Abstract
An optimization method based on energy minimization of the Ising Hamiltonian has been proposed in recent research (S. Utsunomiya et al., Optics Express 19, 2011). Large-scale implementation of such a high-speed optimization method has also been proposed. (T. Inagaki et al., Science, 234, 2016). This paper introduces the quantum neural networks, that can be realized by high-speed devices and applies them to combinatorial ptimization problems. In such schemes using quantum neural networks, an objective function for target optimization problems has to be implemented on mutual connections. In this paper, a mutually connected neural network has been implemented on quantum neural networks to solve combinatorial optimization problems. The simulation results show that quantum neural networks can solve combinatorial optimization problems.
