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- W4385262017 abstract "Quantum tomography is a widely applicable method for reconstructing unknown quantum states and processes. However, its applications in quantum technologies usually also require estimating the difference between prepared and target quantum states with relivable confidence intervals. In this work, we suggest a computationally efficient and reliable scheme for determining well-justified error bars for quantum tomography. We approximate the probability distribution of the Hilbert-Schmidt distance between the target state and the estimation, which is given by the linear inversion, by calculating its moments. We also present a generalization of this approach for quantum process tomography. We benchmark our approach for a number of quantum tomography protocols using both simulated and experimental data. The obtained results pave a way to the use of the suggested scheme for complete characterization of quantum systems of various nature." @default.
- W4385262017 created "2023-07-26" @default.
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- W4385262017 date "2023-07-24" @default.
- W4385262017 modified "2023-09-27" @default.
- W4385262017 title "Reliable confidence regions for quantum tomography using distribution moments" @default.
- W4385262017 doi "https://doi.org/10.48550/arxiv.2307.12823" @default.
- W4385262017 hasPublicationYear "2023" @default.
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