Sub-linear Upper Bounds on Fourier dimension of Boolean Functions in terms of Fourier sparsity

Swagato Sanyal

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arXiv · 1407.3500

Sub-linear Upper Bounds on Fourier dimension of Boolean Functions in terms of Fourier sparsity

Swagato Sanyal

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Abstract

We prove that the Fourier dimension of any Boolean function with Fourier sparsity $s$ is at most $O\left(s^{2/3}\right)$. Our proof method yields an improved bound of $\widetilde{O}(\sqrt{s})$ assuming a conjecture of Tsang~\etal~\cite{tsang}, that for every Boolean function of sparsity $s$ there is an affine subspace of $\mathbb{F}_2^n$ of co-dimension $O(\poly\log s)$ restricted to which the function is constant. This conjectured bound is tight upto poly-logarithmic factors as the Fourier dimension and sparsity of the address function are quadratically separated. We obtain these bounds by observing that the Fourier dimension of a Boolean function is equivalent to its non-adaptive parity decision tree complexity, and then bounding the latter.

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Swagato Sanyal. 2014-07-13. Sub-linear Upper Bounds on Fourier dimension of Boolean Functions in terms of Fourier sparsity. https://arxiv.org/abs/1407.3500

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