Finding Short-Range Parity-Time Phase-Transition Points with a Neural Network  

作　　者：Songju Lei Dong Bai Zhongzhou Ren Mengjiao Lyu 雷松炬;柏栋;任中州;吕梦蛟(School of Physics,Nanjing University,Nanjing 210093,China;School of Physics Science and Engineering,Tongji University,Shanghai 200092,China;Key Laboratory of Advanced Micro-Structure Materials(Ministry of Education),Shanghai 200092,China;College of Science,Nanjing University of Aeronautics and Astronautics(NUAA),Nanjing 210016,China;Key Laboratory of Aerospace Information Materials and Physics(NUAA),MIIT,Nanjing 211106,China)

机构地区：[1]School of Physics,Nanjing University,Nanjing 210093,China [2]School of Physics Science and Engineering,Tongji University,Shanghai 200092,China [3]Key Laboratory of Advanced Micro-Structure Materials(Ministry of Education),Shanghai 200092,China [4]College of Science,Nanjing University of Aeronautics and Astronautics(NUAA),Nanjing 210016,China [5]Key Laboratory of Aerospace Information Materials and Physics(NUAA),MIIT,Nanjing 211106,China

出　　处：《Chinese Physics Letters》2021年第5期7-10,共4页中国物理快报（英文版）

基　　金：Supported by the National Natural Science Foundation of China (Grant Nos.11535004,11975167,11761161001,11375086,11565010,11881240623 and 11961141003);the National Key R&D Program of China (Grant Nos.2018YFA0404403 and 2016YFE0129300);the Science and Technology Development Fund of Macao (Grant No.008/2017/AFJ);the Fundamental Research Funds for the Central Universities (Grant Nos.22120210138 and 22120200101)。

摘　　要：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 Schrodinger 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.

关 键 词：ANN Hamiltonian Finding Short-Range Parity-Time Phase-Transition Points with a Neural Network 

分 类 号：O413[理学—理论物理] TP183[理学—物理]