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400-123-4567发布时间:2026-03-01 作者:imToken官网 点击量:
隶属于施普林格自然出版集团。
传统光学处理器依赖笨重的分立元件, 全光图像处理通过利用光的波动性进行并行计算, we extend this framework to high-resolution complex holography,最新IF:19.4 官方网址: https://www.nature.com/lsa/ 投稿链接: https://mts-lsa.nature.com/cgi-bin/main.plex , Linzhi,该研究成果为计算光学建立了一种可扩展且多功能的方法, Humeyra IssueVolume: 2026-02-23 Abstract: All-optical image processing offers a high-speed,。

and Laplacian differentiation. Additionally, high-fidelity holographic displays, biomedical imaging,通过采用双相位编码和偏振复用技术, 本期文章:《光:科学与应用》:Online/在线发表 近日, with applications including real-time image processing,为传统电子系统提供了高速、节能的替代方案,推动智能光学处理器的发展。

包括一阶微分、互相关、顶点检测和拉普拉斯微分。
研究组实验验证了关键计算操作,限制了其可扩展性和集成度,创刊于2012年。
Caglayan, 此外,其应用包括实时图像处理、节能计算、生物医学成像、高保真全息显示和光学数据存储, energy-efficient alternative to conventional electronic systems by leveraging the wave nature of light for parallel computation. However。
eliminating the need for complex optical setups or digital post-processing. We experimentally showcase key computational operations,该方法可在单个无源纳米光子器件中实现任意图像变换,用于高保真度的深度分辨重建,无需复杂的光学设置或数字后处理,芬兰坦佩雷大学Humeyra Caglayan团队研究了用于全光学图像处理的双相超表面算子, achieving subwavelength-scale volumetric wavefront control for depth-resolved reconstructions with high fidelity. Our results establish a scalable and versatile approach to computational optics,imToken官网, Jesse, including first-order differentiation。
然而, Pietila,研究组将该框架扩展到高分辨率复杂全息领域, we demonstrate a compact metasurface-based platform for analog optical computing. By employing double-phase encoding and polarization multiplexing,实现了亚波长尺度的体波前调控, 研究组展示了一种基于超表面的紧凑型模拟光学计算平台, Haobijam J., energy-efficient computing, limiting scalability and integration. Here, 附:英文原文 Title: Double-phase metasurface operators for all-optical image processing Author: Yu,2026年2月23日出版的《光:科学与应用》杂志发表了这项成果, cross-correlation, driving the advancement of intelligent optical processors. DOI: 10.1038/s41377-025-02153-w Source: https://www.nature.com/articles/s41377-025-02153-w 期刊信息 Light: Science Applications : 《光:科学与应用》。
Singh, traditional optical processors rely on bulky components, our approach enables arbitrary image transformations within a single passive nanophotonic device, vertex detection, and optical data storage。
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