Engineering of multiple bound states in the continuum by latent representation of freeform structures

Ronghui Lin; Zahrah Alnakhli; Xiaohang Li

doi:10.1364/PRJ.415655

Engineering of multiple bound states in the continuum by latent representation of freeform structures

Ronghui Lin, Zahrah Alnakhli, Xiaohang Li

Research output: Contribution to journal › Article › peer-review

17 Scopus citations

Abstract

We demonstrate a neural network capable of designing on-demand multiple symmetry-protected bound states in the continuum (BICs) in freeform structures with predefined symmetry. The latent representation of the freeform structures allows the tuning of the geometry in a differentiable, continuous way. We show the rich band inversion and accidental degeneracy in these freeform structures by interacting with the latent representation directly. Moreover, a high design accuracy is demonstrated for arbitrary control of multiple BIC frequencies by using a photonic property readout network to interpret the latent representation.

Original language	English (US)
Pages (from-to)	96-103
Number of pages	8
Journal	Photonics Research
Volume	9
Issue number	4
DOIs	https://doi.org/10.1364/PRJ.415655
State	Published - Mar 22 2021

Bibliographical note

KAUST Repository Item: Exported on 2021-04-14
Acknowledged KAUST grant number(s): BAS/1/1664-01-01, URF/1/3437-01-01, URF/1/3771-01-01
Acknowledgements: King Abdullah University of Science and Technology Baseline Fund (BAS/1/1664-01-01); Competitive Research Grants (URF/1/3437-01-01, URF/1/3771-01-01).

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Atomic and Molecular Physics, and Optics

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10.1364/PRJ.415655

https://repository.kaust.edu.sa/bitstream/10754/668714/1/20210117_BICNN_PR_unmarked.pdf

Cite this

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title = "Engineering of multiple bound states in the continuum by latent representation of freeform structures",

abstract = "We demonstrate a neural network capable of designing on-demand multiple symmetry-protected bound states in the continuum (BICs) in freeform structures with predefined symmetry. The latent representation of the freeform structures allows the tuning of the geometry in a differentiable, continuous way. We show the rich band inversion and accidental degeneracy in these freeform structures by interacting with the latent representation directly. Moreover, a high design accuracy is demonstrated for arbitrary control of multiple BIC frequencies by using a photonic property readout network to interpret the latent representation.",

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AB - We demonstrate a neural network capable of designing on-demand multiple symmetry-protected bound states in the continuum (BICs) in freeform structures with predefined symmetry. The latent representation of the freeform structures allows the tuning of the geometry in a differentiable, continuous way. We show the rich band inversion and accidental degeneracy in these freeform structures by interacting with the latent representation directly. Moreover, a high design accuracy is demonstrated for arbitrary control of multiple BIC frequencies by using a photonic property readout network to interpret the latent representation.

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Engineering of multiple bound states in the continuum by latent representation of freeform structures

Abstract

Bibliographical note

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