Smallest neural network to learn the Ising criticality.

  title={Smallest neural network to learn the Ising criticality.},
  author={Dongkyu Kim and Dong-Hee Kim},
  journal={Physical review. E},
  volume={98 2-1},
Learning with an artificial neural network encodes the system behavior in a feed-forward function with a number of parameters optimized by data-driven training. An open question is whether one can minimize the network complexity without loss of performance to reveal how and why it works. Here we investigate the learning of the phase transition in the Ising model and find that having two hidden neurons can be enough for an accurate prediction of critical temperature. We show that the networks… 

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