Numerical optimization identifies non-Gaussian quantum states that outperform Gaussian states for sensing under loss and phase noise, with up to 2.2 dB advantage persisting under homodyne detection.
Extremal properties of the variance and the quantum Fisher information
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abstract
We show that the variance is its own concave roof. For rank-2 density matrices and operators with zero diagonal elements in the eigenbasis of the density matrix, we prove analytically that the quantum Fisher information is four times the convex roof of the variance. Strong numerical evidence suggests that this statement is true even for operators with nonzero diagonal elements or density matrices with a rank larger than 2. We also find that within the different types of generalized quantum Fisher information considered in [D. Petz, J. Phys. A: Math. Gen. 35, 929 (2002); P. Gibilisco, F. Hiai, and D. Petz, IEEE Trans. Inf. Theory 55, 439 (2009)], after appropriate normalization, the quantum Fisher information is the largest. Hence, we conjecture that the quantum Fisher information is four times the convex roof of the variance even for the general case.
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Optimized Quantum States for Sensing in the Presence of Loss and Phase Noise
Numerical optimization identifies non-Gaussian quantum states that outperform Gaussian states for sensing under loss and phase noise, with up to 2.2 dB advantage persisting under homodyne detection.