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Review of numerical optimization techniques for meta-device design [Invited]

期刊

OPTICAL MATERIALS EXPRESS
卷 9, 期 4, 页码 1842-1863

出版社

Optica Publishing Group
DOI: 10.1364/OME.9.001842

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资金

  1. Defense Advanced Research Projects Agency (DARPA) [HR00111720032]
  2. U.S. Air Force [FA9550-18-1-0070]
  3. Office of Naval Research [N00014-16-1-2630]
  4. National Science Foundation (NSF)

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Optimization techniques have been indispensable for designing high-performance meta-devices targeted to a wide range of applications. In fact, today optimization is no longer an afterthought and is a fundamental tool for many optical and RF designers. Still, many devices presented in recent literature do not take advantage of optimization techniques. This paper seeks to address this by presenting both an introduction to and a review of several of the most popular techniques currently used for meta-device design. Additionally, emerging techniques like topology optimization and multi-objective optimization and their context to device design are thoroughly discussed. Moreover, attention is given to future directions in meta-device optimization such as surrogate-modeling and deep learning which have the potential to disrupt the fields of optical and radio frequency (RF) inverse-design. Finally, many design examples from the literature are presented and a flow-chart that provides guidance on how best to apply these optimization algorithms to a given problem is provided for the reader. (C) 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

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