19 citations · 38 across the 14 of their papers we have counts for
7 papers · 1 filter
Incorporating rank-free coupling and external field via an incoherent modulated spatial photonic Ising machine
Ze Zheng, Yuegang Li, Hang Xu +3
Spatial photonic Ising machines offer a novel optical platform for optimization and spin-model simulation, but existing diffraction-based schemes rely on auxiliary spins or multipl…
Optical diffraction neural networks assisted computational ghost imaging through dynamic scattering media
Yue-Gang Li, Ze Zheng, Jun-jie Wang +4
Ghost imaging leverages a single-pixel detector with no spatial resolution to acquire object echo intensity signals, which are correlated with illumination patterns to reconstruct…
Discovering autonomous quantum error correction via deep reinforcement learning
Yue Yin, Tailong Xiao, Xiaoyang Deng +3
Quantum error correction is essential for fault-tolerant quantum computing. However, standard methods relying on active measurements may introduce additional errors. Autonomous qua…
Real-time imaging through dynamic scattering media enabled by fixed optical modulations
Yuegang Li, Junjie Wang, Tailong Xiao +5
Dynamic scattering remains a significant challenge to the practical deployment of anti-scattering imaging. Existing methods, such as transmission matrix measurements, iterative wav…
Learning to Restore Heisenberg Limit in Noisy Quantum Sensing via Quantum Digital Twin
Hang Xu, Tailong Xiao, Jingzheng Huang +2
Quantum sensors leverage nonclassical resources to achieve sensing precision at the Heisenberg limit, surpassing the standard quantum limit attainable through classical strategies.…
Towards Heisenberg limit without critical slowing down via quantum reinforcement learning
Hang Xu, Tailong Xiao, Jingzheng Huang +3
Critical ground states of quantum many-body systems have emerged as vital resources for quantum-enhanced sensing. Traditional methods to prepare these states often rely on adiabati…
Quantum neural compressive sensing for ghost imaging
Xinliang Zhai, Tailong Xiao, Jingzheng Huang +2
Demonstrating the utility of quantum algorithms is a long-standing challenge, where quantum machine learning becomes one of the most promising candidate that can be resorted to. In…