continuous control 1hong-ou-mandel interference 1optical neural networks 1quantum photonics 1reinforcement learning 1
From the 1 of 3 linked papers with an AI index.
Showing quant-phShow all
3 papers · 1 filter
quant-ph2026
Quantum Optical Reinforcement Learning via Spectrum-Resolved Hong-Ou-Mandel Interference
Shaojun Wu, Jiahua Xu, Shan Jin +7
The paper presents a spectrum‑resolved Hong‑Ou‑Mandel (SR‑HOM) optical neural network that uses photon spectral modes as trainable resources to build a compact actor‑critic reinfor…
quant-ph2026
Deterministic Generation of Arbitrary Fock States via Resonant Subspace Engineering
Shan Jin, Ming Li, Weizhou Cai +10
Deterministic preparation of high-excitation Fock states is a central challenge in bosonic quantum information, with control complexity that generically explodes as the Hilbert spa…
quant-ph2026
Pareto Front Engineering of Dynamical Sweet Spots in Superconducting Qubits
Zhen Yang, Shan Jin, Yajie Hao +4
Operating superconducting qubits at dynamical sweet spots (DSSs) suppresses decoherence from low-frequency flux noise. A key open question is how long coherence can be extended und…