神经网络量子态及其应用  

Neural network quantum states and their applications

作　　者：蒋文杰 邓东灵 JIANG Wen-Jie;DENG Dong-Ling(Institute for Interdisciplinary Information Sciences,Tsinghua University,Beijing 100084,China;Shanghai Qi Zhi Institute,Shanghai 200232,China)

机构地区：[1]清华大学交叉信息研究院,北京100084 [2]上海期智研究院,上海200232

出　　处：《物理》2021年第2期76-83,共8页Physics

摘　　要：神经网络量子态是由人工神经网络所表示的量子态。得益于机器学习,尤其是深度学习近年来取得的突破性进展,神经网络量子态的研究得到了广泛的关注,成为当前的热点前沿方向。文章将介绍不同的神经网络量子态,其物理性质与典型应用场景,最新进展,以及面临的挑战。Neural-network quantum states are states represented by artificial neural networks.Thanks to the dramatic progress achieved recently in the field of machine learning,especially deep learning,the study of neural-network quantum states has attracted tremendous attention across communities,and has become one of the most active directions of research.In this paper,we review different kinds of neural-network quantum states,their physical properties,and typical applications.In addition,we also discuss some most recent advances and future challenges along this direction.

关 键 词：人工神经网络 量子多体问题 量子纠缠 贝尔不等式 

分 类 号：O413[理学—理论物理] TP183[理学—物理]