express26×262^6 \times 2^6Disjointness, we derive anO~(n⋅6d/6)≤O~(n⋅1.35d˙)\tilde{O}\left(n \cdot 6^{d / 6}\right) \leq \tilde{O}\left(n \cdot 1. \dot{35^d}\right)time andn⋅poly⁡(log⁡n,d)n \cdot \operatorname{poly}(\log n, d)space algorithm for Orthogonal Vectors onnnvectors indddimensions. We show similar results for counting pairs of orthogonal vectors.

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