Spin-Variable Reduction Method for Handling Linear Equality Constraints in Ising Machines

We propose a spin-variable reduction method for Ising machines to handle linear equality constraints in combinatorial optimization problem. including quantum-annealing can effectively solve problems. They are designed find the lowest-energy solution of quadratic unconstrained binary (QUBO), which is mapped from The proposed reduces number variables formulate QUBO compared conventional penalty method. demonstrate sufficient condition obtain optimum problem and its general applicability. apply it typical problems, such as graph κ-partitioning assignment Experiments using simulated-annealing based that outperforms extends application larger-size problems with constraints.