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◆ Nature nanotechnology2026-09-09

How nanophotonics can drive optical computing toward practical applications.

Yitong Chen, Guoqiang Yang, Tao Yan, Chunyang Tang, Jiamin Wu, Qionghai Dai

原始摘要(英文原文)· Original abstract
The rapid advancement of artificial intelligence (AI) imposes unprecedented speed and energy requirements on large-scale computation. Owing to its intrinsic high bandwidth, massive parallelism capacity and low energy consumption, optical computing is widely regarded as one of the most promising technologies to address AI computation demands. Here we offer a synthesis of photonic platforms that have already shown programmability, high integration density and stability, and that can support large-scale AI models, edge computing, and logic and scientific computing. We summarize the requirements that optical computing imposes on nanomaterials properties, architecture design, nanofabrication and large-scale integration. Finally, we analyse commercial systems and provide a perspective on how nanotechnology-informed solutions can improve performance in terms of computing speed, scalability and complexity in optical computing.
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How nanophotonics can drive optical computing toward practical applications. — 科研速览 Science Skim