基于深度学习的两分量 BEC 中量子相变点的识别.

Recognizing the phase transition of matter is an important problem in physics research. Convolutional neural network algorithm of confusion label scheme is used to identify quantum phase transition point of two- component Bose-Einstein condensates (BEC) in this paper. By calculating the output accuracy of neural net- work, the W-shape performance curve is obtained. The maximum value in the middle of W-shape performance curve corresponds to the critical point of quantum phase transition. The research results show that the critical point obtained by deep learning is consistent with the analytic calculation results. The deep learning method of confusion label scheme can be applied to the phase transition system of existing two phases. [ABSTRACT FROM AUTHOR]