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In the laboratory of the Graduate School of New Frontier Sciences at the University of Tokyo, research is being conducted on theories and applications related to Materials Informatics (MI). In 2020, a black-box optimization method called FMQA, which combines machine learning and quantum annealing, was proposed. FMQA is a method that can be applied not only in the field of materials development that the faculty members are working on but also in a wide range of areas such as substance exploration in chemistry and drug discovery, as well as optimal design in manufacturing (such as wing shapes), attracting significant attention from various fields. We spoke with the members of the laboratory about the story behind the birth of FMQA. *For more detailed information, please refer to the related links. For more details, you can download the PDF or feel free to contact us.*
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