English

Optimality of Frequency Moment Estimation

Data Structures and Algorithms 2025-08-06 v2 Computational Complexity Information Theory math.IT

Abstract

Estimating the second frequency moment of a stream up to (1±ε)(1\pm\varepsilon) multiplicative error requires at most O(logn/ε2)O(\log n / \varepsilon^2) bits of space, due to a seminal result of Alon, Matias, and Szegedy. It is also known that at least Ω(logn+1/ε2)\Omega(\log n + 1/\varepsilon^{2}) space is needed. We prove an optimal lower bound of Ω(log(nε2)/ε2)\Omega\left(\log \left(n \varepsilon^2 \right) / \varepsilon^2\right) for all ε=Ω(1/n)\varepsilon = \Omega(1/\sqrt{n}). Note that when ε>n1/2+c\varepsilon>n^{-1/2 + c}, where c>0c>0, our lower bound matches the classic upper bound of AMS. For smaller values of ε\varepsilon we also introduce a revised algorithm that improves the classic AMS bound and matches our lower bound.

Keywords

Cite

@article{arxiv.2411.02148,
  title  = {Optimality of Frequency Moment Estimation},
  author = {Mark Braverman and Or Zamir},
  journal= {arXiv preprint arXiv:2411.02148},
  year   = {2025}
}

Comments

This version retracts a previously included sketch claiming that the lower bound should extend to non-integral frequency moments F_p for p in (1,2)

R2 v1 2026-06-28T19:47:28.116Z