The macroscopic world governed by classical physics, as we perceive it, differs vastly from the microscopic world governed by quantum physics. Despite the great strides that have been made in measurement technology for quantum properties, many phenomena observed in the quantum many-body systems, where multiple degrees of freedom influence each other, cannot be addressed directly with current methods due to the complexity of the signals. This limitation is closely related to the fact that we humans are incapable of conceptually comprehending information that is too complex and multi-dimensional. However, even if we cannot understand it, these data carries information of the quantum systems. Thus, the use of rapidly developing AI will facilitate the deciphering of previously incomprehensible quantum properties, and thereby reduce them to something that can be used by humans.

This research aims to develop AI-physical science for reading and using the complex signals produced by quantum systems. Most classical science and technology deals with macroscopic averaging of fluctuations of signals obtained from quantum systems, rarely leveraging the vast microscopic degrees of freedom. However, the emergence of AI has enabled us to actively utilize some of the unused microscopic degrees of freedom and to transcribe it into information human beings can understand. This in turn has increased the possibility of establishing the next-generation processing utilizing various material properties such as quantum nature and nonlinearity, in other words, developing a completely new type of computing that implements functions such as recording and computing information using microscopic degrees of freedom.

In this research, we first aim to decipher and utilize complex quantum output signals called “quantum fingerprints” and “quantum bits (qubits).” AI scientists and researchers in the field of quantum physical property measurement collaborate and boldly integrate their measurement devices, contributing to applications such as quantum computing technology and quantum physical tags. In other words, it would allow for mapping the real world into a complex quantum world beyond the degrees of freedom that humans can comprehend, which in turn would help expand human perception, thinking, and science and technology itself through quantum AI.

Through our research to date, we have accumulated world-leading academic knowledge and expertise in the fields of quantum properties and quantum science and technology. We will accelerate the further progress of both areas by supplementing the respective strengths of our two research fields: advanced measurement technology in quantum physics experiments and information processing in machine learning. Our existing studies have demonstrated that the complexity of physical phenomena arising from microscopic degrees of freedom can be converted into usable information resources using the deep learning methods. We will further pursue our research to trigger a chain reaction of unconventional challenges and innovations.

Discovering a route between the quantum world and our real world through AI would transform science, allowing for the development of new quantum-based technologies. For example, if we can develop a method to ultimately determine the identity of substance, it could be applied to the real world as a “quantum physics tag” to identify products and many other things. In the future, the combination of quantum physics and AI will be likely to make innovation happen in multiple areas: the exploration of the field of quantum AI, in which the complexity and non-linearity of quantum are actively incorporated into AI; and the development of new quantum computing technology, in which the fluctuations of quantum are controlled to a high degree through the use of AI.