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This research establishes the first non-trivial upper bound for the quantum query complexity of Boolean Matrix Product Verification, significantly improving upon previous Grover search limits. By linking this problem to Orthogonal Vectors, the study provides tighter bounds that reveal a polynomial separation between graph radius and diameter decision complexities. These theoretical advances deepen our understanding of fundamental limits in quantum algorithms for matrix operations and data structures.
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Improved Quantum Query Bounds for Boolean Matrix Product Verification

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arXiv:2609.40180v1 Announce Type: new Abstract: We prove the first non-trivial upper bound for the quantum query complexity of Boolean Matrix Product Verification ($\mathsf{BMPV}$), answering a longstanding open question in quantum query complexity. For $n\times n$ matrices, our upper bound is $\widetilde O(n^{17/12})$, improving on the standard $O(n^{3/2})$ bound obtained using Grover search by Buhrman and \v{S}palek (SODA 2006). We complement this result by showing an $\Omega(n^{5/4})$ lower bound, which improves over the previous best known lower bound of $\widetilde\Omega(n^{19/18})$ by Childs, Kimmel, and Kothari (ESA 2012). Our approach centers on a connection with Orthogonal Vectors ($\mathsf{OV}$), which asks whether an indexed list of $n$ Boolean vectors of dimension $n$ contains two vectors with disjoint supports. In particular, we prove equivalences between $\mathsf{OV}$ and $\mathsf{BMPV}$ and establish the above bounds for $\mathsf{OV}$. We also prove a tight $\widetilde \Theta(n^{3/2})$ bound for a variant of $\mathsf{BMPV}$ that asks whether the product contains a given row vector. Together, these results imply a polynomial separation between the quantum query complexities of deciding whether a graph has radius at most two and whether it has diameter at most two.

Abstract:We prove the first non-trivial upper bound for the quantum query complexity of Boolean Matrix Product Verification ($\mathsf{BMPV}$), answering a longstanding open question in quantum query complexity. For $n\times n$ matrices, our upper bound is $\widetilde O(n^{17/12})$, improving on the standard $O(n^{3/2})$ bound obtained using Grover search by Buhrman and Špalek (SODA 2006). We complement this result by showing an $\Omega(n^{5/4})$ lower bound, which improves over the previous best known lower bound of $\widetilde\Omega(n^{19/18})$ by Childs, Kimmel, and Kothari (ESA 2012). Our approach centers on a connection with Orthogonal Vectors ($\mathsf{OV}$), which asks whether an indexed list of $n$ Boolean vectors of dimension $n$ contains two vectors with disjoint supports. In particular, we prove equivalences between $\mathsf{OV}$ and $\mathsf{BMPV}$ and establish the above bounds for $\mathsf{OV}$. We also prove a tight $\widetilde \Theta(n^{3/2})$ bound for a variant of $\mathsf{BMPV}$ that asks whether the product contains a given row vector. Together, these results imply a polynomial separation between the quantum query complexities of deciding whether a graph has radius at most two and whether it has diameter at most two.

Quantum Physics (quant-ph); Data Structures and Algorithms (cs.DS)

arXiv:2609.40180 [quant-ph]

(or arXiv:2609.40180v1 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.2609.40180 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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