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Phys. Rev. B, 2020, Volume 101, 64406, 12 pages (Mi phrb5)  

Revealing quantum chaos with machine learning

Y. A. Kharkovabc, V. E. Sotskova, A. A. Karazeevade, E. O. Kiktenkoafg, A. K. Fedorovad

a Russian Quantum Center, Skolkovo, Moscow 143025, Russia
b School of Physics, University of New South Wales, Sydney 2052, Australia
c Joint Center for Quantum Information and Computer Science, NIST/University of Maryland, College Park, Maryland 20742, USA
d Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region 141700, Russia
e QuTech, Delft Technical University, 2600 GA Delft, Netherlands
f Steklov Mathematical Institute of Russian Academy of Sciences, Moscow 119991, Russia
g NTI Center for Quantum Communications, National University of Science and Technology MISIS, Moscow 119049, Russia

Funding Agency Grant Number
Russian Foundation for Basic Research 18-37-00096
Russian Science Foundation 19-71-10092
The initial stage of the work was supported by RFBR (Grant No. 18-37-00096). The work on the extension of results on the anomaly detection and applications to many-body systems was supported by RSF (No. 19-71-10092).


DOI: https://doi.org/10.1103/PhysRevB.101.064406


Bibliographic databases:

ArXiv: 1902.09216
Received: 23.05.2019
Revised: 02.12.2019
Accepted:10.12.2019
Language:

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