摘要
相比于经典的隐马尔可夫模型,量子隐马尔可夫模型有着求解速度快和参数数量少的优点而备受关注。但是在从经典到量子的转变过程中,可以发现量子隐马尔可夫过程与量子开放系统有着紧密的联系。不同于前人的研究,该文从开放量子系统出发,研究了量子隐马尔可夫与开放系统所对应的主方程之间的联系,并展示了两个工作:(1)研究了量子开放系统的条件主方程和量子隐马尔可夫模型之间的联系,并以量子输运系统为例,从理论上得到了量子条件主方程和量子隐马尔可夫模型之间的对应关系;(2)提出了一种基于极大似然估计思想的学习算法来解决量子隐马尔可夫模型中的参数求解问题。
Compared with the classical hidden Markov model,the hidden quantum Markov model has the advantages of fast solving speed and fewer parameters,which has attracted much attention.But in the process of transition from classical to quantum,we find that the hidden quantum Markov process is closely related to the quantum open system.Different from previous studies,this article starts from the open quantum system,studies the relationship between the hidden quantum Markov and the main equation corresponding to the open system.On this base,taking the quantum transport system as an example,the relationship between the quantum conditional master equation and the hidden quantum Markov model is theoretically revealed.And then a learning algorithm based on the idea of maximum likelihood estimation is proposed to solve the parameter solving the problem in the hidden quantum Markov model.
作者
李晓瑜
胡勇
卢俊邑
朱钦圣
LI Xiaoyu;HU Yong;LU Junyi;ZHU Qinsheng(School of Information and Software Engineering,University of Electronic Science and Technology of China,Chengdu,610054;School of Physics,University of Electronic Science and Technology of China,Chengdu,610054)
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2021年第5期644-649,共6页
Journal of University of Electronic Science and Technology of China
基金
国家重点研发计划(2018YFA0306703)。
关键词
隐马尔可夫模型
参数求解
量子条件主方程
量子开放系统
hidden Markov model
parameters solve
quantum conditional master equation
quantum open system
