The social implementation of quantum computers is progressing a bit at a time. One issue that often arises in considering real-world examples is the acquisition of data. Companies want to supply data for useful projects, but providing internal data is often a hurdle. To some extent, simulations and runs with dummy or sample data are useful for internal persuasion. At blueqat, we are accelerating the provision of real quantum computers and HPC through the deployment of our own GPU clusters and GPU cloud services. In addition, by using NVIDIA&#39;s cuQuantum, we expect to be able to perform quantum gate calculations at practical sizes ahead of the era of hundreds and thousands of qubits of quantum gates that we are about to enter. Therefore, in order to facilitate data acquisition, we are proceeding to construct a 3D space on a PC where optimization and machine learning trials can be conducted using a digital twin. We can simulate various urban optimization projects such as route optimization, production optimization, and stabilization of renewable energy, while visualizing the results of such simulations. Modeling and rendering are done in our cloud, and the interface can be made into a web app via Unreal Engine or javascript libraries. <img src="https://assets.blueqat.com/public/uploads/us-east-2:4805ff4b-c3cc-4344-b165-86544c34d0bf/2023/01/13/image.png"/>Example: Route optimization demo using a model of Shinjuku In the future, we will continue to build a simulation environment tailored to our clients&#39; needs, and will continue to make efforts to efficiently implement quantum technology in society.

Digital twin development for social implementation of quantum computers has been started.

Yuichiro Minato