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Artificial Intelligence in a Photonic Temporal Processor
Youlve Chen, Jinlong Xiang, Yimin Hu +13
Optical neural networks (ONNs) promise high-throughput and energy-efficient artificial intelligence, yet essentially all implementations so far encode information across space eith…
On-chip Multimode Opto-electronic Neural Network
Jinlong Xiang, Youlve Chen, Chaojun Xu +5
Opto-electronic computing combines the complementary strengths of photonics and electronics to deliver ultrahigh computational throughput with high energy efficiency. However, its…
Deep Photonic Reservoir Computing with On-chip Nonlinearity
Jinlong Xiang, Youlve Chen, Yuchen Yin +6
Reservoir computing, renowned for its low training cost, has emerged as a promising lightweight paradigm for efficient spatiotemporal processing,it remains challenging to realize d…
Reconfigurable non-Abelian geometric phase in hybrid integrated photonics
Youlve Chen, Jiaxin Zhang, Jinlong Xiang +4
The non-Abelian geometric phase possesses the capability of enabling robust and fault-resilient unitary transformations, making it a cornerstone of holonomic quantum computation. T…
Observation of generic U(m) non-Abelian holonomy in photonics
Youlve Chen, Jinlong Xiang, An He +3
Non-Abelian geometric phases form the foundation of fault-tolerant holonomic quantum computation. An "all-geometric" approach leveraging these phases enables robust unitary operati…
Direct tensor processing with coherent light
Yufeng Zhang, Xiaobing Liu, Chenguang Yang +7
Tensor processing is the cornerstone of modern technological advancements, powering critical applications in data analytics and artificial intelligence. While optical computing off…