Optimal quantum detector tomography via linear regression estimation
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Wang, Y
Dong, D
Zhang, J
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Austin, TX, USA
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Abstract
Quantum detector tomography is a fundamental technique for calibrating quantum devices and performing quantum engineering tasks. In this paper, we design the optimal probe states for quantum detector tomography via linear regression estimation. In particular, two optimal criteria are adopted where one is related to upper bound of the mean squared error and the other concerns how robust the estimation result is with respect to measurement noise. We prove the optimal value based on the two criteria and provide two illustrative examples of optimal probe states.
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Proceedings of the IEEE Conference on Decision and Control
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Nanometrology
Optical technology
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Xiao, S; Wang, Y; Dong, D; Zhang, J, Optimal quantum detector tomography via linear regression estimation, Proceedings of the IEEE Conference on Decision and Control, 2021, pp. 4140-4145