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...

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Bibliographic Details
Main Author: Shin, Juyoung
Other Authors: Chang Guoqing
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2025
Subjects:
Online Access:https://hdl.handle.net/10356/184488
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Institution: Nanyang Technological University
Language: English