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Paper:

TR26-086 | 19th May 2026 09:14

A Note on Second-Order Expected Maximum-Load Bounds for Binary Linear Hashing

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TR26-086
Authors: Nader Bshouty
Publication: 24th May 2026 06:42
Downloads: 16
Keywords: 


Abstract:

Let $S\subseteq {\mathbb F}_2^u$ have size $n=2^\ell$, and let $h:{\mathbb F}_2^u\to {\mathbb F}_2^\ell$ be a uniformly random linear map. For
$y\in{\mathbb F}_2^\ell$, write ${load}_h(y):=|h^{-1}(y)\cap S|$, and let
$M(S,h):=\max_{y\in{\mathbb F}_2^\ell}\{load}_h(y)$ be the maximum load. Jaber, Kumar and Zuckerman (STOC 2025) proved that the expected maximum load of $h$ on $S$ is at most $16\log n/\log\log n$, matching the fully independent keys-into-bins scale up to constants. Their proof also gives the tail estimate
\[
\Pr\left[
M(S,h)\ge R\frac{\log n}{\log\log n}
\right]
\le O\left(\frac{1}{R^{2}}\right).
\]
We record a base optimization in their exponential-potential method showing that binary linear hashing nearly matches fully independent hashing also at the
level of the second-order maximum-load scale. For every $R>1$ satisfying $R\ell^{1-1/R}\ge D\ln\ell$, where $D$ is an absolute constant, we prove
\[
\Pr\left[
M(S,h)\ge R\frac{\log n}{\log\log n}
\right]
\le
O\left(
\frac{(\log\log n)^2}{R^2(\log n)^{2-2/R}}
\right).
\]
Integrating this tail yields
\[
{\mathbb E}[M(S,h)]
\le
\left(
1+
(1+o(1))
\frac{\log\log\log n}{\log\log n}
\right)
\frac{\log n}{\log\log n}.
\]
Thus binary linear hashing matches fully independent hashing in the leading term and matches the dominant second-order correction up to a $1+o(1)$ factor.

We also prove, by an independent self-contained argument, a sharp tail bound for one prescribed bucket: for fixed $y\in{\mathbb F}_2^\ell$,
\[
\Pr[{load}_h(y)>2^a-2]\le \gamma^{-1}2^{-a^2},
\]
where $\gamma=\prod_{j\ge1}(1-2^{-j})$. A subspace construction shows that this is asymptotically tight even in the leading constant as $a\to\infty$. However, this controls only a fixed bucket; a direct union bound over all buckets loses a factor $2^\ell$.



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