Rapid and Robust High Order Spectral Solvers for Learning Photonic Structures

用于学习光子结构的快速、鲁棒的高阶谱求解器

• 批准号: 2111283
• 负责人: David Nicholls
• 金额: $ 42.08万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2111283&HistoricalAwards=false
• 关键词: Rapid; Robust; Order; Spectral; Solvers

Over the past two decades engineers have built optical devices with stunning capabilities of detection, sensing, and imaging. While intuition has been an invaluable guide in pushing the envelope of what is possible, the increasing complexity of design and the wide array of available components is rendering this approach ever more difficult. For this reason, numerical simulation has become an invaluable tool. As this approach becomes ever more pervasive, the search for rapid, robust, and highly accurate algorithms has become quite acute. The PI will enhance his class of simulation tools by exploring new avenues of numerical approximation, novel paths to enforcing the governing equations, and appealing to the powerful methods of Machine Learning (in particular, Deep Learning) to discover optimal parameter values for device design. The PI will also develop a rigorous analysis of these new numerical schemes in order to evaluate and validate their real-world performance. This project will provide support for one graduate student each year of the three year award.Over the past two decades engineers have built optical devices with stunning capabilities of detection, sensing, and imaging. While intuition and linearized models have been invaluable guides in pushing the envelope of what is possible, the increasing complexity of design and the wide array of available components is rendering this approach ever more difficult. For this reason, numerical simulation has become an invaluable tool. As this approach becomes ever more pervasive, the search for rapid, robust, and highly accurate algorithms has become quite acute. The PI will enhance his class of High-Order Spectral solvers with the following objectives: (1) Incorporating two-dimensional materials into his rapid and highly accurate three-dimensional "Field Expansions" vector Maxwell equation solver; (2) Expand his "High-Order Perturbation of Surfaces/Asymptotic Waveform Evaluation" algorithm for joint geometry/frequency perturbation to the three-dimensional vector Maxwell equations; (3) Extend his "High-Order Perturbation of Envelopes" algorithm for structural perturbations to this three--dimensional case; (4) Provide rigorous analytical justification for each of the latter two; and (5) Bring to bear the powerful new tools of Deep Learning to discover optimal parameter values for device design.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在过去的二十年里，工程师们已经制造出具有惊人探测、传感和成像能力的光学设备。虽然直觉一直是推动可能的极限的宝贵指南，但设计的复杂性和可用组件的广泛性使这种方法变得更加困难。因此，数值模拟已成为一种宝贵的工具。随着这种方法变得越来越普遍，寻找快速、健壮和高度精确的算法已经变得非常迫切。PI将通过探索数值近似的新途径，执行控制方程的新途径，以及吸引机器学习（特别是深度学习）的强大方法来发现设备设计的最佳参数值，从而增强他的仿真工具类。PI还将对这些新的数值方案进行严格的分析，以评估和验证它们在现实世界中的性能。该项目将在三年的奖励中每年为一名研究生提供支持。在过去的二十年里，工程师们已经制造出具有惊人探测、传感和成像能力的光学设备。虽然直觉和线性化模型在推动可能的极限方面是无价的指导，但设计的复杂性和可用组件的广泛排列使得这种方法变得更加困难。因此，数值模拟已成为一种宝贵的工具。随着这种方法变得越来越普遍，寻找快速、健壮和高度精确的算法已经变得非常迫切。PI将通过以下目标提高他的高阶光谱求解器：(1)将二维材料纳入他的快速和高精度的三维“场扩展”矢量麦克斯韦方程求解器；(2)将关节几何/频率摄动的“曲面高阶摄动/渐近波形评估”算法扩展到三维矢量Maxwell方程；(3)将结构扰动的“包络高阶摄动”算法推广到这种三维情况；(4)为后两者提供严格的分析理由；(5)利用强大的深度学习新工具来发现设备设计的最佳参数值。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

A high–order spectral algorithm for the numerical simulation of layered media with uniaxial hyperbolic materials

用于单轴双曲材料层状介质数值模拟的高阶谱算法

• DOI: 10.1016/j.jcp.2022.110961
• 发表时间: 2022
• 期刊: Journal of Computational Physics
• 影响因子: 4.1
• 作者: Nicholls, David P.

Data-Driven Design of Thin-Film Optical Systems using Deep Active Learning

使用深度主动学习的薄膜光学系统的数据驱动设计

• DOI: 10.1364/oe.459295
• 发表时间: 2022
• 期刊: Optics express
• 影响因子: 3.8
• 作者: Hong, Y.;Nicholls, D.
• 通讯作者: Nicholls, D.

Joint Geometry/Frequency Analyticity of Fields Scattered by Periodic Layered Media

• DOI: 10.1137/22m1477568
• 发表时间: 2023-06
• 期刊: SIAM Journal on Mathematical Analysis
• 影响因子: 2
• 作者: Matthew Kehoe;D. Nicholls