通过混合概率抽样网络实现超精度,高容量和广泛的结构颜色
Zeyong Wei1,2,3,4,5, Weijie Xu1,2,3,4,5, Siyu Dong1,2,3,4,5
1School of Physics Science and Engineering, Tongji University, Shanghai, China.
Light, science & applications
|March 11, 2026
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.
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.
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