Introduces non-Gaussian control parameters (s0, δ0) and an optimization method that reduces photon detections by a factor of three and increases preparation probability by nearly 10^8 for GKP states, with gains shown across cat, cubic phase, and random states.
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Convex optimization formulations and an analytical symplectic trace expression are introduced to reconstruct physical Gaussian covariance matrices and witness genuine multipartite entanglement from experimental data.
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Beyond Stellar Rank: Control Parameters for Scalable Optical Non-Gaussian State Generation
Introduces non-Gaussian control parameters (s0, δ0) and an optimization method that reduces photon detections by a factor of three and increases preparation probability by nearly 10^8 for GKP states, with gains shown across cat, cubic phase, and random states.
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Revisiting Gaussian genuine entanglement witnesses with modern software
Convex optimization formulations and an analytical symplectic trace expression are introduced to reconstruct physical Gaussian covariance matrices and witness genuine multipartite entanglement from experimental data.