English

Counting Short Vector Pairs by Inner Product and Relations to the Permanent

Data Structures and Algorithms 2020-07-29 v1 Computational Complexity Combinatorics

Abstract

Given as input two nn-element sets A,B{0,1}d\mathcal A,\mathcal B\subseteq\{0,1\}^d with d=clogn(logn)2/(loglogn)4d=c\log n\leq(\log n)^2/(\log\log n)^4 and a target t{0,1,,d}t\in \{0,1,\ldots,d\}, we show how to count the number of pairs (x,y)A×B(x,y)\in \mathcal A\times \mathcal B with integer inner product x,y=t\langle x,y \rangle=t deterministically, in n2/2Ω( ⁣lognloglogn/(clog2c))n^2/2^{\Omega\bigl(\!\sqrt{\log n\log \log n/(c\log^2 c)}\bigr)} time. This demonstrates that one can solve this problem in deterministic subquadratic time almost up to log2n\log^2 n dimensions, nearly matching the dimension bound of a subquadratic randomized detection algorithm of Alman and Williams [FOCS 2015]. We also show how to modify their randomized algorithm to count the pairs w.h.p., to obtain a fast randomized algorithm. Our deterministic algorithm builds on a novel technique of reconstructing a function from sum-aggregates by prime residues, which can be seen as an {\em additive} analog of the Chinese Remainder Theorem. As our second contribution, we relate the fine-grained complexity of the task of counting of vector pairs by inner product to the task of computing a zero-one matrix permanent over the integers.

Keywords

Cite

@article{arxiv.2007.14092,
  title  = {Counting Short Vector Pairs by Inner Product and Relations to the Permanent},
  author = {Andreas Björklund and Petteri Kaski},
  journal= {arXiv preprint arXiv:2007.14092},
  year   = {2020}
}