Fractional OAM charge ℓ=1.5 induces an optimal 67.5° GKP lattice rotation that reduces error rate 23.9× with <0.2% loss in Fisher information and yields 41% higher metrological capacity.
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Optimizing the squeezing phase in a correlated squeezed-thermal reservoir maximizes quantum Fisher information for phase and correlation parameters and reduces joint-estimation variance.
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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OAM-Induced Lattice Rotation Reveals a Fractional Optimum in Fault-Tolerant GKP Quantum Sensing
Fractional OAM charge ℓ=1.5 induces an optimal 67.5° GKP lattice rotation that reduces error rate 23.9× with <0.2% loss in Fisher information and yields 41% higher metrological capacity.
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From Independent to Joint: Enhancing Quantum Phase and Correlation Factor Estimation by Squeezed Reservoir Engineering
Optimizing the squeezing phase in a correlated squeezed-thermal reservoir maximizes quantum Fisher information for phase and correlation parameters and reduces joint-estimation variance.
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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.