First multimode quantum model of pure-Kerr PDCS predicts single- and two-mode squeezing plus quantum dispersive waves, with up to 20 dB squeezing limited by losses.
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Ultralow-loss Si3N4 PICs generate path-encoded EPR pairs (F=0.9875) and fuse them into four-photon GHZ states at F=0.943(8) and 27 Hz—two orders of magnitude above prior silicon-photonic rates.
Continuous-variable photonic platform with 20,000-mode cluster state simulates advection transport equation, achieving relative errors of 0.8% and 0.92% on first- and second-order moments via homodyne readout.
Reinforcement learning controls photonic circuits to prepare cubic-phase states at 96% success and directly generate quartic-phase gates with photon-number-resolving measurements.
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.
citing papers explorer
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Quantum Dispersive Waves and Multimode Squeezing in Pure-Kerr Parametrically Driven Cavity Solitons
First multimode quantum model of pure-Kerr PDCS predicts single- and two-mode squeezing plus quantum dispersive waves, with up to 20 dB squeezing limited by losses.
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An ultralow-loss integrated photonic platform for discrete-variable quantum information processing
Ultralow-loss Si3N4 PICs generate path-encoded EPR pairs (F=0.9875) and fuse them into four-photon GHZ states at F=0.943(8) and 27 Hz—two orders of magnitude above prior silicon-photonic rates.
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Analog photonic simulator for large-scale transport
Continuous-variable photonic platform with 20,000-mode cluster state simulates advection transport equation, achieving relative errors of 0.8% and 0.92% on first- and second-order moments via homodyne readout.
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Deep reinforcement learning for near-deterministic preparation of cubic- and quartic-phase gates in photonic quantum computing
Reinforcement learning controls photonic circuits to prepare cubic-phase states at 96% success and directly generate quartic-phase gates with photon-number-resolving measurements.
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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.