2022/09/09
Kyoto University
Waseda University
Keio University
A joint research group, including Professor Susumu Noda and Assistant Professor Takuya Inoue of the Graduate School of Engineering, Kyoto University; Associate Professor Muneki Tanaka of the Faculty of Science and Technology, Keio University; Project Senior Assistant Professor／Project Assistant Professor／Project Lecturer Yuya Seki of the Graduate School of Science and Technology, Keio University; and Professor Nozomu Togawa of the Faculty of Science and Engineering, Waseda University, has successfully discovered a new design that can dramatically improve laser performance compared to conventional designs. This was achieved by applying a combinatorial optimization method using quantum annealing to the design of "photonic-crystal lasers," a next-generation semiconductor laser characterized by its ability to operate with high power and high beam quality. This achievement suggests that quantum computing technology, which has so far been mainly applied to a limited range of problems, can be widely applied to optimization problems in product design and production processes in the manufacturing field. This is an important step toward the development of the smart manufacturing field.
In the field of manufacturing, efforts are currently underway to realize "smart manufacturing," which automates and optimizes all processes from product design to manufacturing processes by utilizing AI and robots, with the aim of improving productivity and significantly reducing costs. However, in optimization problems in the manufacturing field, it is generally difficult to optimize all parameters within a realistic timeframe due to the extremely large number of physical design variables that must be considered. Quantum annealing has recently attracted attention as a method suitable for solving such optimization problems with many design variables, and its usefulness is already being demonstrated for some problems, such as optimizing delivery routes and personnel shifts. However, there have been few examples of applying quantum annealing to problems involving complex physical phenomena, such as the optimization of product design and manufacturing processes, and its applicability to the smart manufacturing field has not been clear.
In this study, the research group applied a structural optimization method using quantum annealing to the design problem of "photonic-crystal lasers," which are expected to become widespread as a laser light source for smart processing in the future, as a case study to verify the applicability of quantum computing to the manufacturing field. As a result, by leveraging the diverse design flexibility of photonic-crystal lasers, they succeeded in finding a new design that can improve all three important indicators of laser performance: "optical output," "beam divergence angle," and "polarization ratio." This achievement is an important step that suggests the applicability of quantum computing technology to the manufacturing field.
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