Adaptive Quantum Process Tomography via Linear Regression Estimation

被引：0
|
作者：
Yu, Qi [1 ]
Dong, Daoyi [1 ]
Wang, Yuanlong [1 ,2 ]
Petersen, Ian R. [3 ]
机构：
[1] Univ New South Wales, Sch Engn & Informat Technol, Canberra, ACT, Australia
[2] Griffith Univ, Ctr Quantum Dynam, Brisbane, Qld 4111, Australia
[3] Australian Natl Univ, Res Sch Elect Energy & Mat Engn, Canberra, ACT, Australia
来源：
2020 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS (SMC) | 2020年
关键词：
Adaptive quantum process tomography; quantum cybernetics; linear regression estimation; quantum control; HAMILTONIAN IDENTIFICATION; STATE TOMOGRAPHY; QUBIT SYSTEMS; ALGORITHM;
D O I：
10.1109/smc42975.2020.9283060
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper proposes a recursively adaptive tomography protocol to improve the precision of quantum process estimation for finite dimensional systems. The problem of quantum process tomography is firstly formulated as a parameter estimation problem which can then be solved by the linear regression estimation method. An adaptive algorithm is proposed for the selection of subsequent input states given the previous estimation results. Numerical results show that the proposed adaptive process tomography protocol can achieve an improved level of estimation performance.
引用
收藏
页码：4173 / 4178
页数：6
相关论文
共 50 条
  • [31] (Nearly) Optimal Private Linear Regression via Adaptive Clipping
    Varshney, Prateek
    Thakurta, Abhradeep
    Jain, Prateek
    CONFERENCE ON LEARNING THEORY, VOL 178, 2022, 178
  • [32] PROCESS ESTIMATION - LINEAR ADAPTIVE ALGORITHMS AND NEURAL NETWORKS
    THAM, MT
    MONTAGUE, GA
    MORRIS, AJ
    LECTURE NOTES IN CONTROL AND INFORMATION SCIENCES, 1991, 158 : 171 - 188
  • [33] ADAPTIVE ESTIMATION OF REGRESSION-MODELS VIA MOMENT RESTRICTIONS
    NEWEY, WK
    JOURNAL OF ECONOMETRICS, 1988, 38 (03) : 301 - 339
  • [34] Adaptive estimation in autoregression or β-mixing regression via model selection
    Baraud, Y
    Comte, F
    Viennet, G
    ANNALS OF STATISTICS, 2001, 29 (03): : 839 - 875
  • [35] On adaptive linear regression
    Maity, Arnab
    Sherman, Michael
    JOURNAL OF APPLIED STATISTICS, 2008, 35 (11-12) : 1409 - 1422
  • [36] Multiple Change-Points Estimation in Linear Regression Models via an Adaptive LASSO Expectile Loss Function
    Gabriela Ciuperca
    Nicolas Dulac
    Journal of Statistical Theory and Practice, 2022, 16
  • [37] Multiple Change-Points Estimation in Linear Regression Models via an Adaptive LASSO Expectile Loss Function
    Ciuperca, Gabriela
    Dulac, Nicolas
    JOURNAL OF STATISTICAL THEORY AND PRACTICE, 2022, 16 (03)
  • [38] Heritability estimation for a linear combination of phenotypes via ridge regression
    Li, Xiaoguang
    Feng, Xingdong
    Liu, Xu
    BIOINFORMATICS, 2022, 38 (20) : 4687 - 4696
  • [39] Changepoint Estimation in a Segmented Linear Regression via Empirical Likelihood
    Liu, Zhihua
    Qian, Lianfen
    COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION, 2010, 39 (01) : 85 - 100
  • [40] Quantum process tomography via optimal design of experiments
    Gazit, Yonatan
    Ng, Hui Khoon
    Suzuki, Jun
    PHYSICAL REVIEW A, 2019, 100 (01)
12345