Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

Experimental methods in the physical sciences

Quantum Detector Tomography

Lijian Zhang, Hendrik B. Coldenstrodt-Ronge, Animesh Datta, Ian A. Walmsley

Published Jan 1, 2013• 2 citations
Publisher
DOI
10.1016/b978-0-12-387695-9.00009-3

Related papers

Experimental quantum detector tomography

Coldenstrodt-Ronge, Jeff S. Lundeen, Pregnell +6 more

Conference on Lasers and Electro-Optics•Jan 1, 2008•0 citations

Optimal and two-step adaptive quantum detector tomography

Shuixin Xiao, Yuanlong Wang, Daoyi Dong +1 more

arXiv:2106.09255•Automatica•Apr 20, 2022•15 citations

Tomography of quantum detectors

Jeff S. Lundeen, Alejandro Feito, Hendrik B. Coldenstrodt-Ronge +6 more

arXiv:0807.2444•Nature Physics•Nov 16, 2008•364 citations

On the regularization and optimization in quantum detector tomography

Shuixin Xiao, Yuanlong Wang, Jun Zhang +4 more

arXiv:2207.10327•Automatica•Jun 17, 2023•6 citations

Quantum state and detector tomography with known rank

Shuixin Xiao, Yuanlong Wang, Jun Zhang +2 more

Quantum state tomography and quantum detector tomography are two main problems in quantum system identification. In this paper, we study state tomography and detector tomography with prior knowledge about the true rank of the unknown state/detector. In this case, we propose a sufficient condition for static (non-adaptive) tomography algorithms to achieve the optimal infidelity scaling O(1/N) on the number of state copies N. Then we present two examples of such static quantum state tomography and quantum detector tomography algorithms. Numerical examples demonstrate the effectiveness of our algorithms.

IFAC-PapersOnLine•Jan 1, 2023•4 citations

Optimal and adaptive quantum detector tomography

Shuixin Xiao, Yuanlong Wang, Daoyi Dong +1 more

Quantum detector tomography is a fundamental technique for calibrating quantum devices and performing quantum engineering tasks. In this paper, we design optimal probe states for detector estimation based on the minimum upper bound of the mean squared error (UMSE) and the maximum robustness. We establish the minimum UMSE and the minimum condition number for quantum detectors and provide concrete examples that can achieve optimal detector tomography. In order to enhance estimation precision, we also propose a two-step adaptive detector tomography algorithm and investigate how this adaptive strategy can be used to achieve efficient estimation of quantum detectors. Moreover, the superposition of coherent states are used as probe states for quantum detector tomography and the estimation error is analyzed. Numerical results demonstrate the effectiveness of both the proposed optimal and adaptive quantum detector tomography methods.

•Jun 17, 2021•0 citations
Quantum state tomography and quantum detector tomography are two main problems in quantum system identification. In this paper, we study state tomography and detector tomography with prior knowledge about the true rank of the unknown state/detector. In this case, we propose a sufficient condition for static (non-adaptive) tomography algorithms to achieve the optimal infidelity scaling O(1/N) on the number of state copies N. Then we present two examples of such static quantum state tomography and quantum detector tomography algorithms. Numerical examples demonstrate the effectiveness of our algorithms.
Quantum detector tomography is a fundamental technique for calibrating quantum devices and performing quantum engineering tasks. In this paper, we design optimal probe states for detector estimation based on the minimum upper bound of the mean squared error (UMSE) and the maximum robustness. We establish the minimum UMSE and the minimum condition number for quantum detectors and provide concrete examples that can achieve optimal detector tomography. In order to enhance estimation precision, we also propose a two-step adaptive detector tomography algorithm and investigate how this adaptive strategy can be used to achieve efficient estimation of quantum detectors. Moreover, the superposition of coherent states are used as probe states for quantum detector tomography and the estimation error is analyzed. Numerical results demonstrate the effectiveness of both the proposed optimal and adaptive quantum detector tomography methods.