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Constraining Continuous Topology Optimizations to Discrete Solutions for Photonic Applications

Ballew, Conner and Roberts, Gregory and Zheng, Tianzhe and Faraon, Andrei (2023) Constraining Continuous Topology Optimizations to Discrete Solutions for Photonic Applications. ACS Photonics . ISSN 2330-4022. doi:10.1021/acsphotonics.2c00862. (In Press)

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Photonic topology optimization is a technique used to find the permittivity distribution of a device that optimizes an electromagnetic figure-of-merit. Two common versions are used: continuous density-based optimizations that optimize a gray scale permittivity defined over a grid, and discrete level-set optimizations that optimize the shape of the material boundary of a device. In this work we present a method for constraining a continuous optimization such that it is guaranteed to converge to a discrete solution. This is done by inserting a constrained suboptimization with low computational overhead cost at each iteration of an overall gradient-based optimization. The technique adds only one hyperparameter with straightforward behavior to control the aggressiveness of binarization. Computational examples are provided to analyze the hyperparameter behavior, show this technique can be used in conjunction with projection filters, show the benefits of using this technique to provide a nearly discrete starting point for subsequent level-set optimization, and show that an additional hyperparameter can be introduced to control the overall material/void fraction. This method excels for problems where the electromagnetic figure-of-merit is majorly affected by the binarization requirement and situations where identifying suitable hyperparameter values becomes challenging with existing methods.

Item Type:Article
Related URLs:
URLURL TypeDescription ItemDiscussion Paper
Ballew, Conner0000-0003-4854-8342
Zheng, Tianzhe0000-0001-7058-5196
Faraon, Andrei0000-0002-8141-391X
Additional Information:This work was supported by the Defense Advanced Research Projects Agency EXTREME Program (HR00111720035), the Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, U.S.A., under a contract with the National Aeronautics and Space Administration (APRA 399131. and PDRDF 107614-19AW0079), the National Institutes of Health (NIH) Brain Initiative Program Grant NIH 1R21EY029460-01, and Caltech Rothenberg Innovation Initiative.
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)HR00111720035
NASA/JPL/CaltechAPRA 399131.
NASA/JPL/CaltechPDRDF 107614-19AW0079
Rothenberg Innovation Initiative (RI2)UNSPECIFIED
Record Number:CaltechAUTHORS:20230206-9587900.22
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:119065
Deposited By: Research Services Depository
Deposited On:09 Mar 2023 21:32
Last Modified:09 Mar 2023 21:32

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