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Probe optimization for quantum metrology via closed-loop learning control

Xiaodong Yang, Jayne Thompson, Ze Wu, Mile Gu, Xinhua Peng, Jiangfeng Du

2020npj Quantum Information34 citationsDOIOpen Access PDF

Abstract

Abstract Experimentally achieving the precision that standard quantum metrology schemes promise is always challenging. Recently, additional controls were applied to design feasible quantum metrology schemes. However, these approaches generally does not consider ease of implementation, raising technological barriers impeding its realization. In this paper, we circumvent this problem by applying closed-loop learning control to propose a practical controlled sequential scheme for quantum metrology. Purity loss of the probe state, which relates to quantum Fisher information, is measured efficiently as the fitness to guide the learning loop. We confirm its feasibility and certain superiorities over standard quantum metrology schemes by numerical analysis and proof-of-principle experiments in a nuclear magnetic resonance system.

Topics & Concepts

Quantum metrologyMetrologyQuantumQuantum sensorComputer scienceElectronic engineeringScheme (mathematics)Computer engineeringControl (management)Quantum computerQuantum technologyQuantum imagingQuantum error correctionQuantum networkMeasurement problemAlgorithmQuantum informationQuantum gateControl engineeringPhysicsQuantum controlQuantum algorithmQuantum Information and CryptographyQuantum Computing Algorithms and ArchitectureQuantum Mechanics and Applications
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