Faster algorithms for k-Orthogonal Vectors in low dimension

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Main Authors: Dürr, Anita, Kipouridis, Evangelos, Węgrzycki, Karol
Format: Preprint
Published: 2025
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author Dürr, Anita
Kipouridis, Evangelos
Węgrzycki, Karol
author_facet Dürr, Anita
Kipouridis, Evangelos
Węgrzycki, Karol
contents In the Orthogonal Vectors problem (OV), we are given two families $A, B$ of subsets of $\{1,\ldots,d\}$, each of size $n$, and the task is to decide whether there exists a pair $a \in A$ and $b \in B$ such that $a \cap b = \emptyset$. Straightforward algorithms for this problem run in $\mathcal{O}(n^2 \cdot d)$ or $\mathcal{O}(2^d \cdot n)$ time, and assuming SETH, there is no $2^{o(d)}\cdot n^{2-\varepsilon}$ time algorithm that solves this problem for any constant $\varepsilon > 0$. Williams (FOCS 2024) presented a $\tilde{\mathcal{O}}(1.35^d \cdot n)$-time algorithm for the problem, based on the succinct equality-rank decomposition of the disjointness matrix. In this paper, we present a combinatorial algorithm that runs in randomized time $\tilde{\mathcal{O}}(1.25^d n)$. This can be improved to $\mathcal{O}(1.16^d \cdot n)$ using computer-aided evaluations. We generalize our result to the $k$-Orthogonal Vectors problem, where given $k$ families $A_1,\ldots,A_k$ of subsets of $\{1,\ldots,d\}$, each of size $n$, the task is to find elements $a_i \in A_i$ for every $i \in \{1,\ldots,k\}$ such that $a_1 \cap a_2 \cap \ldots \cap a_k = \emptyset$. We show that for every fixed $k \ge 2$, there exists $\varepsilon_k > 0$ such that the $k$-OV problem can be solved in time $\mathcal{O}(2^{(1 - \varepsilon_k)\cdot d}\cdot n)$. We also show that, asymptotically, this is the best we can hope for: for any $\varepsilon > 0$ there exists a $k \ge 2$ such that $2^{(1 - \varepsilon)\cdot d} \cdot n^{\mathcal{O}(1)}$ time algorithm for $k$-Orthogonal Vectors would contradict the Set Cover Conjecture.
format Preprint
id arxiv_https___arxiv_org_abs_2507_11098
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Faster algorithms for k-Orthogonal Vectors in low dimension
Dürr, Anita
Kipouridis, Evangelos
Węgrzycki, Karol
Data Structures and Algorithms
In the Orthogonal Vectors problem (OV), we are given two families $A, B$ of subsets of $\{1,\ldots,d\}$, each of size $n$, and the task is to decide whether there exists a pair $a \in A$ and $b \in B$ such that $a \cap b = \emptyset$. Straightforward algorithms for this problem run in $\mathcal{O}(n^2 \cdot d)$ or $\mathcal{O}(2^d \cdot n)$ time, and assuming SETH, there is no $2^{o(d)}\cdot n^{2-\varepsilon}$ time algorithm that solves this problem for any constant $\varepsilon > 0$. Williams (FOCS 2024) presented a $\tilde{\mathcal{O}}(1.35^d \cdot n)$-time algorithm for the problem, based on the succinct equality-rank decomposition of the disjointness matrix. In this paper, we present a combinatorial algorithm that runs in randomized time $\tilde{\mathcal{O}}(1.25^d n)$. This can be improved to $\mathcal{O}(1.16^d \cdot n)$ using computer-aided evaluations. We generalize our result to the $k$-Orthogonal Vectors problem, where given $k$ families $A_1,\ldots,A_k$ of subsets of $\{1,\ldots,d\}$, each of size $n$, the task is to find elements $a_i \in A_i$ for every $i \in \{1,\ldots,k\}$ such that $a_1 \cap a_2 \cap \ldots \cap a_k = \emptyset$. We show that for every fixed $k \ge 2$, there exists $\varepsilon_k > 0$ such that the $k$-OV problem can be solved in time $\mathcal{O}(2^{(1 - \varepsilon_k)\cdot d}\cdot n)$. We also show that, asymptotically, this is the best we can hope for: for any $\varepsilon > 0$ there exists a $k \ge 2$ such that $2^{(1 - \varepsilon)\cdot d} \cdot n^{\mathcal{O}(1)}$ time algorithm for $k$-Orthogonal Vectors would contradict the Set Cover Conjecture.
title Faster algorithms for k-Orthogonal Vectors in low dimension
topic Data Structures and Algorithms
url https://arxiv.org/abs/2507.11098