@inproceedings{9cb005b6d78a433fb8b163eac74b08ff,
title = "Quantum state and detector tomography through closed and open quantum systems",
abstract = "The estimation of all the parameters in an un-known quantum state or measurement device, known as quantum state tomography (QST) and quantum detector tomography (QDT), is fundamental to the characterization and control of quantum systems. This paper presents a unified state space framework for QST and QDT based on observable measurement results at different evolution moments, applicable to both closed and Markovian open quantum systems. We derive lower bounds on the number of sampling points required for a unique estimation and analyze the computational complexity and mean squared error (MSE) scaling. As the estimator may yield unphysical results, we introduce new correction techniques to enforce physicality, which may also improve the infidelity scaling. The effectiveness of the proposed methods is validated through numerical simulations.",
author = "Shuixin Xiao and Yuanlong Wang and Petersen, \{Ian R.\} and Daoyi Dong",
note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 64th IEEE Conference on Decision and Control, CDC 2025 ; Conference date: 09-12-2025 Through 12-12-2025",
year = "2026",
month = jan,
day = "12",
doi = "10.1109/CDC57313.2025.11312504",
language = "English",
isbn = "979-8-3315-2628-3",
series = "Proceedings of the IEEE Conference on Decision and Control",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "6691--6696",
booktitle = "2025 IEEE 64th Conference on Decision and Control, CDC 2025",
address = "United States",
}