From the 1 of 5 linked papers with an AI index.
4 papers · 1 filter
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…
Non-Local and Non-Markovian Effects of a Microscopic Two-Level Defect in Superconducting Quantum Circuits
Yang Gao, Yujia Zhang, Huikai Xu +12
Microscopic two-level systems (TLS) -- ubiquitous atomic-scale defects in solid-state quantum devices -- are a dominant source of qubit decoherence, yet their role is often conside…
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…
Quantum ensemble learning with a programmable superconducting processor
Jiachen Chen, Yaozu Wu, Zhen Yang +30
Quantum machine learning is among the most exciting potential applications of quantum computing. However, the vulnerability of quantum information to environmental noises and the c…