Enhanced light-matter interactions in dielectric nanostructures via machine-learning approach
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Xu, Lei; Rahmani, Mohsen; Ma, Yixuan; Smirnova, Daria; Zangeneh Kamali, Khosro; Deng, Fu; Chiang, Yan Kei; Huang, Lujun; Zhang, Haoyang; Gould, Stephen; Neshev, Dragomir; Miroshnichenko, Andrey
Description
A key concept underlying the specific functionalities of metasurfaces is the use of constituent components to shape the wavefront of the light on demand. Metasurfaces are versatile, novel platforms for manipulating the scattering, color, phase, or intensity of light. Currently, one of the typical approaches for designing a metasurface is to optimize one or two variables among a vast number of fixed parameters, such as various materials' properties and coupling effects, as well as the...[Show more]
dc.contributor.author | Xu, Lei | |
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dc.contributor.author | Rahmani, Mohsen | |
dc.contributor.author | Ma, Yixuan | |
dc.contributor.author | Smirnova, Daria | |
dc.contributor.author | Zangeneh Kamali, Khosro | |
dc.contributor.author | Deng, Fu | |
dc.contributor.author | Chiang, Yan Kei | |
dc.contributor.author | Huang, Lujun | |
dc.contributor.author | Zhang, Haoyang | |
dc.contributor.author | Gould, Stephen | |
dc.contributor.author | Neshev, Dragomir | |
dc.contributor.author | Miroshnichenko, Andrey | |
dc.date.accessioned | 2022-02-16T00:56:00Z | |
dc.date.available | 2022-02-16T00:56:00Z | |
dc.identifier.issn | 0277-786X | |
dc.identifier.uri | http://hdl.handle.net/1885/261192 | |
dc.description.abstract | A key concept underlying the specific functionalities of metasurfaces is the use of constituent components to shape the wavefront of the light on demand. Metasurfaces are versatile, novel platforms for manipulating the scattering, color, phase, or intensity of light. Currently, one of the typical approaches for designing a metasurface is to optimize one or two variables among a vast number of fixed parameters, such as various materials' properties and coupling effects, as well as the geometrical parameters. Ideally, this would require multidimensional space optimization through direct numerical simulations. Recently, an alternative, popular approach allows for reducing the computational cost significantly based on a deep-learning-assisted method. We utilize a deep-learning approach for obtaining high-quality factor (high-Q) resonances with desired characteristics, such as linewidth, amplitude, and spectral position. We exploit such high-Q resonances for enhanced light-matter interaction in nonlinear optical metasurfaces and optomechanical vibrations, simultaneously. We demonstrate that optimized metasurfaces achieve up to 400-fold enhancement of the third-harmonic generation; at the same time, they also contribute to 100-fold enhancement of the amplitude of optomechanical vibrations. This approach can be further used to realize structures with unconventional scattering responses. | |
dc.description.sponsorship | We are grateful to Andrey Sukhorukov, Yue Sun, and Camille Diffine for fruitful discussions. The authors acknowledge the funding support provided by the Australian Research Council (ARC). The work of A.E.M. was supported by UNSW Scientia Fellowship and ARC Discovery Project (DP170103778). M.R. sincerely appreciates funding from ARC Discovery Early Career Research Fellowship (DE170100250). D.S. acknowledges financial support from the Russian Foundation for Basic Research (Grants Nos. 18- 02-00381 and 19-02-00261) and the Australian Research Council (DE19010043). The authors appreciate the use of the Australian National Fabrication Facility (ANFF)–the ACT Node. | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en_AU | |
dc.publisher | SPIE - The International Society for Optical Engineering | |
dc.rights | © The Authors. | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.source | Proceedings of SPIE - International Society for Optical Engineering | |
dc.title | Enhanced light-matter interactions in dielectric nanostructures via machine-learning approach | |
dc.type | Journal article | |
local.description.notes | Imported from ARIES | |
local.identifier.citationvolume | 2 | |
dc.date.issued | 2020 | |
local.identifier.absfor | 100799 - Nanotechnology not elsewhere classified | |
local.identifier.ariespublication | U4474173xPUB58 | |
local.identifier.ariespublication | U4474173xPUB73 | |
local.publisher.url | http://spie.org/x1848.xml?WT.svl=mddp2 | |
local.type.status | Published Version | |
local.contributor.affiliation | Xu, Lei, College of Science, ANU | |
local.contributor.affiliation | Rahmani, Mohsen, College of Science, ANU | |
local.contributor.affiliation | Ma, Yixuan, Nankai University | |
local.contributor.affiliation | Smirnova, Daria, College of Science, ANU | |
local.contributor.affiliation | Kamali, Khosro, College of Science, ANU | |
local.contributor.affiliation | Deng, Fu, University of New South Wales, | |
local.contributor.affiliation | Chiang, Yan Kei , University of New South Wales | |
local.contributor.affiliation | Huang, Lujun, University of New South Wales | |
local.contributor.affiliation | Zhang, Haoyang, University of New South Wales, | |
local.contributor.affiliation | Gould, Stephen, College of Engineering and Computer Science, ANU | |
local.contributor.affiliation | Neshev, Dragomir, College of Science, ANU | |
local.contributor.affiliation | Miroshnichenko, Andrey, College of Science, ANU | |
dc.relation | http://purl.org/au-research/grants/arc/DP170103778 | |
dc.relation | http://purl.org/au-research/grants/arc/DE170100250 | |
local.bibliographicCitation.issue | 2 | |
local.bibliographicCitation.startpage | 026003-1 | |
local.bibliographicCitation.lastpage | 026003-11 | |
local.identifier.doi | 10.1117/1.AP.2.2.026003 | |
local.identifier.absseo | 869999 - Manufacturing not elsewhere classified | |
dc.date.updated | 2020-12-13T07:27:27Z | |
dcterms.accessRights | Open Access | |
dc.provenance | Published by SPIE and CLP under a Creative Commons Attribution 4.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI. | |
dc.rights.license | Creative Commons Attribution 4.0 Unported License | |
Collections | ANU Research Publications |
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