用贝叶斯优化自动设计宽带非互易热辐射器，性能远超人工设计。
Automated design of nonreciprocal thermal emitters via Bayesian optimization
- 结合贝叶斯优化与重参数化，从简单结构逐步优化出高效设计。
- 仅用少量层数实现5到40微米波段的宽频非互易发射。
- 适合需要高性能热管理或能量调控的器件设计者参考。
打破基尔霍夫热辐射定律的非互易热辐射器在热能应用中具有重要潜力。其带宽与角度范围的设计通常依赖物理直觉。本文提出一种通用数值方法，以掺杂磁光材料和磁外尔半金属为模型材料，聚焦无图案多层结构，通过贝叶斯优化与重参数化结合，从低效结构出发逐步提升宽带非互易性。结果表明，该方法可发现仅用较少层数即可在5至40微米波段实现宽带非互易发射的结构，性能和简洁性均显著优于当前基于直觉的最先进设计。
原文摘要 · Abstract (English)
Nonreciprocal thermal emitters that break Kirchhoff's law of thermal radiation promise exciting applications for thermal and energy applications. The design of the bandwidth and angular range of the nonreciprocal effect, which directly affects the performance of nonreciprocal emitters, typically relies on physical intuition. In this study, we present a general numerical approach to maximize the nonreciprocal effect. We choose doped magneto-optic materials and magnetic Weyl semimetal materials as model materials and focus on pattern-free multilayer structures. The optimization randomly starts from a less effective structure and incrementally improves the broadband nonreciprocity through the combination of Bayesian optimization and reparameterization. Optimization results show that the proposed approach can discover structures that can achieve broadband nonreciprocal emission at wavelengths from 5 to 40 micrometers using only a fewer layers, significantly outperforming current state-of-the-art designs based on intuition in terms of both performance and simplicity.
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