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Conference Paper: Nanophotonic inverse design using artificial neural network

TitleNanophotonic inverse design using artificial neural network
Authors
Peurifoy, JohnShen, YichenYang, YiJing, LiCano-Renteria, FidelJoannopoulos, JohnTegmark, MaxSoljacˇic´, Marin
Issue Date2017
Citation
Optics InfoBase Conference Papers, 2017, v. Part F66-FiO 2017 How to Cite?
DOI: http://dx.doi.org/10.1364/FIO.2017.FTh4A.4
AbstractWe propose a neural network approach to inverse design nanophotonic objects. Using a fully connected artificial neural network, the method finds the geometry of a spherical nanoparticle that match a desired scattering spectrum - either at a single wavelength, or at a broad-band.
Persistent Identifierhttp://hdl.handle.net/10722/317053

 

DC FieldValueLanguage
dc.contributor.authorPeurifoy, John-
dc.contributor.authorShen, Yichen-
dc.contributor.authorYang, Yi-
dc.contributor.authorJing, Li-
dc.contributor.authorCano-Renteria, Fidel-
dc.contributor.authorJoannopoulos, John-
dc.contributor.authorTegmark, Max-
dc.contributor.authorSoljacˇic´, Marin-
dc.date.accessioned2022-09-19T06:18:41Z-
dc.date.available2022-09-19T06:18:41Z-
dc.date.issued2017-
dc.identifier.citationOptics InfoBase Conference Papers, 2017, v. Part F66-FiO 2017-
dc.identifier.urihttp://hdl.handle.net/10722/317053-
dc.description.abstractWe propose a neural network approach to inverse design nanophotonic objects. Using a fully connected artificial neural network, the method finds the geometry of a spherical nanoparticle that match a desired scattering spectrum - either at a single wavelength, or at a broad-band.-
dc.languageeng-
dc.relation.ispartofOptics InfoBase Conference Papers-
dc.titleNanophotonic inverse design using artificial neural network-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1364/FIO.2017.FTh4A.4-
dc.identifier.scopuseid_2-s2.0-85035104450-
dc.identifier.volumePart F66-FiO 2017-

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