期刊论文

英文

Physical Review E

2470-0045

2022

105

6

064139

10.1103/PhysRevE.105.064139

Fundamental Research Funds for the Central Universities#&#&#CCNU19QN029 National Natural Science Foundation of China#&#&#11505071#&#&#61702207#&#&#61873104 Hungarian Scientific Research Fund#&#&#K123815 Nemzeti Kutatási Fejlesztési és Innovációs Hivatal

本校为第一机构

The latest advances of statistical physics have shown remarkable performance of machine learning in identifying phase transitions. In this paper, we apply domain adversarial neural network (DANN) based on transfer learning to studying nonequilibrium and equilibrium phase transition models, which are percolation model and directed percolation (DP) model, respectively. With the DANN, only a small fraction of input configurations (two-dimensional images) needs to be labeled, which is automatically chosen, to capture the critical point. To learn the DP model, the method is refined by an iterative ...