Multi-BOWS: multi-fidelity multi-objective Bayesian optimization with warm starts for nanophotonic structure design
Multi-BOWS: multi-fidelity multi-objective Bayesian optimization with warm starts for nanophotonic structure design
复制标题
Multi-BOWS：纳米光子结构设计的多保真度多目标贝叶斯优化和热启动
DOI：
10.1039/d3dd00177f
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发表时间：
2024
期刊：
影响因子：
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通讯作者：
Leu, Paul W.
中科院分区：
文献类型：
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作者：
Kim, Jungtaek;Li, Mingxuan;Li, Yirong;Gómez, Andrés;Hinder, Oliver;Leu, Paul W.
光学器件的设计是一个复杂而耗时的过程。为了简化这个过程，我们提出了一个新的框架，多保真度多目标贝叶斯优化与热启动，称为多BOWS。这种方法通过管理多个竞争目标并在设计过程中利用多保真度评估来自动发现新的纳米光子结构。我们采用Multi-BOWS方法设计专门用于透明电磁屏蔽的光学器件，这一挑战需要平衡可见光透明度和有效的电磁波防护。我们的方法利用了这样一种理解，即使用较粗的网格网格进行模拟的速度更快，但精度低于使用较密集的网格网格的模拟。与早期的多保真度多目标方法不同，Multi-BOWS从更快、更不准确的评估开始，我们称之为“热启动”，然后转移到密集的网格网格以提高准确性。因此，对于这项工作中研究的纳米光子结构，Multi-BOWS在Pareto前沿下的归一化面积比仅低保真度和仅高保真度技术大3.2-89.9%，这测量了透明度和屏蔽效果之间的平衡。此外，我们的方法优于现有的多保真度方法，获得0.5-10.3%的帕累托前沿下的感兴趣的结构的归一化面积。
The design of optical devices is a complex and time-consuming process. To simplify this process, we present a novel framework of multi-fidelity multi-objective Bayesian optimization with warm starts, called Multi-BOWS. This approach automatically discovers new nanophotonic structures by managing multiple competing objectives and utilizing multi-fidelity evaluations during the design process. We employ our Multi-BOWS method to design an optical device specifically for transparent electromagnetic shielding, a challenge that demands balancing visible light transparency and effective protection against electromagnetic waves. Our approach leverages the understanding that simulations with a coarser mesh grid are faster, albeit less accurate than those using a denser mesh grid. Unlike the earlier multi-fidelity multi-objective method, Multi-BOWS begins with faster, less accurate evaluations, which we refer to as “warm-starting,” before shifting to a dense mesh grid to increase accuracy. As a result, Multi-BOWS demonstrates 3.2–89.9% larger normalized area under the Pareto frontier, which measures a balance between transparency and shielding effectiveness, than low-fidelity only and high-fidelity only techniques for the nanophotonic structures studied in this work. Moreover, our method outperforms an existing multi-fidelity method by obtaining 0.5–10.3% larger normalized area under the Pareto frontier for the structures of interest.