A team of researchers including Professor Masahiro TAKADA of the Institute for AI and Beyond, and Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU) of the University of Tokyo, led by Postdoctoral Research Associate Yosuke KOBAYASHI at the University of Arizona combined machine learning technique, a neural network method with numerical simulation data by the supercomputer “ATERUI II” at the National Astronomical Observatory of Japan (NAOJ) to successfully generate theoretical predictions of the power spectrum, and then measure the most fundamental quantities which characterize properties of the universe such as the amount of dark matter.

The emulator developed in this study is expected to be applied to galaxy maps that will be captured by the Prime Focus Spectrograph, under development, led by the Kavli IPMU, to be mounted on NAOJ’s Subaru Telescope, to study dark matter mass and the nature of dark energy, leading to new discoveries beyond the current understanding of the universe.

Details of their study were published in Physical Review D on April 20, 2022

Professor Masahiro TAKADA is the Sub-Leader of the Basic Research Project entitled “New developments in AI through study of evolution of the Milky Way from initial quantum fluctuations to its assembly” at the Institute for AI and Beyond of the University of Tokyo.

Related Links：
・Full press release at Kavli IPMU official website
https://www.ipmu.jp/en/20220721-emulator
・Paper Abstract in Physical Review D
https://journals.aps.org/prd/abstract/10.1103/PhysRevD.105.083517

Professor Tatsuya HARADA of the Research Center for Advanced Science and Technology （RCAST）of the University of Tokyo was awarded the Science and Technology Award in the Science and Technology Promotion Category for the 2022 Commendation for Science and Technology from the Minister of Education, Culture, Sports, Science and Technology (MEXT) jointly with Professor Shinichi SATO of National Institute of Informatics (NII) and his research collaborators on April 20, 2022 for the contributions made by the “Medical Big-Data Cloud Platform and its application to AI automated diagnosis research”.

The "Commendation for Science and Technology from the Minister of Education, Culture, Sports, Science and Technology" is awarded to persons who have made outstanding achievements in research and development, promotion of understanding related to science and technology.

Professor Tatsuya HARADA is the Project Leader of the Basic Research (Advancement of Fundamental AI) project entitled "Automatic Learning of High Accurate Prediction Models from Limited Supervised Data" at the Institute for AI and Beyond of the University of Tokyo.

・MEXT Homepage: Selected the 2022 Commendation for Science and Technology (Awards for Science and Technology in Research Category) by the Minister of Education, Culture, Sports, Science and Technology (only in Japanese).
https://www.mext.go.jp/b_menu/houdou/mext_00989.html
・Research Center for Advanced Science and Technology, The University of Tokyo (only in Japanese):
https://www.rcast.u-tokyo.ac.jp/ja/news/release/20220408.html
・National Institute of Informatics (NII) News Release
https://www.nii.ac.jp/news/release/2022/0408.html

Professor Masashi SUGIYAMA, Sub-Leader of the Basic Research (Advancement of Fundamental AI) entitled "Automatic Learning of High Accurate Prediction Models from Limited Supervised Data" (Project Leader, Professor Tatsuya HARADA), was selected for the 2022 Commendation for Science and Technology (Awards for Science and Technology in Research Category) by the Minister of Education, Culture, Sports, Science and Technology (MEXT).
The Award Ceremony will be held on April 20 at the auditorium of the Ministry.
The "Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology" is awarded to persons who have made outstanding achievements in research and development, promotion of understanding related to science and technology.

Awarded research:
Weakly Supervised Machine Learning for Building Reliable Artificial Intelligence

On 14th March 2022, Professor Eiji Saitoh, the leader of the Basic Research “Analysis of materials’ quantum properties using AI” received the Japan Academy Prize.

Japan Academy Prize
The Japan Academy Prizes is awarded to persons who have achieved notable research landmarks or who have authored particularly outstanding academic papers or books.

About awarded research
Pioneering Research on Physics of Spin Current

Related Links
Japan Academy: Recipients of the Imperial Prize, the Japan Academy Prizes and the Duke of Edinburgh Prize elected
https://www.japan-acad.go.jp/en/news/2022/031401.html

Faculty of Engineering, The University of Tokyo:
【Awards and Commendations】Professor Eiji Saitoh, Department of Applied Physics, received Japan Academy Prize
https://www.t.u-tokyo.ac.jp/foee/topics/setnws_202203161143454127410294.html

Associate Professor Kenji Tanaka's research development of a "Urban Simulator for the next generation utilizing AI digital technology" from the Institute for AI and Beyond's Applied Research (High-cycle Research) has been featured on DG Lab Haus, a media outlet that provides information on cutting-edge technologies. This article features interviews with Associate Professor Tanaka, Mr. Shinichi Matsuda, Senior Director, AI Strategy Office Technology Unit, SoftBank Corp., and Ryo Kunieda, Manager, AI Strategy Office.

Title: "Another Ebina City" in Virtual Space - Institute for AI and Beyond's "Urban Simulator for the next generation utilizing AI digital technology"
Media: DG Lab Haus
Article URL: https://media.dglab.com/2021/06/08-ebina-01/

The University of Tokyo, Softbank Corp., Odakyu Electric Railway Co., Ltd. and GRID Corp. will collaborate on the research development of a "Urban Simulator for the next generation utilizing AI digital technology" implementing Algorithm for People-Flow Naviation that encourages visitors to change their behavior in Ebina Station and area facilities on the Odakyu Line as one of the research themes in the Institute of AI and Beyond.

PDF（Japanese Only）
https://www.u-tokyo.ac.jp/content/400160449.pdf