Optimal low-depth quantum signal-processing phase estimation
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| Publicado en: | Nature Communications vol. 16, no. 1 (2025), p. 1504 |
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| Publicado: |
Nature Publishing Group
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| Materias: | |
| Acceso en línea: | Citation/Abstract Full Text - PDF |
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| Resumen: | Quantum effects like entanglement and coherent amplification can be used to drastically enhance the accuracy of quantum parameter estimation beyond classical limits. However, challenges such as decoherence and time-dependent errors hinder Heisenberg-limited amplification. We introduce Quantum Signal-Processing Phase Estimation algorithms that are robust against these challenges and achieve optimal performance as dictated by the Cramér-Rao bound. These algorithms use quantum signal transformation to decouple interdependent phase parameters into largely orthogonal ones, ensuring that time-dependent errors in one do not compromise the accuracy of learning the other. Combining provably optimal classical estimation with near-optimal quantum circuit design, our approach achieves a standard deviation accuracy of 10−4 radians for estimating unwanted swap angles in superconducting two-qubit experiments, using low-depth ( < 10) circuits. This represents up to two orders of magnitude improvement over existing methods. Theoretically and numerically, we demonstrate the optimality of our algorithm against time-dependent phase errors, observing that the variance of the time-sensitive parameter φ scales faster than the asymptotic Heisenberg scaling in the small-depth regime. Our results are rigorously validated against the quantum Fisher information, confirming our protocol’s ability to achieve unmatched precision for two-qubit gate learning.Fault-tolerant quantum computing would require very high accuracy in quantum gate characterisation. Here, the authors introduce an optimal low-depth phase estimation method inspired by quantum signal processing, significantly improving gate calibration accuracy. |
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| ISSN: | 2041-1723 |
| DOI: | 10.1038/s41467-025-56724-x |
| Fuente: | Health & Medical Collection |