Butsuri
Online ISSN : 2423-8872
Print ISSN : 0029-0181
ISSN-L : 0029-0181
Volume 74 , Issue 2
Showing 1-20 articles out of 20 articles from the selected issue
Preface
Contents
Artificial Intelligence and Physics
  • Yusuke Nomura, Youhei Yamaji, Masatoshi Imada
    Type: Reviews
    2019 Volume 74 Issue 2 Pages 72-81
    Published: February 05, 2019
    Released: August 01, 2019
    JOURNALS RESTRICTED ACCESS

    Machine learning is used to extract essential pattern from big data. This technique can be used to extract the essential feature of quantum many-body wave function (=a vector with exponentially large dimensions), and to obtain compact representation of many-body states. In this article, we review representations of many-body states using Boltzmann machine, a type of artificial neural network. We introduce an efficient representation using restricted Boltzmann machines (RBM) and also discuss the efforts to improve the RBM wave functions.

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Reviews
  • Hatsumi Mori
    Type: Reviews
    2019 Volume 74 Issue 2 Pages 82-92
    Published: February 05, 2019
    Released: August 01, 2019
    JOURNALS RESTRICTED ACCESS

    The highly “electron-electron” correlated researches have been vigorously developed in π-, d-, and f-electron systems. Moreover, “electron-proton” coupled studies have attracted much attentions in π-electron based organic crystals. In this review, the basic model, room-temperature ferroelectricity, and novel phenomena of conductivities and magnetism by electron-proton coupling in organic crystals were introduced. Especially, the π-electron based quantum spin liquid state coupled with quantum fluctuation of protons in hydrogen bonds and the switching of conductivity and magnetism triggered by the disorder-order transition of deuterium in hydrogen-bonds have been reported as novel proton-electron coupling properties. Moreover, these phenomena with dynamical π-electron-proton coupling can be controlled by external stimuli such as pressure and electric field.

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Researches
Crossroad
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