A framework to compute resonances arising from multiple scattering

Jan David Fischbach, Fridtjof Betz, Nigar Asadova, Pietro Tassan, Darius Urbonas, Thilo Stöferle, Rainer F. Mahrt, Sven Burger, Carsten Rockstuhl, Felix Binkowski, Thomas Jebb Sturges
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Abstract

A sample refinement strategy suitable for accurately locating a large number of poles is introduced. We tie the AAA algorithm into an automatic differentiation framework to efficiently differentiate multi-scattering resonance calculations. The resulting resonance solver allows for efficient gradient-based optimization, demonstrated here by the inverse design of an integrated exciton-polariton cavity. This contribution serves as an important step towards efficient resonance calculations in a variety of multi-scattering scenarios, such as inclusions in stratified media, periodic lattices, and scatterers with arbitrary shapes. A sample refinement strategy suitable for accurately locating a large number of poles is introduced. We tie the AAA algorithm into an automatic differentiation framework to efficiently differentiate multi-scattering resonance calculations. The resulting resonance solver allows for efficient gradient-based optimization, demonstrated here by the inverse design of an integrated exciton-polariton cavity. This contribution serves as an important step towards efficient resonance calculations in a variety of multi-scattering scenarios, such as inclusions in stratified media, periodic lattices, and scatterers with arbitrary shapes.
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计算多重散射共振的框架
介绍了一种适用于精确定位大量极点的样本细化策略。我们将 AAA 算法与自动微分框架相结合,以高效微分多散射共振计算。由此产生的共振求解器允许进行基于梯度的高效优化,这里通过反向设计一个集成的激子-极化子腔来证明这一点。这一贡献是在各种多散射情况下实现高效共振计算的重要一步,如分层介质中的夹杂物、周期晶格和任意形状的散射体。我们介绍了一种适用于精确定位大量极点的样本细化策略。我们将 AAA 算法与自动微分框架相结合,以高效地微分多散射共振计算。由此产生的共振求解器允许进行基于梯度的高效优化,并在此通过反向设计集成的激子-极化子腔进行了演示。这是在多种多散射情况下(如分层介质中的夹杂物、周期晶格和任意形状的散射体)进行高效共振计算的重要一步。
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