ORCID
Rodrick Kuate Defo: 0000-0002-4278-8196
Document Type
Datasets
Date
2026
Keywords
density of photonic states convergence, design region area convergence, optimized design regions
Language
English
Funder(s)
Syracuse University
Acknowledgements
R.K.D. acknowledges financial support that made this work possible from the College of Engineering and Computer Science of Syracuse University. The authors also acknowledge that the work reported on in this paper was substantially performed using Zest, the Syracuse University research computing high-performance computing cluster.
Disciplines
Electrical and Computer Engineering
Description/Abstract
We propose a topology-optimization framework for optimizing finite structures of arbitrary shape by combining density-based methods with level-set approaches. We first optimize regular polygonal structures to suppress the photonic density of states and find that the best performing polygon is consistent with a tiling of space with hexagonal unit cells. We next show that introducing cavities into hexagonal structures further suppresses the photonic density of states, particularly when the cavity is also hexagonal. Such a result would find application in the design of fiber-optic cables. We then describe an approach for optimizing arbitrary x-simple or y-simple designs that can recover finite supercells of a hexagonal unit cell. Our approach can therefore discover the symmetry of photonic-crystal primitive unit cells that significantly suppress the photonic density of states for a given set of material parameters within a single optimization. For structures where the shape of the design region varied during the optimization, the last 2*Nctrl entries of the optimized design region data correspond to boundary y coordinates normalized by the length of the design region in y.
Recommended Citation
Mishra, Prakash; Joshi, Sukhad Dnyanesh; Hatzis, Quintin A.; Bahulikar, Aditya; Gursoy, M. Cenk; and Kuate Defo, Rodrick, "Data for: Optimizing Finite Structures to Suppress the Photonic Density of States" (2026). Electrical Engineering and Computer Science - All Scholarship. 252.
https://surface.syr.edu/eecs/252
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
