Unsupervised learning of phase transition in quantum spin model
This report investigates the application of unsupervised learning techniques to detect phase transitions in quantum spin systems, focusing on the 2D and 3D Ising models. Using Monte Carlo simulations, we generate spin configurations and apply Principal Component Analysis (PCA), autoencoders, and...
Saved in:
| 主要作者: | |
|---|---|
| 其他作者: | |
| 格式: | Final Year Project |
| 語言: | English |
| 出版: |
Nanyang Technological University
2025
|
| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/184488 |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|