Tight Cell Probe Bounds for Succinct Boolean Matrix-Vector Multiplication

TL;DR

This paper establishes tight bounds for succinct Boolean matrix-vector multiplication in the cell probe model, presenting a new data structure with improved query time and matching lower bounds, advancing understanding of the problem's complexity.

Contribution

It introduces a new cell probe data structure with optimal query time and storage, and proves matching lower bounds, settling the complexity of succinct Boolean matrix-vector multiplication.

Findings

New data structure with $ ilde{O}(n^{3/2})$ query time and storage

Lower bounds showing no significantly faster data structures are possible

Results extend to matrix-vector multiplication over $ extbf{F}_2$

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 $\tilde{O}(n^{7/4})$ time and is succinct in the sense that it stores the input matrix in read-only memory, plus an additional $\tilde{O}(n^{7/4})$ 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 $\tilde{O}(n^{3/2})$ storing just $\tilde{O}(n^{3/2})$ bits on the side. We then complement our data structure with a lower bound showing that any data structure storing $r$ bits on the side, with $n < r < n^2$ must have query time $t$ satisfying $t r = \tilde{\Omega}(n^3)$. For $r \leq n$, any data structure must have $t = \tilde{\Omega}(n^2)$. 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 $\mathbb{F}_2$.