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Deep Learning of Phase Transitions for Bilinear-Biquadratic Spin-1 Chains from Correlation Aspects
We investigate the role of different correlation functions in reconstructing the phase diagram of the spin-1 bilinear-biquadratic chain, parametrized by the angle $θ$ between the bilinear and biquadratic couplings, using our previously developed label-free machine-learning pipeline \cite{Ming21, Min
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