Illustrated tutorial on global optimization in nanophotonics
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866910318194589696 |
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| author | Bennet, Pauline Langevin, Denis Essoual, Chaymae Khaireh-Walieh, Abdourahman Teytaud, Olivier Wiecha, Peter Moreau, Antoine |
| author_facet | Bennet, Pauline Langevin, Denis Essoual, Chaymae Khaireh-Walieh, Abdourahman Teytaud, Olivier Wiecha, Peter Moreau, Antoine |
| contents | Numerical optimization for the inverse design of photonic structures is a tool which is providing increasingly convincing results -- even though the wave nature of problems in photonics makes them particularly complex. In the meantime, the field of global optimization is rapidly evolving but is prone to reproducibility problems, making it harder to identify the right algorithms to use. This paper is thought as a tutorial on global optimization for photonic problems. We provide a general background on global optimization algorithms and a rigorous methodology for a physicist interested in using these tools -- especially in the context of inverse design. We suggest algorithms and provide explanations for their efficiency. We provide codes and examples as an illustration than can be run online, integrating quick simulation code and Nevergrad, a state-of-the-art benchmarking library. Finally, we show how physical intuition can be used to discuss optimization results and to determine whether the solutions are satisfactory or not. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2309_09760 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Illustrated tutorial on global optimization in nanophotonics Bennet, Pauline Langevin, Denis Essoual, Chaymae Khaireh-Walieh, Abdourahman Teytaud, Olivier Wiecha, Peter Moreau, Antoine Optics Computational Physics Numerical optimization for the inverse design of photonic structures is a tool which is providing increasingly convincing results -- even though the wave nature of problems in photonics makes them particularly complex. In the meantime, the field of global optimization is rapidly evolving but is prone to reproducibility problems, making it harder to identify the right algorithms to use. This paper is thought as a tutorial on global optimization for photonic problems. We provide a general background on global optimization algorithms and a rigorous methodology for a physicist interested in using these tools -- especially in the context of inverse design. We suggest algorithms and provide explanations for their efficiency. We provide codes and examples as an illustration than can be run online, integrating quick simulation code and Nevergrad, a state-of-the-art benchmarking library. Finally, we show how physical intuition can be used to discuss optimization results and to determine whether the solutions are satisfactory or not. |
| title | Illustrated tutorial on global optimization in nanophotonics |
| topic | Optics Computational Physics |
| url | https://arxiv.org/abs/2309.09760 |