• Aiming at developing practical quantum optimization technology known as quantum annealing, we are working on exploring basic technologies that can overcome the limitations and applications in collaboration with multiple companies. The advantage of the method is that it can be used simply by formulating a cost function that draws the goal to be optimized once, but we are not limited to the original method. We extend it by considering a much easier problem, sequential optimization by learning, black box optimization, etc.. In particular, it is being applied to automated driving, logistics in factories, and evacuation guidance during disasters.

Applications to route search problems such as automatic driving of various vehicles, evacuation route guidance at the time of disaster, process scheduling and a large number of combination problems. We can provide a solution to combinatorial optimization in each industry. (Transportation / distribution, manufacturing, materials, drug discovery, etc.)

• Mathematical physics
• Fundamental theory of physical properties
• Statistical Mechanics
• Quantum Mechanics
• Sparse Modeling
• Machine Learning
• Bayesian Optimization
• Optimization Problem
• Quantum Annealing
• Quantum Computation