All-optical diffractive neural networks (DNNs) offer low latency, low energy consumption, and massive parallelism. However, their scalability in terms of network scale and multi-task processing remains limited. Here, we experimentally demonstrate a large-scale metasurface-based diffractive learning machine for angle-mu...
Ming-Cheng Luo, Jian-Min Xiong, Jia-Yong Peng et al.· 0 citations
The rapid growth of artificial intelligence (AI) demands high-performance hardware accelerators. Photonic computing with microring resonators (MRRs) has attracted significant interest, but conventional architectures use MRRs primarily as scalar weights, with speed constrained by the resonance linewidth of ~ 10 GHz...
Shao-Jie Liu, Teng-Ji Xu, Ben-Shan Wang et al.· Nature Communications· 0 citations
Recent advances in in-sensor computing demonstrate the potential of integrating sensing and computation at the perception front end; however, many existing approaches rely on customized devices, facing scalability, uniformity, and power challenges. Here, we present a cross-platform in-sensor computing strategy that emb...
Ming-Qiang Wang, Hui Yu, Ben-Shan Wang et al.· Nature Communications· 0 citations
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