Manifold learning for knowledge discovery and design in nanophotonics

Yashar Kiarashi; Mohammadreza Zandehshahvar; Ali Adibi

doi:10.1117/12.2590199

5 March 2021 Manifold learning for knowledge discovery and design in nanophotonics

Yashar Kiarashi, Mohammadreza Zandehshahvar, Ali Adibi

Proceedings Volume 11694, Photonic and Phononic Properties of Engineered Nanostructures XI; 116940M (2021) https://doi.org/10.1117/12.2590199
Event: SPIE OPTO, 2021, Online Only

Abstract

The systematic realization of the nature of the optical functionalities requires significant knowledge about the influence of nanostructure features on the propagation of electromagnetic waves. Due to the lack of such valuable information, cumbersome numerical calculations are currently the prevalent approach in designing nanostructures. In this talk, we introduce a novel technique based on manifold learning to reduce the complexity of the design problems. The developed algorithms provide valuable insights about the feasibility of a desired optical response and the roles of design parameters in forming the response through low-dimensional visualization. This extracted underlying information can be employed in different settings to accelerate the design of electromagnetic nanostructures for a wide range of applications.

Conference Presentation

Citation Download Citation

Yashar Kiarashi, Mohammadreza Zandehshahvar, and Ali Adibi "Manifold learning for knowledge discovery and design in nanophotonics", Proc. SPIE 11694, Photonic and Phononic Properties of Engineered Nanostructures XI, 116940M (5 March 2021); https://doi.org/10.1117/12.2590199

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