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arXiv:2611.08574 · v1

Composition Theorem for Randomized Query Complexity

首次提交 2026-11-06 02:37
版本更新 2026-11-06 02:37
雷达观测 2026-11-09 10:16
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摘要

For bounded-error randomized query complexity, we resolve the composition conjecture up to logarithmic factors. The general upper bound R(f∘g)=O ⁣(R(f)R(g)log⁡(R(f)+1))R(f\circ g) = O\!\left(R(f)R(g)\log(R(f)+1)\right) was already known. Although Meiburg recently disproved constant-factor multiplicative composition for total Boolean functions, the conjecture allowing polylogarithmic losses remained open. We settle this question by proving that, for all (possibly partial) Boolean functions ff and gg, R(f∘g)=Ω ⁣(R(f)R(g)log⁡(n+1)), R(f\circ g) = Ω\!\left(\frac{R(f)R(g)}{\log(n+1)}\right), where nn is the input size for ff.

作者备注:21 pages

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v1 · 2026-11-06 02:37 · 最新观测版本

Composition Theorem for Randomized Query Complexity

For bounded-error randomized query complexity, we resolve the composition conjecture up to logarithmic factors. The general upper bound R(f∘g)=O ⁣(R(f)R(g)log⁡(R(f)+1))R(f\circ g) = O\!\left(R(f)R(g)\log(R(f)+1)\right) was already known. Although Meiburg recently disproved constant-factor multiplicative composition for total Boolean functions, the conjecture allowing polylogarithmic losses remained open. We settle this question by proving that, for all (possibly partial) Boolean functions ff and gg, R(f∘g)=Ω ⁣(R(f)R(g)log⁡(n+1)), R(f\circ g) = Ω\!\left(\frac{R(f)R(g)}{\log(n+1)}\right), where nn is the input size for ff.

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