Machine Learning Many-Body Localization: Search for the Elusive Nonergodic Metal-Reference-Cited by-同舟云学术

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Machine Learning Many-Body Localization: Search for the Elusive Nonergodic Metal

Published:2018-12-10 Issue:24 Volume:121 Page:
ISSN:0031-9007
Container-title:Physical Review Letters
language:en
Short-container-title:Phys. Rev. Lett.

Author:

Hsu Yi-Ting,Li Xiao,Deng Dong-Ling,Das Sarma S.

Funder

Microsoft

University of Maryland

Laboratory for Physical Sciences

Publisher

American Physical Society (APS)

Subject

General Physics and Astronomy

Link

http://harvest.aps.org/v2/journals/articles/10.1103/PhysRevLett.121.245701/fulltext

Reference69 articles.

1. Absence of Diffusion in Certain Random Lattices

2. Metal-Insulator Transitions

3. Localization in One-Dimensional Lattices in the Presence of Incommensurate Potentials

4. Disordered electronic systems

5. Proposed Experimental Realization of Anderson Localization in Random and Incommensurate Artificially Layered Systems

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