Various QUBO Formulations of the Graph Isomorphism Problem and Related Problems

Daisuke Takafuji, Koji Nakano, Yasuaki Ito, Takashi Yazane, Junko Yano, Takumi Kato, Shiro Ozaki, Rie Mori, Ryota Katsuki


Quadratic Unconstrained Binary Optimization (QUBO) is a combinatorial optimization to find an optimal binary solution vector that minimizes the energy value defined by a quadratic formula of binary variables in the vector. The graph isomorphism problem is one of the applications of combinatorial optimization, and is not known to be solvable in polynomial time. The problem is also not known to be NP-complete. We propose four QUBO formulations for graph isomorphism problem instances. We also propose four QUBO formulations for induced subgraph isomorphism problem instances and two QUBO formulations for subgraph isomorphism problem instances, which are NP-complete problems. We solve QUBO instances defined by our QUBO formulations, using known QUBO solvers: Gurobi optimizer, Fixstars Amplify AE and OpenJij with SA.


Quantum computing; combinatorial optimization; graph isomorphism; QUBO solvers

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