6 citations · 10 across the 2 of their papers we have counts for
2 papers
cond-mat.stat-mech2023★ 6 cited
Deep Learning of Phase Transitions for Quantum Spin Chains from Correlation Aspects
Ming-Chiang Chung, Guang-Yu Huang, Ian P. McCulloch +1
Using machine learning (ML) to recognize different phases of matter and to infer the entire phase diagram has proven to be an effective tool given a large dataset. In our previous…
cond-mat.supr-con2021★ 4 cited
Deep learning of topological phase transitions from entanglement aspects for two-dimensional chiral p-wave superconductors
Ming-Chiang Chung, Tsung-Pao Cheng, Guang-Yu Huang +1
Applying deep learning to investigate topological phase transitions (TPTs) becomes a useful method due to not only its ability to recognize patterns but also its statistical excell…