多任务拓优化光子设备在低维里埃域通过深度学习的多任务拓优化
Simei Mao1, Lirong Cheng1, Houyu Chen1
1Tsinghua-Berkeley Shenzhen Institute and Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.
Nanophotonics (Berlin, Germany)
|December 5, 2024
概括
我们开发了一个深度神经网络 (DNN) 用于光子反向设计. 这种方法可以同时快速优化多个复杂的光学设备,大大减少设计时间和资源.
科学领域:
- 光子学 是一个光子学.
- 计算电磁学的计算.
- 材料科学是一种材料科学.
背景情况:
- 光学提供紧,功能和可制造的集成设备.
- 优化自由形光学设备是复杂的,需要广泛的电磁模拟,特别是在多设备设计.
研究的目的:
- 引入一种使用深度神经网络 (DNN) 的新型拓优化方法,以实现光子设备的高效多任务反向设计.
- 为了加速高性能自由形光学设备的设计过程.
主要方法:
- 在低维里埃域中使用深度神经网络 (DNN) 进行拓优化.
- DNN从目标光学响应预测低频里埃元件,以重建设备几何形状,删除高频元件以简化设计空间.
主要成果:
- 该DNN成功地设计了多个波长的波器即时和同时高精度.
- 转移学习使得完全新目标的快速优化成为可能,大大减少了设计代.
- 该方法通过设计与波导合的单光子源来证明了通用性.
结论:
- DNN辅助的拓优化大大减少了光子设备多任务优化所需的时间和资源.
- 这种方法可以大规模设计和应用各种自由形式的光子装置.
相关概念视频
Ampere-Maxwell's Law: Problem-Solving
544
A parallel-plate capacitor with capacitance C, whose plates have area A and separation distance d, is connected to a resistor R and a battery of voltage V. The current starts to flow at t = 0. What is the displacement current between the capacitor plates at time t? From the properties of the capacitor, what is the corresponding real current?
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
To solve the problem, we can use the equations from the analysis of an RC circuit and Maxwell's version of Ampère's law.
For the first part of...
544
Linear Approximation in Frequency Domain
85
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
85
Linear Approximation in Time Domain
63
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
63


