Machine learning trains an ensemble optimal control scheme to pick optimal measurement times for non-Markovian quantum noise parameters, reaching near Cramér-Rao bound precision.
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Radioactive molecules combine nuclear and molecular properties to offer enhanced sensitivity for detecting new physics beyond the Standard Model.
A review of time-reversal and interaction-based readout in cavity QED for quantum metrology, covering SATIN, scrambling-enhanced metrology, and related schemes.
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Learning Non-Markovian Noise via Ensemble Optimal Control
Machine learning trains an ensemble optimal control scheme to pick optimal measurement times for non-Markovian quantum noise parameters, reaching near Cramér-Rao bound precision.
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Radioactive Molecules as Laboratories of Fundamental Physics
Radioactive molecules combine nuclear and molecular properties to offer enhanced sensitivity for detecting new physics beyond the Standard Model.
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Time-Reversal and Reversible Dynamics in Cavity QED for Quantum Metrology
A review of time-reversal and interaction-based readout in cavity QED for quantum metrology, covering SATIN, scrambling-enhanced metrology, and related schemes.