English

Boolean Functions with Minimal Spectral Sensitivity

Computational Complexity 2025-02-21 v2

Abstract

We show examples of total Boolean functions that depend on nn variables and have spectral sensitivity Θ(logn)\Theta(\sqrt{\log n}), which is asymptotically minimal. Our main new function combines the Hamming code with the Boolean address function and has λ(f)=(1+o(1))log2n\lambda(f) = \sqrt{(1+o(1)) \log_2 n}, which is optimal even up to a constant factor. By combining this function with itself in a specific way, we also obtain a family of functions with s0(f)=(c+o(1))log2n\text{s}_0(f) = (c+o(1)) \log_2 n and s0(f)=(1c+o(1))log2n\text{s}_0(f) = (1-c+o(1)) \log_2 n for any c[0,1]c \in [0,1]. This is an optimal tradeoff for Boolean functions with low sensitivity, as the lower bound on sensitivity by Simon generalizes to s0(f)+s1(f)log2nlog2log2n+2.\text{s}_0(f)+\text{s}_1(f)\geq\log_2 n - \log_2 \log_2 n + 2. As a corollary, this gives a new example of a function with minimal possible sensitivity (up to a constant factor), s(f)=(12+o(1))log2n\text{s}(f) = (\frac{1}{2}+o(1)) \log_2 n.

Keywords

Cite

@article{arxiv.2412.16088,
  title  = {Boolean Functions with Minimal Spectral Sensitivity},
  author = {Krišjānis Prūsis and Jevgēnijs Vihrovs},
  journal= {arXiv preprint arXiv:2412.16088},
  year   = {2025}
}
R2 v1 2026-06-28T20:44:06.995Z