Corpus ID: 237491599

Randomized-gauge test for machine learning of Ising model order parameter

@inproceedings{Morishita2021RandomizedgaugeTF,
  title={Randomized-gauge test for machine learning of Ising model order parameter},
  author={Tomoyuki Morishita and Synge Todo},
  year={2021}
}
Recently, machine learning has been applied successfully for identifying phases and phase transitions of the Ising models. The continuous phase transition is characterized by spontaneous symmetry breaking, which can not be detected in general from a single spin configuration. To investigate if neural networks can extract correlations among spin snapshots, we propose a new test using the random-gauge Ising model. We show that neural networks can extract the order parameter or the energy of the… Expand