Time-domain topology optimization for dispersive and broadband inverse design in nanophotonics

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OriginalspracheEnglisch
Titel des SammelwerksMachine Learning in Photonics
Herausgeber/-innenFrancesco Ferranti, Mehdi Keshavarz Hedayati, Andrea Fratalocchi
Herausgeber (Verlag)SPIE
Seitenumfang3
ISBN (elektronisch)9781510673526
PublikationsstatusVeröffentlicht - 18 Juni 2024
VeranstaltungMachine Learning in Photonics 2024 - Strasbourg, Frankreich
Dauer: 8 Apr. 202412 Apr. 2024

Publikationsreihe

NameProceedings of SPIE - The International Society for Optical Engineering
Band13017
ISSN (Print)0277-786X
ISSN (elektronisch)1996-756X

Abstract

The adjoint method is an efficient technique for the topology optimization of complex nanophotonic systems, including nanostructures, metasurfaces and integrated optical circuits. While such method has been traditionally used in the frequency domain, its extension to the time domain opens new opportunities for wideband optimization of dispersive materials for applications ranging from broadband absorbers to enhanced quantum emitters in dispersive environments. We propose a topology optimization technique for the inverse design of linear optical materials with arbitrary dispersion and anisotropy. We introduce a general adjoint scheme in the time-domain based on the complex-conjugate pole-residue pair (CCPR) model. This approach has the advantage of treating dispersive media and broadband response naturally in a single simulation run. We implement this framework within the finite-difference time-domain (FDTD) method and investigate the method for optimizing metallic and dielectric nanoantennas over the optical spectral range of 350-1000 nm. The combination of the method with parallel computing enables the large-scale inverse design of nanostructures in 3D with extreme field confinement. Nanostructures found via inverse design and featuring the intriguing anapole effect are also discussed. This effect enables nanostructures that show field enhancement, negligible scattering, and low losses. The possibility of reducing losses in plasmonic nanostructures via inverse design is an interesting possibility offered by the method and may open new avenues towards the realization of transparent plasmonic metamaterials for applications in linear and nonlinear nanophotonics.

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Time-domain topology optimization for dispersive and broadband inverse design in nanophotonics. / Gedeon, Johannes; Hassan, Emadeldeen; Evlyukhin, Andrey B. et al.
Machine Learning in Photonics. Hrsg. / Francesco Ferranti; Mehdi Keshavarz Hedayati; Andrea Fratalocchi. SPIE, 2024. 130170G (Proceedings of SPIE - The International Society for Optical Engineering; Band 13017).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandAufsatz in KonferenzbandForschungPeer-Review

Gedeon, J, Hassan, E, Evlyukhin, AB & Lesina, AC 2024, Time-domain topology optimization for dispersive and broadband inverse design in nanophotonics. in F Ferranti, MK Hedayati & A Fratalocchi (Hrsg.), Machine Learning in Photonics., 130170G, Proceedings of SPIE - The International Society for Optical Engineering, Bd. 13017, SPIE, Machine Learning in Photonics 2024, Strasbourg, Frankreich, 8 Apr. 2024. https://doi.org/10.1117/12.3026073
Gedeon, J., Hassan, E., Evlyukhin, A. B., & Lesina, A. C. (2024). Time-domain topology optimization for dispersive and broadband inverse design in nanophotonics. In F. Ferranti, M. K. Hedayati, & A. Fratalocchi (Hrsg.), Machine Learning in Photonics Artikel 130170G (Proceedings of SPIE - The International Society for Optical Engineering; Band 13017). SPIE. https://doi.org/10.1117/12.3026073
Gedeon J, Hassan E, Evlyukhin AB, Lesina AC. Time-domain topology optimization for dispersive and broadband inverse design in nanophotonics. in Ferranti F, Hedayati MK, Fratalocchi A, Hrsg., Machine Learning in Photonics. SPIE. 2024. 130170G. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.3026073
Gedeon, Johannes ; Hassan, Emadeldeen ; Evlyukhin, Andrey B. et al. / Time-domain topology optimization for dispersive and broadband inverse design in nanophotonics. Machine Learning in Photonics. Hrsg. / Francesco Ferranti ; Mehdi Keshavarz Hedayati ; Andrea Fratalocchi. SPIE, 2024. (Proceedings of SPIE - The International Society for Optical Engineering).
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AU - Gedeon, Johannes

AU - Hassan, Emadeldeen

AU - Evlyukhin, Andrey B.

AU - Lesina, Antonio Calà

N1 - Publisher Copyright: © 2024 SPIE.

PY - 2024/6/18

Y1 - 2024/6/18

N2 - The adjoint method is an efficient technique for the topology optimization of complex nanophotonic systems, including nanostructures, metasurfaces and integrated optical circuits. While such method has been traditionally used in the frequency domain, its extension to the time domain opens new opportunities for wideband optimization of dispersive materials for applications ranging from broadband absorbers to enhanced quantum emitters in dispersive environments. We propose a topology optimization technique for the inverse design of linear optical materials with arbitrary dispersion and anisotropy. We introduce a general adjoint scheme in the time-domain based on the complex-conjugate pole-residue pair (CCPR) model. This approach has the advantage of treating dispersive media and broadband response naturally in a single simulation run. We implement this framework within the finite-difference time-domain (FDTD) method and investigate the method for optimizing metallic and dielectric nanoantennas over the optical spectral range of 350-1000 nm. The combination of the method with parallel computing enables the large-scale inverse design of nanostructures in 3D with extreme field confinement. Nanostructures found via inverse design and featuring the intriguing anapole effect are also discussed. This effect enables nanostructures that show field enhancement, negligible scattering, and low losses. The possibility of reducing losses in plasmonic nanostructures via inverse design is an interesting possibility offered by the method and may open new avenues towards the realization of transparent plasmonic metamaterials for applications in linear and nonlinear nanophotonics.

AB - The adjoint method is an efficient technique for the topology optimization of complex nanophotonic systems, including nanostructures, metasurfaces and integrated optical circuits. While such method has been traditionally used in the frequency domain, its extension to the time domain opens new opportunities for wideband optimization of dispersive materials for applications ranging from broadband absorbers to enhanced quantum emitters in dispersive environments. We propose a topology optimization technique for the inverse design of linear optical materials with arbitrary dispersion and anisotropy. We introduce a general adjoint scheme in the time-domain based on the complex-conjugate pole-residue pair (CCPR) model. This approach has the advantage of treating dispersive media and broadband response naturally in a single simulation run. We implement this framework within the finite-difference time-domain (FDTD) method and investigate the method for optimizing metallic and dielectric nanoantennas over the optical spectral range of 350-1000 nm. The combination of the method with parallel computing enables the large-scale inverse design of nanostructures in 3D with extreme field confinement. Nanostructures found via inverse design and featuring the intriguing anapole effect are also discussed. This effect enables nanostructures that show field enhancement, negligible scattering, and low losses. The possibility of reducing losses in plasmonic nanostructures via inverse design is an interesting possibility offered by the method and may open new avenues towards the realization of transparent plasmonic metamaterials for applications in linear and nonlinear nanophotonics.

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ER -

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