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   Hadley Black, Deeparnab Chakrabarty (November 2023, Annual Symposium on Foundations of Computer Science)

   Monotonicity testing of Boolean functions on the hypergrid, $$f:[n]^d \to \{0,1\}$$, is a classic topic in property testing. Determining the non-adaptive complexity of this problem is an important open question. For arbitrary $$n$$, [Black-Chakrabarty-Seshadhri, SODA 2020] describe a tester with query complexity $$\widetilde{O}(\varepsilon^{-4/3}d^{5/6})$$. This complexity is independent of $$n$$, but has a suboptimal dependence on $$d$$. Recently, [Braverman-Khot-Kindler-Minzer, ITCS 2023] and [Black-Chakrabarty-Seshadhri, STOC 2023] describe $$\widetilde{O}(\varepsilon^{-2} n^3\sqrt{d})$$ and $$\widetilde{O}(\varepsilon^{-2} n\sqrt{d})$$-query testers, respectively. These testers have an almost optimal dependence on $$d$$, but a suboptimal polynomial dependence on $$n$$. \smallskip In this paper, we describe a non-adaptive, one-sided monotonicity tester with query complexity $$O(\varepsilon^{-2} d^{1/2 + o(1)})$$, \emph{independent} of $$n$$. Up to the $$d^{o(1)}$$-factors, our result resolves the non-adaptive complexity of monotonicity testing for Boolean functions on hypergrids. The independence of $$n$$ yields a non-adaptive, one-sided $$O(\varepsilon^{-2} d^{1/2 + o(1)})$$-query monotonicity tester for Boolean functions $$f:\mathbb{R}^d \to \{0,1\}$$ associated with an arbitrary product measure. 

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