Covariance matrices for finite-dimensional DFT-related position-momentum pairs are fully characterized via unitary invariants, convex geometry, and SDP, yielding extremal states and application bounds.
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Integrating quantum catalysis, entanglement, and squeezing in a distributed quantum network yields better multiphase sensing precision than any two alone, approaching the Heisenberg limit, with partial catalysis outperforming global catalysis in both ideal and lossy cases.
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The uncertainty geometry of finite-dimensional position and momentum
Covariance matrices for finite-dimensional DFT-related position-momentum pairs are fully characterized via unitary invariants, convex geometry, and SDP, yielding extremal states and application bounds.
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Quantum-enhanced distributed network sensing using multiple quantum resources
Integrating quantum catalysis, entanglement, and squeezing in a distributed quantum network yields better multiphase sensing precision than any two alone, approaching the Heisenberg limit, with partial catalysis outperforming global catalysis in both ideal and lossy cases.