Identifying quantum phase transitions with minimal prior knowledge by unsupervised learning
In this work, we proposed a novel approach for identifying quantum phase transitions in one-dimensional quantum many-body systems using AutoEncoder (AE), an unsupervised machine learning technique, with minimal prior knowledge. The training of the AEs is done with reduced density matrix (RDM) data o...
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| Format: | Article |
| Language: | English |
| Published: |
SciPost
2025-03-01
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| Series: | SciPost Physics Core |
| Online Access: | https://scipost.org/SciPostPhysCore.8.1.029 |
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