Efficient, inverse large-scale optimization of diffractive lenses
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arXiv
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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866912603245117440 |
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| author | Gerhardt, Marco Hong, Sungkun Lee, Moosung |
| author_facet | Gerhardt, Marco Hong, Sungkun Lee, Moosung |
| contents | Scalable photonic optimization holds the promise of significantly enhancing the performance of diffractive lenses across a wide range of photonic applications. However, the high computational cost of conventional full three-dimensional electromagnetic solvers has thus far been a major obstacle to large-scale-domain optimization. Here, we address this limitation by integrating the convergent Born series with the adjoint-field optimization framework, enabling inverse design with its domain size up to a $110 \times 110 \times 46\ μ\text{m}^3$ volume$-$corresponding to 0.1 gigavoxels$-$using a single, cost-effective graphics card. The optimized lens achieves a 9% improvement in axial resolution and a 20% increase in focusing efficiency compared to a standard Fresnel lens of identical diameter and numerical aperture. These gains point to immediate application opportunities for optimizing high-performance microscopy, photolithography, and optical trapping systems using modest computational resources. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_15411 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Efficient, inverse large-scale optimization of diffractive lenses Gerhardt, Marco Hong, Sungkun Lee, Moosung Optics Applied Physics Scalable photonic optimization holds the promise of significantly enhancing the performance of diffractive lenses across a wide range of photonic applications. However, the high computational cost of conventional full three-dimensional electromagnetic solvers has thus far been a major obstacle to large-scale-domain optimization. Here, we address this limitation by integrating the convergent Born series with the adjoint-field optimization framework, enabling inverse design with its domain size up to a $110 \times 110 \times 46\ μ\text{m}^3$ volume$-$corresponding to 0.1 gigavoxels$-$using a single, cost-effective graphics card. The optimized lens achieves a 9% improvement in axial resolution and a 20% increase in focusing efficiency compared to a standard Fresnel lens of identical diameter and numerical aperture. These gains point to immediate application opportunities for optimizing high-performance microscopy, photolithography, and optical trapping systems using modest computational resources. |
| title | Efficient, inverse large-scale optimization of diffractive lenses |
| topic | Optics Applied Physics |
| url | https://arxiv.org/abs/2506.15411 |