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arXiv:2611.11409 · v1

Linear Set Reconciliation with $O(d)$ Additive Redundancy

首次提交 2026-11-08 22:23
版本更新 2026-11-08 22:23
雷达观测 2026-11-10 12:16
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摘要

In set reconciliation, two parties holding sets A,B⊆[n]A, B \subseteq [n] with ∣A△B∣≤d|A \triangle B| \le d seek to recover their symmetric difference from short F2\mathbb{F}_2-linear sketches, which is equivalent to recovering a dd-sparse vector x=1A△B∈F2nx = \mathbf{1}_{A \triangle B} \in \mathbb{F}_2^n from its syndrome Hx∈F2mHx \in \mathbb{F}_2^m. While the information-theoretic counting bound requires L(n,d):=log⁡∑i=0d(ni)=dlog⁡(n/d)+Θ(d)L(n,d) := \log \sum_{i=0}^d \binom{n}{i} = d\log(n/d) + Θ(d) bits, existing polynomial-time schemes either use at least d⌈log⁡(n+1)⌉d\lceil\log(n+1)\rceil bits (algebraic sketches, leaving an Ω(dlog⁡d)Ω(d\log d)-bit gap) or incur a multiplicative (1+δ)L(n,d)(1+δ)L(n,d) overhead (peeling-based sketches), raising the question of whether L(n,d)+O(d)L(n,d) + O(d) bits is achievable with fast updates and decoding. We construct a public-coin randomized F2\mathbb{F}_2-linear sketch of length L(n,d)+O(d)+λlog⁡O(1)nL(n,d) + O(d) + λ\log^{O(1)} n that recovers each fixed input of weight at most dd with probability at least 1−2−λ1 - 2^{-λ}, with log⁡O(1)n\log^{O(1)} n update time and dexp⁡(O((log⁡log⁡n)2))=dno(1)d\exp(O((\log\log n)^2)) = dn^{o(1)} worst-case decoding time. In particular, for n≤2polylog⁡(d)n \le 2^{\operatorname{polylog}(d)} and λ≤d1−Ω(1)λ\le d^{1-Ω(1)}, this achieves L(n,d)+O(d)L(n,d) + O(d) bits with polylog⁡(d)\operatorname{polylog}(d) update time and d1+o(1)d^{1+o(1)} decoding time. Our construction encodes dd permuted rows via randomly scaled Pinsketch syndromes and sketches the resulting bit array column by column. Decoding columns sequentially from prefix predictions cancels recovered rows and exposes undecided rows as decoder-side hints, reducing each column to a hinted sparse recovery problem that we solve via a recursive sketch, HintSketch.

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v1 · 2026-11-08 22:23 · 最新观测版本

Linear Set Reconciliation with $O(d)$ Additive Redundancy

In set reconciliation, two parties holding sets A,B⊆[n]A, B \subseteq [n] with ∣A△B∣≤d|A \triangle B| \le d seek to recover their symmetric difference from short F2\mathbb{F}_2-linear sketches, which is equivalent to recovering a dd-sparse vector x=1A△B∈F2nx = \mathbf{1}_{A \triangle B} \in \mathbb{F}_2^n from its syndrome Hx∈F2mHx \in \mathbb{F}_2^m. While the information-theoretic counting bound requires L(n,d):=log⁡∑i=0d(ni)=dlog⁡(n/d)+Θ(d)L(n,d) := \log \sum_{i=0}^d \binom{n}{i} = d\log(n/d) + Θ(d) bits, existing polynomial-time schemes either use at least d⌈log⁡(n+1)⌉d\lceil\log(n+1)\rceil bits (algebraic sketches, leaving an Ω(dlog⁡d)Ω(d\log d)-bit gap) or incur a multiplicative (1+δ)L(n,d)(1+δ)L(n,d) overhead (peeling-based sketches), raising the question of whether L(n,d)+O(d)L(n,d) + O(d) bits is achievable with fast updates and decoding. We construct a public-coin randomized F2\mathbb{F}_2-linear sketch of length L(n,d)+O(d)+λlog⁡O(1)nL(n,d) + O(d) + λ\log^{O(1)} n that recovers each fixed input of weight at most dd with probability at least 1−2−λ1 - 2^{-λ}, with log⁡O(1)n\log^{O(1)} n update time and dexp⁡(O((log⁡log⁡n)2))=dno(1)d\exp(O((\log\log n)^2)) = dn^{o(1)} worst-case decoding time. In particular, for n≤2polylog⁡(d)n \le 2^{\operatorname{polylog}(d)} and λ≤d1−Ω(1)λ\le d^{1-Ω(1)}, this achieves L(n,d)+O(d)L(n,d) + O(d) bits with polylog⁡(d)\operatorname{polylog}(d) update time and d1+o(1)d^{1+o(1)} decoding time. Our construction encodes dd permuted rows via randomly scaled Pinsketch syndromes and sketches the resulting bit array column by column. Decoding columns sequentially from prefix predictions cancels recovered rows and exposes undecided rows as decoder-side hints, reducing each column to a hinted sparse recovery problem that we solve via a recursive sketch, HintSketch.

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