神经网络辅助的超路由器用于光纤模式和极化解复杂化
Yu Zhao1,2, Huijiao Wang1, Tian Huang1
1Electronic Information School, and School of Microelectronics, Wuhan University, Wuhan 430072, China.
Nanophotonics (Berlin, Germany)
|December 5, 2024
概括
一个新的神经网络辅助元路由器可以同时管理多个维度的光纤模式,包括强度和极化. 这一突破提高了未来光纤通信和光学互连应用的数据传输能力.
科学领域:
- 光电学是指光电子产品.
- 在Metasurfaces上使用.
- 光纤光学是指光纤的使用.
背景情况:
- 数据爆炸需要先进的光纤通信技术.
- 当前模式的解复数器缺乏多维模式处理 (强度,偏振).
- 这限制了它们在空间分割多重复合 (SDM) 中的有效性.
研究的目的:
- 为光纤通信开发一个多维模式解复合器.
- 为了利用神经网络优化的超表面进行模式识别.
- 增强数据传输能力和设备功能.
主要方法:
- 设计了一个神经网络辅助的元路由器,使用单一的元表面层.
- 用神经网络技术优化了元表面,用于模式识别.
- 实验性地描述了一个四种模式的元路由器,处理两个空间状态和两个极化状态.
主要成果:
- 超路由器成功地解复了四种光纤模式.
- 模式因其强度分布和极化状态而有所区分.
- 模式被路由到不同的空间区域进行识别.
结论:
- 拟议的框架为先进的光纤模式解复合提供了一个范例.
- 它使得超简单,超紧的设备具有增强的传输能力.
- 这项技术为通信和计算中的智能光学互连铺平了道路.
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