三种高效快速的量子态滤波和估计优化算法

doi:10.16451/j.cnki.issn1003-6059.201907005

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Abstract

The quantum state estimation and filtering problems under different interference and noise conditions are studied, and the corresponding efficient convex algorithms for quantum state density matrix reconstruction are proposed. A quantum state filtering algorithm is proposed for the simultaneous existence of sparse state interference and measurement noise. Two different quantum state estimation algorithms for the existence of sparse state interference and measurement noise are proposed, respectively. In the simulation experiments of the 5-qubit density matrix estimation, the performances of the three proposed algorithms are compared, and the performances of the three algorithms with different measurement rates are analyzed. Experimental results show that the three algorithms have high convergent speeds and low computational complexity, low estimation errors and measurement rates.

Key words： Quantum State Estimation Alternating Direction Multiplier Method Convex Optimization Sparse State Interference Measurement Noise

Received: 14 January 2019

ZTFLH:

TP 301.6

Fund:

Supported by National Natural Science Foundation of China (No.61573330)

About author:: CONG Shuang(Corresponding author), Ph.D., professor. Her research interests include manipulation and realization of quantum system states.DING Jiao, master student. Her research interests include estim.ZHANG Kun, master student. His research interests include estimation of quantum states.ZHANG Jiaojiao, Ph.D. candidate. Her research interests include estimation of quantum states.

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Cite this article:

CONG Shuang,DING Jiao,ZHANG Kun等. Three Types of Efficient and Fast Optimization Algorithms for Quantum State Filtering and Estimation[J]. , 2019, 32(7): 615-623.

URL:

http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201907005 OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2019/V32/I7/615