Towards Photonic Band Diagram Generation with Transformer-Latent Diffusion Models
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| Main Authors: | , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866914071593353216 |
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| author | Delchevalerie, Valentin Roy, Nicolas Bougaham, Arnaud Mayer, Alexandre Frénay, Benoît Lobet, Michaël |
| author_facet | Delchevalerie, Valentin Roy, Nicolas Bougaham, Arnaud Mayer, Alexandre Frénay, Benoît Lobet, Michaël |
| contents | 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. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2510_01749 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Towards Photonic Band Diagram Generation with Transformer-Latent Diffusion Models Delchevalerie, Valentin Roy, Nicolas Bougaham, Arnaud Mayer, Alexandre Frénay, Benoît Lobet, Michaël Optics Computer Vision and Pattern Recognition 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. |
| title | Towards Photonic Band Diagram Generation with Transformer-Latent Diffusion Models |
| topic | Optics Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2510.01749 |