TY - JOUR

T1 - Mapping induced subgraph isomorphism problems to ising models and its evaluations by an ising machine

AU - Yoshimura, Natsuhito

AU - Tawada, Masashi

AU - Tanaka, Shu

AU - Arai, Junya

AU - Yagi, Satoshi

AU - Uchiyama, Hiroyuki

AU - Togawa, Nozomu

N1 - Publisher Copyright:
Copyright © 2021 The Institute of Electronics, Information and Communication Engineers

PY - 2021/4

Y1 - 2021/4

N2 - SUMMARY Ising machines have attracted attention as they are expected to solve combinatorial optimization problems at high speed with Ising models corresponding to those problems. An induced subgraph isomorphism problem is one of the decision problems, which determines whether a specific graph structure is included in a whole graph or not. The problem can be represented by equality constraints in the words of combinatorial optimization problem. By using the penalty functions corresponding to the equality constraints, we can utilize an Ising machine to the induced subgraph isomorphism problem. The induced subgraph isomorphism problem can be seen in many practical problems, for example, finding out a particular malicious circuit in a device or particular network structure of chemical bonds in a compound. However, due to the limitation of the number of spin variables in the current Ising machines, reducing the number of spin variables is a major concern. Here, we propose an efficient Ising model mapping method to solve the induced subgraph isomorphism problem by Ising machines. Our proposed method theoretically solves the induced subgraph isomorphism problem. Furthermore, the number of spin variables in the Ising model generated by our proposed method is theoretically smaller than that of the conventional method. Experimental results demonstrate that our proposed method can successfully solve the induced subgraph isomorphism problem by using the Ising-model based simulated annealing and a real Ising machine.

AB - SUMMARY Ising machines have attracted attention as they are expected to solve combinatorial optimization problems at high speed with Ising models corresponding to those problems. An induced subgraph isomorphism problem is one of the decision problems, which determines whether a specific graph structure is included in a whole graph or not. The problem can be represented by equality constraints in the words of combinatorial optimization problem. By using the penalty functions corresponding to the equality constraints, we can utilize an Ising machine to the induced subgraph isomorphism problem. The induced subgraph isomorphism problem can be seen in many practical problems, for example, finding out a particular malicious circuit in a device or particular network structure of chemical bonds in a compound. However, due to the limitation of the number of spin variables in the current Ising machines, reducing the number of spin variables is a major concern. Here, we propose an efficient Ising model mapping method to solve the induced subgraph isomorphism problem by Ising machines. Our proposed method theoretically solves the induced subgraph isomorphism problem. Furthermore, the number of spin variables in the Ising model generated by our proposed method is theoretically smaller than that of the conventional method. Experimental results demonstrate that our proposed method can successfully solve the induced subgraph isomorphism problem by using the Ising-model based simulated annealing and a real Ising machine.

KW - Annealing machine

KW - Induced subgraph

KW - Ising machines

KW - Ising model

KW - Isomorphism problem

KW - Quadratic unconstraint binary optimization

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UR - http://www.scopus.com/inward/citedby.url?scp=85105115659&partnerID=8YFLogxK

U2 - 10.1587/TRANSINF.2020EDP7026

DO - 10.1587/TRANSINF.2020EDP7026

M3 - Article

AN - SCOPUS:85105115659

SN - 0916-8532

VL - E104.D

SP - 481

EP - 489

JO - IEICE Transactions on Information and Systems

JF - IEICE Transactions on Information and Systems

IS - 4

ER -