An $Ω( (\log n / \log \log n)^2 )$ Cell-Probe Lower Bound for Dynamic Boolean Data Structures

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Main Author: Ko, Young Kun
Format: Preprint
Published: 2026
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author Ko, Young Kun
author_facet Ko, Young Kun
contents We resolve the long-standing open problem of Boolean dynamic data structure hardness, proving an unconditional lower bound of $Ω((\log n / \log\log n)^2)$ for the Multiphase Problem of Patrascu [STOC 2010] (instantiated with Inner Product over $\mathbb{F}_2$). This matches the celebrated barrier for weighted problems established by Larsen [STOC 2012] and closes the gap left by the $Ω(\log^{1.5} n)$ Boolean bound of Larsen, Weinstein, and Yu [STOC 2018]. The previous barrier was methodological: all prior works relied on ``one-way'' communication games, where the inability to verify query simulations necessitated complex machinery (such as the Peak-to-Average Lemma) that hit a hard ceiling at $\log^{1.5} n$. Our key contribution is conceptual: We introduce a 2.5-round Multiphase Communication Game that augments the standard one-way model with a verification round, where Bob confirms the consistency of Alice's simulation against the actual memory. This simple, qualitative change allows us to bypass technical barriers and obtain the optimal bound directly. As a consequence, our analysis naturally extends to other hard Boolean functions, offering a general recipe for translating discrepancy lower bounds into $Ω((\log n / \log\log n)^2)$ dynamic Boolean data structure lower bounds. We also argue that this result likely represents the structural ceiling of the Chronogram framework initiated by Fredman and Saks [STOC 1989]: any $ω(\log^2 n)$ lower bound would require either fundamentally new techniques or major circuit complexity breakthroughs.
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id arxiv_https___arxiv_org_abs_2603_25914
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle An $Ω( (\log n / \log \log n)^2 )$ Cell-Probe Lower Bound for Dynamic Boolean Data Structures
Ko, Young Kun
Computational Complexity
Data Structures and Algorithms
Information Theory
We resolve the long-standing open problem of Boolean dynamic data structure hardness, proving an unconditional lower bound of $Ω((\log n / \log\log n)^2)$ for the Multiphase Problem of Patrascu [STOC 2010] (instantiated with Inner Product over $\mathbb{F}_2$). This matches the celebrated barrier for weighted problems established by Larsen [STOC 2012] and closes the gap left by the $Ω(\log^{1.5} n)$ Boolean bound of Larsen, Weinstein, and Yu [STOC 2018]. The previous barrier was methodological: all prior works relied on ``one-way'' communication games, where the inability to verify query simulations necessitated complex machinery (such as the Peak-to-Average Lemma) that hit a hard ceiling at $\log^{1.5} n$. Our key contribution is conceptual: We introduce a 2.5-round Multiphase Communication Game that augments the standard one-way model with a verification round, where Bob confirms the consistency of Alice's simulation against the actual memory. This simple, qualitative change allows us to bypass technical barriers and obtain the optimal bound directly. As a consequence, our analysis naturally extends to other hard Boolean functions, offering a general recipe for translating discrepancy lower bounds into $Ω((\log n / \log\log n)^2)$ dynamic Boolean data structure lower bounds. We also argue that this result likely represents the structural ceiling of the Chronogram framework initiated by Fredman and Saks [STOC 1989]: any $ω(\log^2 n)$ lower bound would require either fundamentally new techniques or major circuit complexity breakthroughs.
title An $Ω( (\log n / \log \log n)^2 )$ Cell-Probe Lower Bound for Dynamic Boolean Data Structures
topic Computational Complexity
Data Structures and Algorithms
Information Theory
url https://arxiv.org/abs/2603.25914