Dual-Frequency Quantum Phase Estimation Mitigates the Spectral Leakage of Quantum Algorithms

2022 
Quantum phase estimation is an important component in diverse quantum algorithms. However, it suffers from spectral leakage, when the reciprocal of the record length is not an integer multiple of the unknown phase, which incurs an accuracy degradation. For the existing single-sample estimation scheme, window-based methods have been proposed for spectral leakage mitigation. As a further advance, we propose a dual-frequency estimator, which asymptotically approaches the Cramér-Rao bound, when multiple samples are available. Numerical results show that the proposed estimator outperforms the existing window-based methods, when the number of samples is sufficiently high.
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