Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Iori Kurata"'
Autor:
So Takamoto, Chikashi Shinagawa, Daisuke Motoki, Kosuke Nakago, Wenwen Li, Iori Kurata, Taku Watanabe, Yoshihiro Yayama, Hiroki Iriguchi, Yusuke Asano, Tasuku Onodera, Takafumi Ishii, Takao Kudo, Hideki Ono, Ryohto Sawada, Ryuichiro Ishitani, Marc Ong, Taiki Yamaguchi, Toshiki Kataoka, Akihide Hayashi, Nontawat Charoenphakdee, Takeshi Ibuka
Publikováno v:
Nature Communications, Vol 13, Iss 1, Pp 1-11 (2022)
Existing neural network potentials are generally designed for narrow target materials. Here the authors develop a neural network potential which is able to handle any combination of 45 elements and show its applicability in multiple domains.
Externí odkaz:
https://doaj.org/article/ccbd9fe386c44d0db429e9944c60406e
Publikováno v:
Physical Review Research, Vol 2, Iss 3, p 033281 (2020)
The Green's function plays a crucial role when studying the nature of quantum many-body systems, especially strongly correlated systems. Although the development of quantum computers in the near future may enable us to compute energy spectra of class
Externí odkaz:
https://doaj.org/article/94e1263a19c54115a613882ed6659f3c
Autor:
So Takamoto, Chikashi Shinagawa, Daisuke Motoki, Kosuke Nakago, Wenwen Li, Iori Kurata, Taku Watanabe, Yoshihiro Yayama, Hiroki Iriguchi, Yusuke Asano, Tasuku Onodera, Takafumi Ishii, Takao Kudo, Hideki Ono, Ryohto Sawada, Ryuichiro Ishitani, Marc Ong, Taiki Yamaguchi, Toshiki Kataoka, Akihide Hayashi, Nontawat Charoenphakdee, Takeshi Ibuka
Publikováno v:
Nature communications. 13(1)
Computational material discovery is under intense study owing to its ability to explore the vast space of chemical systems. Neural network potentials (NNPs) have been shown to be particularly effective in conducting atomistic simulations for such pur
Publikováno v:
Physical Review Research. 2
The Green's function plays a crucial role when studying the nature of quantum many-body systems, especially strongly-correlated systems. Although the development of quantum computers in the near future may enable us to compute energy spectra of class
Autor:
Izumi Masubuchi, Iori Kurata
Publikováno v:
Automatica. 47:1821-1826
Gain-scheduled control via LPV system models enjoys LMI-based synthesis methods and in particular parameter-dependent Lyapunov matrices have been employed to successfully reduce conservatism. Those controllers derived via parameter-dependent Lyapunov
Autor:
Izumi Masubuchi, Iori Kurata
Publikováno v:
Transactions of the Society of Instrument and Control Engineers. 45:469-475
Autor:
Iori Kurata, Izumi Masubuchi
Publikováno v:
CDC
This paper is concerned with design of gain-scheduled (GS) controllers that depend on filtered scheduling parameters. One of the most sophisticated design method, which is based on parameter-dependent Lyapunov matrices, ends up with GS controllers in
Autor:
Iori Kurata, Izumi Masubuchi
Publikováno v:
2009 International Conference on Networking, Sensing and Control.
Gain-scheduling is a practical control method for plants with nonlinearities and/or time-varying dynamics. This paper proposes synthesis of gain-scheduled controllers by using Lyapunov matrix that depends on the filtered scheduling parameter. This av