用扩散模型生成光子晶体能带图，加速逆向设计
Towards Photonic Band Diagram Generation with Transformer-Latent Diffusion Models
- 用Transformer提取结构特征，结合潜空间扩散模型生成能带图
- 首次实现基于扩散模型的能带图生成，可推广至任意三维结构
- 适合做光子器件逆向设计、快速仿真研究的研究者
光子晶体可在纳米尺度精细调控光传播，是光子与量子技术发展的核心。光子能带图（BDs）是研究这类非均匀结构中光传播的关键工具。然而，计算能带图需在多种构型下求解麦克斯韦方程组，数值开销大，尤其在逆向设计优化循环中更为显著。为此，我们提出首个基于扩散模型的能带图生成方法，具备扩展至任意三维结构的潜力。该方法将Transformer编码器（用于从输入结构提取上下文嵌入）与潜空间扩散模型相结合，生成对应能带图。此外，我们分析了为何Transformer与扩散模型能有效捕捉光子学中复杂的干涉与散射现象，为该领域新型代理建模策略提供新路径。
原文摘要 · Abstract (English)
Photonic crystals enable fine control over light propagation at the nanoscale, and thus play a central role in the development of photonic and quantum technologies. Photonic band diagrams (BDs) are a key tool to investigate light propagation into such inhomogeneous structured materials. However, computing BDs requires solving Maxwell's equations across many configurations, making it numerically expensive, especially when embedded in optimization loops for inverse design techniques, for example. To address this challenge, we introduce the first approach for BD generation based on diffusion models, with the capacity to later generalize and scale to arbitrary three dimensional structures. Our method couples a transformer encoder, which extracts contextual embeddings from the input structure, with a latent diffusion model to generate the corresponding BD. In addition, we provide insights into why transformers and diffusion models are well suited to capture the complex interference and scattering phenomena inherent to photonics, paving the way for new surrogate modeling strategies in this domain.
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