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24 November 2021 Bayesian optimization of photonic nanojets generated by multilayer dielectric structures
Dasen Zhang, Zhenzhen Liu, Guochao Wei, Zhaojun Hu, Jun Jun Xiao
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Proceedings Volume 12066, AOPC 2021: Micro-optics and MOEMS; 120660V (2021) https://doi.org/10.1117/12.2604996
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China
Abstract
We employ a Bayesian optimization (BO) approach coupled with electromagnetic solver to optimize the photonic nanojets (PNJs) respectively generated by a 2D cuboid and a 3D concentric cylinder. The operating wavelength is selected atλ = 632.8 nm. By optimizing a five-layer cuboid, we achieved a narrow PNJ with waist at the full width at half-maximum (FWHM) about w ~ 0.2λ and an ultra-long PNJ with a beam length 123λ , respectively. Whereas by optimizing 3D concentric cylinder, we achieved a narrow PNJ with waist at FWHM about w ~ 0.22λand ultra-long PNJ with a beam length 78λ , respectively. Furthermore, we explore the physics behind the PNJ phenomenon, such as the fundamentals of extreme PNJ generation and the relation between the objective intensity profile and the refractive index gradients across the structure. The proposed approach presents an alternative approach to the design of various photonic nanostructures and may provide conventionally-inaccessible physical insight to their functionalities.
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Dasen Zhang, Zhenzhen Liu, Guochao Wei, Zhaojun Hu, and Jun Jun Xiao "Bayesian optimization of photonic nanojets generated by multilayer dielectric structures", Proc. SPIE 12066, AOPC 2021: Micro-optics and MOEMS, 120660V (24 November 2021); https://doi.org/10.1117/12.2604996
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KEYWORDS
Photonic nanostructures
3D modeling
Dielectrics
Electromagnetism
Finite-difference time-domain method
Optimization (mathematics)
Computer simulations
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