4 citations · 4 across the 2 of their papers we have counts for
3 papers
quant-ph2026
Quantum Optical Reinforcement Learning via Spectrum-Resolved Hong-Ou-Mandel Interference
Shaojun Wu, Jiahua Xu, Shan Jin +7
Hong-Ou-Mandel (HOM) interference-based optical neural networks can offer complexity advantages on benchmark learning tasks, but conventional readout compresses the coincidence spe…
quant-ph2025
Enhancing the reachability of variational quantum algorithms via input-state design
Shaojun Wu, Shan Jin, Abolfazl Bayat +1
Variational quantum algorithms (VQAs) face an inherent trade-off between expressivity and trainability: deeper circuits can represent richer states but suffer from noise accumulati…
quant-ph2025★ 4 cited
Fixed-point quantum continuous search algorithm with optimal query complexity
Shan Jin, Yuhan Huang, Shaojun Wu +4
Continuous search problems (CSPs), which involve finding solutions within a continuous domain, frequently arise in fields such as optimization, physics, and engineering. Unlike dis…