Self-guided quantum state learning for mixed states
نویسندگان
چکیده
We provide an adaptive learning algorithm for tomography of general quantum states. Our proposal is based on the simultaneous perturbation stochastic approximation and applies to mixed qudit The salient features our are efficient post-processing in dimension d state, robustness against measurement channel noise, improved infidelity performance as compared contemporary state algorithms. A higher resilience noise makes suitable noisy intermediate-scale applications.
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ژورنال
عنوان ژورنال: Quantum Information Processing
سال: 2022
ISSN: ['1573-1332', '1570-0755']
DOI: https://doi.org/10.1007/s11128-022-03585-8