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This paper proposes a quantum algorithm to solve the graph isomorphism problem by analyzing permutations of eigenvectors derived from adjacency matrices, aiming for polynomial time complexity. The work represents a theoretical advancement in quantum algorithms for specific computational problems within the broader context of quantum computing research.
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The quantum algorithm for graph isomorphism problem

arXiv2 min read

arXiv:1901.06530v2 Announce Type: replace Abstract: The graph isomorphism (GI) problem is the computational problem of finding a permutation of vertices of a given graph $G_1$ that transforms $G_1$ to another given graph $G_2$ and preserves the adjacency. In this work, we propose a quantum algorithm to determine whether there exists such a permutation. To find such a permutation, we introduce isomorphic equivalent graphs of the given graphs to be tested. We proof that the GI problem of the equivalent graphs is equivalent to the GI problem of the given graphs. The idea of the algorithm is to determine whether there exists a permutation can transform the eigenvectors of the adjacency matrix of the equivalent graphs each other. The cost time of the algorithm is polynomial.

Abstract:The graph isomorphism (GI) problem is the computational problem of finding a permutation of vertices of a given graph $G_1$ that transforms $G_1$ to another given graph $G_2$ and preserves the adjacency. In this work, we propose a quantum algorithm to determine whether there exists such a permutation. To find such a permutation, we introduce isomorphic equivalent graphs of the given graphs to be tested. We proof that the GI problem of the equivalent graphs is equivalent to the GI problem of the given graphs. The idea of the algorithm is to determine whether there exists a permutation can transform the eigenvectors of the adjacency matrix of the equivalent graphs each other. The cost time of the algorithm is polynomial.

arXiv:1901.06530 [quant-ph]

(or arXiv:1901.06530v2 [quant-ph] for this version)

https://doi.org/10.48550/arXiv.1901.06530 Focus to learn more arXiv-issued DOI via DataCite

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