Real-time quantum control of spin-coupling damping and application in atomic spin gyroscopes
Integrating classical estimation and control theory with quantum systems holds potential for quantum measurement improvement. Here, we report a real-time linear quadratic regulator (LQR) optimal control for spin damping in electron-nuclear spin-coupling regime. The aim is a quicker response and enha...
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Veröffentlicht in: | Cell reports physical science 2024-02, Vol.5 (2), p.101832, Article 101832 |
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Sprache: | eng |
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Zusammenfassung: | Integrating classical estimation and control theory with quantum systems holds potential for quantum measurement improvement. Here, we report a real-time linear quadratic regulator (LQR) optimal control for spin damping in electron-nuclear spin-coupling regime. The aim is a quicker response and enhanced noise suppression for precision quantum measurements. Using a Kalman quantum observer with electron spin data, we estimate the quantum state of nondirectly observable nuclear spin. LQR full-state feedback optimal control is applied to achieve faster spin-coupling damping. Demonstrated in an atomic spin gyroscope, our method significantly enhances dynamic response with a 4.3-fold improvement in rotational bandwidth. It also boosts long-term stability and measurement sensitivity by 62.9%, presenting a promising avenue to elevate spin-coupling ensemble performance in quantum measurements.
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•Integration of quantum spin systems with modern control methods•Kalman state estimation in quantum spin-coupling system•Closed-loop control architecture for the spin-coupling system•Improved bandwidth and noise suppression through feedback control
Integrating classical estimation and control theory with quantum systems holds the potential to enhance measurement performance. For electron-nuclear spin coupling systems, spin states estimation is achieved with Kalman observation, and implementation of LQR strategy is used to construct feedback control systems, resulting in improved response speed and noise suppression capabilities. |
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ISSN: | 2666-3864 2666-3864 |
DOI: | 10.1016/j.xcrp.2024.101832 |