Error-mitigated photonic quantum circuit Born machine
Alexia Salavrakos, Tigran Sedrakyan, James Mills, Shane Mansfield, and Rawad Mezher
Phys. Rev. A 111, L030401 (2025) - Published 18 March, 2025
This work focuses on generative learning in the framework of photonic quantum computing. The authors present a quantum circuit Born machine tailored to linear optics. They apply an error-mitigation technique that deals with photon loss to the model, and show that the error mitigation improves model training through simulations and experiments on a quantum photonic integrated processor.
Biased estimator channels for classical shadows
Zhenyu Cai, Adrian Chapman, Hamza Jnane, and Bálint Koczor
Phys. Rev. A 111, L030402 (2025) - Published 21 March, 2025
The classical shadow framework is paired with the well-studied bias-variance tradeoff to further reduce the number of shots needed to estimate properties of quantum states.
Verifying energy-time entanglement via nonlocal dispersion cancellation
Jin-Woo Chae, Heebong Seo, U-Shin Kim, and Yoon-Ho Kim
Phys. Rev. A 111, L030403 (2025) - Published 25 March, 2025
The authors experimentally demonstrate direct verification of continuous-variable energy-time entanglement via nonlocal dispersion cancellation under realistic telecom conditions, effectively emulating photon propagation through a 379-km optical fiber. They observe a significant violation of the separability criterion by 32 standard deviations, confirming robust entanglement suitable for secure long-distance quantum communication.















