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Titel:

Machine learning of quantum phase transitions

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Dong, Xiao-Yu; Pollmann, Frank; Zhang, Xue-Feng
Abstract:
Machine learning algorithms provide a new perspective on the study of physical phenomena. In this Rapid Communication, we explore the nature of quantum phase transitions using a multicolor convolutional neural network (CNN) in combination with quantum Monte Carlo simulations. We propose a method that compresses (d+1)-dimensional space-time configurations to a manageable size and then use them as the input for a CNN. We benchmark our approach on two models and show that both continuous and discon...     »
Zeitschriftentitel:
Physical Review B 2019-03
Jahr:
2019
Band / Volume:
99
Heft / Issue:
12
Volltext / DOI:
doi:10.1103/physrevb.99.121104
Verlag / Institution:
American Physical Society (APS)
E-ISSN:
2469-99502469-9969
Publikationsdatum:
07.03.2019
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