The non-Hermitian PT-symmetric system can live in either unbroken or broken PT-symmetric phase. The separation point of the unbroken and broken PT-symmetric phases is called the PT-phase-transition point. Conventionally, given an arbitrary non-Hermitian PT-symmetric Hamiltonian, one has to solve the corresponding Schrdinger equation explicitly in order to determine which phase it is actually in. Here, we propose to use artificial neural network (ANN) to determine the PT-phase-transition points for non-Hermitian PT-symmetric systems with short-range potentials. The numerical results given by ANN agree well with the literature, which shows the reliability of our new method.

非厄米PT对称系统可以存在于完整或破碎的PT对称阶段。未断裂和断裂的PT对称相的分离点称为PT相变点。传统上，给定任意非厄米PT对称哈密顿量，必须明确求解相应的薛定谔方程才能确定它实际处于哪个阶段。在这里，我们建议使用人工神经网络 (ANN) 来确定PT -非厄米PT的相变点-具有短程势的对称系统。人工神经网络给出的数值结果与文献非常吻合，这表明了我们新方法的可靠性。