Autoencoder-based learning of Quantum phase transitions in the two-component Bose-Hubbard model
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866910622900289536 |
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| author | Chowdhury, Iftekher S. Akhouri, Binay Prakash Haque, Shah Howard, Eric |
| author_facet | Chowdhury, Iftekher S. Akhouri, Binay Prakash Haque, Shah Howard, Eric |
| contents | This paper investigates the use of autoencoders and machine learning methods for detecting and analyzing quantum phase transitions in the Two-Component Bose-Hubbard Model. By leveraging deep learning models such as autoencoders, we investigate latent space representations, reconstruction error analysis, and cluster distance calculations to identify phase boundaries and critical points. The study is supplemented by dimensionality reduction techniques such as PCA and t-SNE for latent space visualization. The results demonstrate the potential of autoencoders to describe the dynamics of quantum phase transitions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_18480 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Autoencoder-based learning of Quantum phase transitions in the two-component Bose-Hubbard model Chowdhury, Iftekher S. Akhouri, Binay Prakash Haque, Shah Howard, Eric Quantum Gases High Energy Physics - Lattice Quantum Physics This paper investigates the use of autoencoders and machine learning methods for detecting and analyzing quantum phase transitions in the Two-Component Bose-Hubbard Model. By leveraging deep learning models such as autoencoders, we investigate latent space representations, reconstruction error analysis, and cluster distance calculations to identify phase boundaries and critical points. The study is supplemented by dimensionality reduction techniques such as PCA and t-SNE for latent space visualization. The results demonstrate the potential of autoencoders to describe the dynamics of quantum phase transitions. |
| title | Autoencoder-based learning of Quantum phase transitions in the two-component Bose-Hubbard model |
| topic | Quantum Gases High Energy Physics - Lattice Quantum Physics |
| url | https://arxiv.org/abs/2409.18480 |