English

Improved Lower Bounds for Testing Triangle-freeness in Boolean Functions via Fast Matrix Multiplication

Computational Complexity 2013-08-08 v1 Data Structures and Algorithms

Abstract

Understanding the query complexity for testing linear-invariant properties has been a central open problem in the study of algebraic property testing. Triangle-freeness in Boolean functions is a simple property whose testing complexity is unknown. Three Boolean functions f1f_1, f2f_2 and f3:F2k{0,1}f_3: \mathbb{F}_2^k \to \{0, 1\} are said to be triangle free if there is no x,yF2kx, y \in \mathbb{F}_2^k such that f1(x)=f2(y)=f3(x+y)=1f_1(x) = f_2(y) = f_3(x + y) = 1. This property is known to be strongly testable (Green 2005), but the number of queries needed is upper-bounded only by a tower of twos whose height is polynomial in 1/\epsislon1 / \epsislon, where \epsislon\epsislon is the distance between the tested function triple and triangle-freeness, i.e., the minimum fraction of function values that need to be modified to make the triple triangle free. A lower bound of (1/ϵ)2.423(1 / \epsilon)^{2.423} for any one-sided tester was given by Bhattacharyya and Xie (2010). In this work we improve this bound to (1/ϵ)6.619(1 / \epsilon)^{6.619}. Interestingly, we prove this by way of a combinatorial construction called \emph{uniquely solvable puzzles} that was at the heart of Coppersmith and Winograd's renowned matrix multiplication algorithm.

Keywords

Cite

@article{arxiv.1308.1643,
  title  = {Improved Lower Bounds for Testing Triangle-freeness in Boolean Functions via Fast Matrix Multiplication},
  author = {Hu Fu and Robert Kleinberg},
  journal= {arXiv preprint arXiv:1308.1643},
  year   = {2013}
}
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