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Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
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概括

一个新的混合物概率采样网络 (MPSN) 通过提高复杂结构的精度来改进纳米光子反向设计. 这种方法优化了结构配置,以提高设备的性能.

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科学领域:

  • 纳米光子学 纳米光子学
  • 计算电磁学的计算.
  • 材料科学是一种材料科学.

背景情况:

  • 高精度的反向设计对于推进纳米光子设备至关重要.
  • 现有的方法,如混合密度网络 (MDN),由于光学性能和结构之间的一对多映射,与复杂的结构作斗争.
  • 结构配置中较高的自由度限制了当前逆向设计方法的准确性.

研究的目的:

  • 为纳米光子设备开发一种新的,高精度的反向设计框架.
  • 在处理复杂的结构设计时,克服现有方法的精度限制.
  • 通过改进的反向设计,实现增强和多功能纳米光子设备的创建.

主要方法:

  • 建议采样增强的MDN,称为混合物概率采样网络 (MPSN).
  • 使用一个端到端的框架,输出结构参数的混合高斯分布 (MGD).
  • 实施选择策略,在网络培训中使用最小化与真实数据相对误差的样本.

主要成果:

  • 在纳米光子结构色彩设计中达到高精度高达99.9%.
  • 获得的平均绝对误差小于0.002.
  • 对于具有更高自由度的结构,在反向设计中表现出卓越的性能.

结论:

  • 拟议的MPSN有效地解决了纳米光子反向设计中的一对多映射的挑战.
  • 这项工作为解决纳米光子学中复杂的反向设计问题提供了一条途径.
  • 开发的框架有助于设计具有增强功能的复杂纳米光子设备.