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Machine learning discovery of new phases in programmable quantum
  simulator snapshots

Machine learning discovery of new phases in programmable quantum simulator snapshots

20 December 2021
Cole Miles
R. Samajdar
S. Ebadi
Tout T. Wang
H. Pichler
S. Sachdev
M. Lukin
M. Greiner
Kilian Q. Weinberger
Eun-Ah Kim
ArXivPDFHTML

Papers citing "Machine learning discovery of new phases in programmable quantum simulator snapshots"

7 / 7 papers shown
Title
Interpretable Machine Learning in Physics: A Review
Interpretable Machine Learning in Physics: A Review
Sebastian Johann Wetzel
Seungwoong Ha
Raban Iten
Miriam Klopotek
Ziming Liu
AI4CE
80
0
0
30 Mar 2025
Machine learning phase transitions: Connections to the Fisher
  information
Machine learning phase transitions: Connections to the Fisher information
Julian Arnold
Niels Lörch
Flemming Holtorf
Frank Schafer
23
6
0
17 Nov 2023
Machine learning reveals features of spinon Fermi surface
Machine learning reveals features of spinon Fermi surface
Kevin Zhang
Shih-Wen Feng
Y. Lensky
N. Trivedi
Eun-Ah Kim
18
6
0
05 Jun 2023
Fluctuation based interpretable analysis scheme for quantum many-body
  snapshots
Fluctuation based interpretable analysis scheme for quantum many-body snapshots
Henning Schlomer
A. Bohrdt
26
4
0
12 Apr 2023
Investigating Topological Order using Recurrent Neural Networks
Investigating Topological Order using Recurrent Neural Networks
Mohamed Hibat-Allah
R. Melko
Juan Carrasquilla
16
11
0
20 Mar 2023
Predicting Properties of Quantum Systems with Conditional Generative
  Models
Predicting Properties of Quantum Systems with Conditional Generative Models
Haoxiang Wang
Maurice Weber
J. Izaac
Cedric Yen-Yu Lin
AI4CE
36
9
0
30 Nov 2022
Scalable approach to many-body localization via quantum data
Scalable approach to many-body localization via quantum data
Alexander Gresch
Lennart Bittel
M. Kliesch
17
2
0
17 Feb 2022
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