← 研踪 PaperTrailarXiv:2611.07622 · v1
Approximate Hamming Convolution via Rectangular Matrix Multiplication
首次提交 2026-11-05 16:05
版本更新 2026-11-05 16:05
雷达观测 2026-11-06 11:06
摘要
We study $(1 \pm ε)$-approximate text-to-pattern Hamming distance: given a length-$N$ pattern and a length-$2N$ text, compute the Hamming distance at every alignment to relative error $ε$. For every fixed $a \ge 0$ and $ε= N^{-a}$, we give a randomized algorithm with simultaneous high-probability correctness on a logarithmic-word RAM and expected running time $\widetilde{O}(N^{ω(4a)/2})$, where $\widetilde{O}$ suppresses subpolynomial factors and $ω(k)$ is the exponent for multiplying an $n \times n^k$ matrix by an $n^k \times n$ matrix. With a recent rectangular bound, this improves the published bounds [CGK+20, FKN26] for $1/12 < a < (3 + \sqrt{3})/16$. In particular, the algorithm runs in expected time $\widetilde{O}(N)$ for $0 \le a \le 1/8$, extending the previous near-linear guarantee through $a = 1/12$.
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v1 · 2026-11-05 16:05 · 最新观测版本
Approximate Hamming Convolution via Rectangular Matrix Multiplication
We study $(1 \pm ε)$-approximate text-to-pattern Hamming distance: given a length-$N$ pattern and a length-$2N$ text, compute the Hamming distance at every alignment to relative error $ε$. For every fixed $a \ge 0$ and $ε= N^{-a}$, we give a randomized algorithm with simultaneous high-probability correctness on a logarithmic-word RAM and expected running time $\widetilde{O}(N^{ω(4a)/2})$, where $\widetilde{O}$ suppresses subpolynomial factors and $ω(k)$ is the exponent for multiplying an $n \times n^k$ matrix by an $n^k \times n$ matrix. With a recent rectangular bound, this improves the published bounds [CGK+20, FKN26] for $1/12 < a < (3 + \sqrt{3})/16$. In particular, the algorithm runs in expected time $\widetilde{O}(N)$ for $0 \le a \le 1/8$, extending the previous near-linear guarantee through $a = 1/12$.
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