Boolean Matrix Multiplication (Matrix Product)
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Description
Matrix multiplication of two boolean matrices (i.e. where all entries are in $F_2$ and addition is mod 2)
Related Problems
Generalizations: Matrix Multiplication
Subproblem: Boolean Matrix Multiplication (Combinatorial)
Related: Matrix Product Verification, Distance Product, $(\min, \leq)$ Product
Parameters
n: dimension of square matrix
Table of Algorithms
Name | Year | Time | Space | Approximation Factor | Model | Reference |
---|---|---|---|---|---|---|
Output-Sensitive Quantum BMM | 2018 | O*( \min \{n^{1/3} L^{17/{3}0}, n^{1.5} L^{1/4}\}) | Exact | Quantum | Time | |
O'Neil | 1973 | $O(n^{3})$ | Exact | Deterministic | Time |
Reductions TO Problem
Problem | Implication | Year | Citation | Reduction |
---|---|---|---|---|
CFG Parsing | if: to-time: $O(gn^{3-\epsilon})$ for some $\epsilon > {0}$ where $g$ is the size of the CFG and $n$ is the size of the string then: from-time: $O(n^{3-\epsilon/3})$ where $n \times n$ matrix |
2002 | https://arxiv.org/abs/cs/0112018 | link |
Independent Set Queries | if: to-time: $O(n^{2} / \log^c n)$ to answer all subsequent batches of $\log n$ independent set queries from a graph that takes $O(n^k)$ time to preprocess for some $c,k > {0}$ then: from-time: $O(n^{3} / \log^{c+1} n)$ |
2018 | https://dl-acm-org.ezproxy.canberra.edu.au/doi/pdf/10.1145/3186893, Theorem 6.5 | link |
2-sensitive incremental st-reach | assume: BMM then: combinatorial algorithms cannot solve target with preprocessing time $O(n^{3-\epsilon})$, and update and query times $O(n^{2-\epsilon})$ for any $\epsilon > {0}$ |
2017 | https://arxiv.org/pdf/1703.01638.pdf | link |
1-sensitive incremental ss-reach | assume: BMM then: combinatorial algorithms cannot solve target with preprocessing time $O(n^{3-\epsilon})$, and update and query times $O(n^{2-\epsilon})$ for any $\epsilon > {0}$ |
2017 | https://arxiv.org/pdf/1703.01638.pdf | link |
ap-reach | assume: BMM then: combinatorial algorithms cannot solve target with preprocessing time $O(n^{3-\epsilon})$, and update and query times $O(n^{2-\epsilon})$ for any $\epsilon > {0}$ |
2017 | https://arxiv.org/pdf/1703.01638.pdf | link |
2-sensitive (7/5)-approximate st-shortest paths | assume: BMM then: combinatorial algorithms cannot solve target with preprocessing time $O(n^{3-\epsilon})$, and update and query times $O(n^{2-\epsilon})$ for any $\epsilon > {0}$ in undirected unweighted graphs |
2017 | https://arxiv.org/pdf/1703.01638.pdf | link |
1-sensitive (3/2)-approximate ss-shortest paths | assume: BMM then: combinatorial algorithms cannot solve target with preprocessing time $O(n^{3-\epsilon})$, and update and query times $O(n^{2-\epsilon})$ for any $\epsilon > {0}$ in undirected unweighted graphs |
2017 | https://arxiv.org/pdf/1703.01638.pdf | link |
(5/3)-approximate ap-shortest paths | assume: BMM then: combinatorial algorithms cannot solve target with preprocessing time $O(n^{3-\epsilon})$, and update and query times $O(n^{2-\epsilon})$ for any $\epsilon > {0}$ |
2017 | https://arxiv.org/pdf/1703.01638.pdf | link |
1-sensitive (4/3)-approximate decremental diameter | assume: BMM then: combinatorial algorithms cannot solve target with preprocessing time $O(n^{3-\epsilon})$, and update and query times $O(n^{2-\epsilon})$ for any $\epsilon > {0}$ in undirected unweighted graphs |
2017 | https://arxiv.org/pdf/1703.01638.pdf | link |
1-sensitive (4/3)-approximate decremental eccentricity | assume: BMM then: combinatorial algorithms cannot solve target with preprocessing time $O(n^{3-\epsilon})$, and update and query times $O(n^{2-\epsilon})$ for any $\epsilon > {0}$ |
2017 | https://arxiv.org/pdf/1703.01638.pdf | link |
1-sensitive decremental st-shortest paths | assume: BMM then: for directed unweighted graphs with $n$ vertices and $m \geq n$ edges require either $m^{1-o({1})}\sqrt{n}$ preprocessing time or $m^{1-o({1})}/\sqrt{n}$ query time for every function $m$ of $n$ |
2017 | https://arxiv.org/pdf/1703.01638.pdf | link |
Reductions FROM Problem
Problem | Implication | Year | Citation | Reduction |
---|---|---|---|---|
CFG Parsing | if: to-time: $O(n^{3-\epsilon})$ for some $\epsilon > {0}$ where $n \times n$ matrix then: from-time: $O(gn^{3-\epsilon})$ where $g$ is the size of the CFG |
1975 | https://www-sciencedirect-com.ezproxy.canberra.edu.au/science/article/pii/S0022000075800468 | link |