Quantum Query Complexity of Subgraph Isomorphism and Homomorphism
Raghav Kulkarni, Supartha Podder

TL;DR
This paper establishes new lower bounds on the quantum query complexity for detecting subgraphs and homomorphisms in graphs, revealing that quantum algorithms require significantly more queries than previously known, especially for large graphs.
Contribution
It introduces novel quantum query complexity lower bounds for subgraph isomorphism and homomorphism problems, extending results to hypergraphs and improving existing bounds.
Findings
Quantum query complexity of subgraph isomorphism is at least ((\u03b1_H \u00d7 n))
Quantum query complexity for subgraph isomorphism is (n^{3/4}) for any fixed graph H
Extended bounds to 3-uniform hypergraphs, achieving (n^{4/5}) for isomorphism and (n^{3/2}) for homomorphism
Abstract
Let be a fixed graph on vertices. Let iff the input graph on vertices contains as a (not necessarily induced) subgraph. Let denote the cardinality of a maximum independent set of . In this paper we show: \[Q(f_H) = \Omega\left(\sqrt{\alpha_H \cdot n}\right),\] where denotes the quantum query complexity of . As a consequence we obtain a lower bounds for in terms of several other parameters of such as the average degree, minimum vertex cover, chromatic number, and the critical probability. We also use the above bound to show that for any , improving on the previously best known bound of . Until very recently, it was believed that the quantum query complexity is at least square root of the randomized one. Our bound for matches the square…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Computability, Logic, AI Algorithms · Complexity and Algorithms in Graphs
