期刊
NATURE PHYSICS
卷 10, 期 11, 页码 825-829出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/NPHYS3115
关键词
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资金
- US Army Research Office [W911NF-11-1-0068]
- Australian Research Council Centre of Excellence for Engineered Quantum Systems [CE110001013]
- Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), through the Army Research Office
- Lockheed Martin Corporation
- National Natural Science Foundation of China [11175094, 91221205]
- National Basic Research Program of China [2011CB9216002]
Extrinsic interference is routinely faced in systems engineering, and a common solution is to rely on a broad class of filtering techniques to afford stability to intrinsically unstable systems or isolate particular signals from a noisy background. Experimentalists leading the development of a new generation of quantum-enabled technologies similarly encounter time-varying noise in realistic laboratory settings. They face substantial challenges in either suppressing such noise for high-fidelity quantum operations(1) or controllably exploiting it in quantum-enhanced sensing(2-4) or system identification tasks(5,6), due to a lack of efficient, validated approaches to understanding and predicting quantum dynamics in the presence of realistic time-varying noise. In this work we use the theory of quantum control engineering(7,8) and experiments with trapped Yb-171(+) ions to study the dynamics of controlled quantum systems. Our results provide the first experimental validation of generalized filter-transfer functions casting arbitrary quantum control operations on qubits as noise spectral filters(9,10). We demonstrate the utility of these constructs for directly predicting the evolution of a quantum state in a realistic noisy environment as well as for developing novel robust control and sensing protocols. These experiments provide a significant advance in our understanding of the physics underlying controlled quantum dynamics, and unlock new capabilities for the emerging field of quantum systems engineering.
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