Two-stage solution of quantum process tomography in the natural basis

被引：2

作者：

Xiao, Shuixin ^{[1
,2
]}

Wang, Yuanlong ^{[3
,4
]}

Dong, Daoyi ^{[1
]}

Zhang, Jun ^{[2
]}

机构：

[1] Univ New South Wales, Sch Engn & Informat Technol, Canberra, ACT 2600, Australia

[2] Shanghai Jiao Tong Univ, UMich SJTU Joint Inst, Shanghai 200240, Peoples R China

[3] Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst & Control, Beijing 100190, Peoples R China

[4] Griffith Univ, Ctr Quantum Dynam, Ctr Quantum Computat & Commun Technol, Australian Res Council, Brisbane, Qld 4111, Australia

来源：

2022 IEEE 61ST CONFERENCE ON DECISION AND CONTROL (CDC) | 2022年

基金：

澳大利亚研究理事会; 中国国家自然科学基金;

关键词：

ERROR ANALYSIS;

D O I：

10.1109/CDC51059.2022.9992920

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Quantum process tomography (QPT) is a critical task for characterizing the dynamics of quantum systems and achieving precise quantum control. In this paper, we propose an effective two-stage solution (TSS) for QPT in the natural basis. Our algorithm has O(d(6)) computational complexity where d is the dimension of the quantum system. We establish an error bound O(d(5/)root N) where N is the copy number for each output state. The numerical examples compared with a convex optimization algorithm demonstrate the effectiveness of our algorithm.

引用

页码：5807 / 5812

页数：6

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