Correlation Testing for Affine Invariant Properties on $\mathbb{F}_p^n$ in the High Error Regime
Hamed Hatami, Shachar Lovett

TL;DR
This paper characterizes affine invariant properties on finite fields that can be tested via correlation, showing they are essentially equivalent to correlation with low-degree polynomials, using higher-order Fourier analysis.
Contribution
It provides a complete classification of correlation testable affine invariant properties over finite fields, extending previous results to non-linear properties.
Findings
Any affine invariant, correlation testable property can be tested by Gowers uniformity norms.
Correlation with the property is equivalent to correlation with degree d polynomials.
The classification applies to both linear and non-linear affine invariant properties.
Abstract
Recently there has been much interest in Gowers uniformity norms from the perspective of theoretical computer science. This is mainly due to the fact that these norms provide a method for testing whether the maximum correlation of a function with polynomials of degree at most is non-negligible, while making only a constant number of queries to the function. This is an instance of {\em correlation testing}. In this framework, a fixed test is applied to a function, and the acceptance probability of the test is dependent on the correlation of the function from the property. This is an analog of {\em proximity oblivious testing}, a notion coined by Goldreich and Ron, in the high error regime. In this work, we study general properties which are affine invariant and which are correlation testable using a constant number of queries. We show…
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Taxonomy
TopicsLimits and Structures in Graph Theory · Analytic Number Theory Research · Complexity and Algorithms in Graphs
