English

Tight Cell Probe Bounds for Succinct Boolean Matrix-Vector Multiplication

Data Structures and Algorithms 2017-11-15 v1

Abstract

The conjectured hardness of Boolean matrix-vector multiplication has been used with great success to prove conditional lower bounds for numerous important data structure problems, see Henzinger et al. [STOC'15]. In recent work, Larsen and Williams [SODA'17] attacked the problem from the upper bound side and gave a surprising cell probe data structure (that is, we only charge for memory accesses, while computation is free). Their cell probe data structure answers queries in O~(n7/4)\tilde{O}(n^{7/4}) time and is succinct in the sense that it stores the input matrix in read-only memory, plus an additional O~(n7/4)\tilde{O}(n^{7/4}) bits on the side. In this paper, we essentially settle the cell probe complexity of succinct Boolean matrix-vector multiplication. We present a new cell probe data structure with query time O~(n3/2)\tilde{O}(n^{3/2}) storing just O~(n3/2)\tilde{O}(n^{3/2}) bits on the side. We then complement our data structure with a lower bound showing that any data structure storing rr bits on the side, with n<r<n2n < r < n^2 must have query time tt satisfying tr=Ω~(n3)t r = \tilde{\Omega}(n^3). For rnr \leq n, any data structure must have t=Ω~(n2)t = \tilde{\Omega}(n^2). Since lower bounds in the cell probe model also apply to classic word-RAM data structures, the lower bounds naturally carry over. We also prove similar lower bounds for matrix-vector multiplication over F2\mathbb{F}_2.

Keywords

Cite

@article{arxiv.1711.04467,
  title  = {Tight Cell Probe Bounds for Succinct Boolean Matrix-Vector Multiplication},
  author = {Diptarka Chakraborty and Lior Kamma and Kasper Green Larsen},
  journal= {arXiv preprint arXiv:1711.04467},
  year   = {2017}
}
R2 v1 2026-06-22T22:43:52.135Z