Application of Nonequilibrium Relaxation Scheme to Machine Learning for Detecting a Phase Transition

A great success in detecting the phase transition in a two-dimensional Ising model using a neural network prompts us to apply the idea of nonequilibrium relaxation to the detection. In fact, convolutional neural networks can afford to predict the transition point at an early learning stage. We also mention the limitations of the machine learning approach.