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Asian Network School and Workshop on Complex Condensed Matter Systems 2023
Hanoi, 6-10 November 2023
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ProgrammeO.2 -- Oral, ANSWCCMS-2023 Date: Friday, 10 November 2023> Time: 09:30 - 10:00> Machine learning wave functions to identify fractal phasesTilen Cadez Center for Theoretical Physics of Complex Systems, Institute for Basic Science, Daejeon, Korea We demonstrate [1] that an image recognition algorithm based on a convolutional neural network (CNN) provides a powerful procedure to differentiate between ergodic, non-ergodic extended (fractal) and localized phases in various systems: single-particle models, including random-matrix and random-graph models, and many-body quantum systems. The network can be successfully trained on a small data set of only 500 wave functions (images) per class for a single model. The trained network can then be used to classify phases in the other models and is thus very efficient. We discuss the strengths and limitations of the approach. [1] T. Cadez, B. Dietz, D. Rosa, A. Andreanov, K. Slevin and T. Ohtsuki, arXiv: 2306.01402 Presenter: Tilen Cadez |
Institute of Physics, VAST
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Center for Theoretical Physics |
Center for Computational Physics
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