# Mapping distinct phase transitions to a neural network.

@article{Bachtis2020MappingDP, title={Mapping distinct phase transitions to a neural network.}, author={Dimitrios Bachtis and Gert Aarts and Biagio Lucini}, journal={Physical review. E}, year={2020}, volume={102 5-1}, pages={ 053306 } }

We demonstrate, by means of a convolutional neural network, that the features learned in the two-dimensional Ising model are sufficiently universal to predict the structure of symmetry-breaking phase transitions in considered systems irrespective of the universality class, order, and the presence of discrete or continuous degrees of freedom. No prior knowledge about the existence of a phase transition is required in the target system and its entire parameter space can be scanned with multiple…

## 21 Citations

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