Sub-linear Upper Bounds on Fourier dimension of Boolean Functions in terms of Fourier sparsity
Abstract: We prove that the Fourier dimension of any Boolean function with Fourier sparsity is at most . Our proof method yields an improved bound of assuming a conjecture of Tsang~\etal~\cite{tsang}, that for every Boolean function of sparsity there is an affine subspace of 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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