Unsupervised PCA applied to classical shadow data from random Pauli measurements detects and classifies both symmetry-breaking and topological quantum phase transitions across multiple spin models without Hamiltonian knowledge.
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A Unsupervised Framework for Identifying Diverse Quantum Phase Transitions Using Classical Shadow Tomography
Unsupervised PCA applied to classical shadow data from random Pauli measurements detects and classifies both symmetry-breaking and topological quantum phase transitions across multiple spin models without Hamiltonian knowledge.