Abstract

We present a topology optimization method for a 1D dielectric metasurface, coupling the classical fluctuations-trend analysis (FTA) and diamond-square algorithm (DSA). In classical FTA, a couple of device distributions termed fluctuation or mother and trends or father, with specific spectra, is initially generated. The spectral properties of the trend function allow one to efficiently target the basin of optimal solutions. For optimizing a 1D metasurface to deflect a normally incident plane wave into a given deflecting angle, a cosine-like function has been identified to be an optimal father profile, allowing one to efficiently target a basin of local minima. However, there is no efficient method to predict the father profile number of oscillations that effectively allows one to avoid undesirable local optima. It would be natural to suggest a randomization of the variable that controls the number of oscillations of the father function. However, one of the main drawbacks of the randomness searching process is that, combined with a gradient method, the algorithm can target undesirable local minima. The method proposed in this paper improves the possibility of classical FTA to avoid the trapping of undesirable local optimal solutions. This is accomplished by extending the initial candidate family to higher-quality offspring that are generated due to the DSA. Doing so ensures that the main features of the best trends are stored in the genes of all offspring structures.

© 2020 Optical Society of America

Topology optimization of photonics devices: fluctuation-trend analysis concept; random initial conditions with Gaussian and Durden–Vesecky power density bandlimited spectra

Kofi Edee
J. Opt. Soc. Am. B 37(7) 2111-2120 (2020)

Topology-optimized freeform broadband optical metagrating for high-efficiency large-angle deflection

Yuting Xiao, Mingfeng Xu, Mingbo Pu, Yuhan Zheng, Fei Zhang, Yinghui Guo, Xiong Li, Xiaoliang Ma, and Xiangang Luo
J. Opt. Soc. Am. B 41(2) A52-A59 (2024)

Validation and characterization of algorithms and software for photonics inverse design

Mo Chen, Rasmus E. Christiansen, Jonathan A. Fan, Göktuğ Işiklar, Jiaqi Jiang, Steven G. Johnson, Wenchao Ma, Owen D. Miller, Ardavan Oskooi, Martin F. Schubert, Fengwen Wang, Ian A. D. Williamson, Wenjin Xue, and You Zhou
J. Opt. Soc. Am. B 41(2) A161-A176 (2024)

Design and optimization of ellipsoid scatterer-based metasurfaces via the inverse T-matrix method

Maksym V. Zhelyeznyakov, Alan Zhan, and Arka Majumdar
OSA Continuum 3(1) 89-103 (2020)

Guided-mode resonance filter optimal inverse design using one- and two-dimensional grating

Yaser Khorrami, Davood Fathi, and Raymond C. Rumpf
J. Opt. Soc. Am. B 37(2) 425-432 (2020)