Testing the Binary Rank with Polynomial Query Complexity

2026-09-09

AI Summary

本文提出了一种具有多项式查询复杂度的自适应双边误差测试算法，用于检测0,1矩阵的二进制秩，并能进一步找到该矩阵的一个近似二进制分解。

Abstract

We provide an adaptive two-sided error testing algorithm for the binary rank of a $0,1$ matrix $M$ with query complexity $O(d^3\log(d+1)/ε^2)$, where $d$ is the tested binary rank bound and $ε$ is the distance parameter. This answers an open question posed by Parnas, Ron and Shraibman~\cite{parnas2021property}, who asked whether the binary rank can be tested with query complexity polynomial in $d$ and $1/ε$. Furthermore, our testing algorithm can be used to find an approximate binary decomposition of $M$ with an additional $d(n+m)$ queries. That is, under the promise that the binary rank of $M$ is at most $d$, we show how to find, with probability at least $5/6$, two $0,1$ matrices $A',B'$ such that $M' = A' \cdot B'$ is a $0,1$ matrix which differs from $M$ on at most an $O(ε)$ fraction of its entries.

Problem

• binary rank
• polynomial query complexity
• testing algorithm

Innovation

• binary rank
• polynomial query complexity
• approximate binary decomposition