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Press Releases

DATE2021.05.24 #Press Releases

Establishment of "Quantum Software" Corporate Sponsored Research Program at The University of Tokyo

Disclaimer: machine translated by DeepL which may contain errors.

The University of Tokyo

SCSK Corporation

NTT DATA Corporation

Dentsu International Information Services Inc.

NITTETSU SOLUTIONS Co.

Sumitomo Mitsui Financial Group, Inc. and The Japan Research Institute, Limited

NEC Corporation

Nihon Unisys, Ltd.

Fujitsu Limited

blueqat Corporation

Outline of Corporate Sponsored Research Program

The University of Tokyo National University Corporation (President: Teruo Fujii, hereinafter referred to as "The University of Tokyo"), SCSK Corporation (President and Chief Executive Officer: Toru Tanihara), NTT DATA Corporation (President: Hiroshi Homma), Dentsu International Information Services Inc. (President and CEO: Hiroyuki Morita), Sumitomo Mitsui Financial Group (President and Group CEO: Jun Ota), The Japan Research Institute, Limited (President: Katsunori Tanizaki), NEC Corporation (President and CEO: Takayuki Morita), Nihon Unisys, Ltd. (President and CEO: Takayoshi Morita), Fujitsu Limited (President and CEO: Takahito Tokita), and blueqat Limited (President: Yuichiro Minato) (hereafter, the nine companies excluding the University of Tokyo are referred to as "Sponsors") , for the purpose of researching a new quantum machine learning method using quantum computers (Note 1) and developing quantum applications. The University of Tokyo will establish the "Quantum Software" Corporate Sponsored Research Program from June1, 2021 to May31, 2024 ( three years). The Corporate Sponsored Research Program will be established at the Graduate School of Science, The University of Tokyo, in cooperation with the Institute for Physics of Intelligence, which is affiliated with the Graduate School.

Purpose of the Corporate Sponsored Research Program

The Corporate Sponsored Research Program aims to develop new quantum machine learning methods and quantum applications by combining quantum computers, tensor networks useful for information compression (Note 2), and sampling methods for information extraction, to understand the physics behind quantum computers through large-scale simulations, and to develop cutting-edge The objective of this project is to solve problems in social implementation through the acquisition of knowledge, and to develop quantum-native professionals.

Human Resource Development

In FY2021, the program will be positioned as a trial, with lectures in the form of seminars for students, courses for working people, symposiums and other events scheduled to be held, with full-scale courses scheduled to begin in FY2022. The sponsors will use the program as a venue for human resource development for their employees by providing information on practical matters, and will also support the development of quantum native human resources based on the needs of the industry.

Supporting companies (in alphabetical order)
SCSK Corporation / NTT DATA Corporation / Dentsu International Information Services Inc. / NITTETSU SOLUTIONS Corporation / Sumitomo Mitsui Financial Group, Inc. and The Japan Research Institute, Limited / NEC Corporation / NUNISYS Corporation / Fujitsu Limited / blueqat, Inc.

For inquiries, please contact
(regarding Corporate Sponsored Research Program)
Professor Shinji TODO, Graduate School of Science, The University of Tokyo
TEL: 03-5841-4196 E-mail: wistaria@phys.s.u-tokyo.ac.jp

(For press inquiries)
Graduate School of Science, The University of Tokyo
TEL: 03-5841-0654 E-mail: kouhou.s@gs.mail.u-tokyo.ac.jp

Explanation of Terms

1 Quantum machine learning

A combined field of conventional machine learning and quantum computation. Generally, it aims to improve model accuracy and learning speed by replacing some or all of the conventional machine learning models with quantum computation. ↑up

Note 2 Tensor network

A calculation method used mainly in the field of condensed matter physics. By expressing the object to be calculated as a combination of many tensors, it is possible to compress information and improve calculation efficiency. In recent years, it has attracted attention for its application to quantum computation and machine learning. ↑up