概括
我们开发了一个反向设计的介电超表面,使用人工神经网络进行紧的光学成像. 这项技术使任意角度图像继电器与偏差校正,超过传统的光学设计软件.
科学领域:
- 光学和光子学 在光学和光子学.
- 地表表面技术的技术.
- 在光学领域的人工智能.
背景情况:
- 便携式电子驱动对紧的光学成像系统的需求.
- 折叠光学系统需要光束方向和形状,以最大限度地减少尺寸和偏差.
- 现有的解决方案在微型系统的偏差校正方面面临挑战.
研究的目的:
- 为任意角图像继电器呈现一个反向设计的介电元面.
- 在光学成像系统中实现同时缩小尺寸和纠正偏差.
- 为了利用人工神经网络优化 metasurface 阶段反应.
主要方法:
- 介电元表面的反向设计.
- 使用人工神经网络优化超表面相位响应.
- 与Zemax OpticStudio.com中的全局优化进行比较.
- 超表面的设计,以实现优化的相形状.
主要成果:
- 超表面成功地执行任意角度图像继电器与偏差校正.
- 人工神经网络有效地弥补了偏移图像中的严重偏差.
- 与Zemax相比,提出的方法预测了优越的点差函数和减少的图像扭曲.
- 基于优化的相位形状,实现了功能性地表设计.
结论:
- 反向设计的介电超表面为紧的光学成像提供了一个有前途的解决方案.
- 人工神经网络是优化复杂光学组件 (如超表面) 的强大工具.
- 这种方法可以在微型电子设备中实现高性能成像.
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