Spectral Norm, Economical Sieve, and Linear Invariance Testing of Boolean Functions

Abstract

Given Boolean functions \( f, g : F2n \-1,+1\ \), we say they are linearly isomorphic if there exists \( A ∈ GLn(F2) \) such that \( f(x)=g(Ax) \) for all \( x \). We study this problem in the tolerant property testing framework under the known--unknown model, where \( g \) is given explicitly and \( f \) is accessible only via oracle queries, meaning the algorithm may adaptively request the value of \( f(x) \) for inputs \( x ∈ F2n \) of its choice. Given parameters \( ε 0 \) and \( ω>0 \), the goal is to distinguish whether there exists \( A ∈ GLn(F2)\) such that the normalized Hamming distance between \( f \) and \( g(Ax) \) is at most \( ε \), or whether for every \( A ∈ GLn(F2) \) the distance is at least \( ε+ω \). Our main result is a tolerant tester making \( O ( ( m/ω )4 ) \) queries to \( f \), where \( m \) is an upper bound on the spectral norm of \( g \), improving the previous \( O ( ( m/ω )24 ) \) bound of Wimmer and Yoshida. We complement this with a nearly matching lower bound of \( (m2) \) for constant \( ω \) (for example, \( ω=1/4 \)), improving the prior \( ( m) \) lower bound of Grigorescu, Wimmer and Xie. A key technical ingredient on the algorithmic side is a query-efficient local list corrector. For the lower bound, we give a reduction from communication complexity using a novel subclass of Maiorana--McFarland functions from symmetric-key cryptography.

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