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Deep learning enabled design of complex transmission matrices for universal optical components

hal.structure.identifierOptoelectronics Research Centre [Southampton] [ORC]
hal.structure.identifierSchool of Physics and Astronomy [Southampton]
dc.contributor.authorDINSDALE, Nicholas
hal.structure.identifierSchool of Physics and Astronomy [Southampton]
hal.structure.identifierÉquipe Matériaux et Procédés pour la Nanoélectronique [LAAS-MPN]
dc.contributor.authorWIECHA, Peter
hal.structure.identifierOptoelectronics Research Centre [Southampton] [ORC]
hal.structure.identifierSchool of Physics and Astronomy [Southampton]
dc.contributor.authorDELANEY, Matthew
hal.structure.identifierOptoelectronics Research Centre [Southampton] [ORC]
dc.contributor.authorREYNOLDS, Jamie
hal.structure.identifierOptoelectronics Research Centre [Southampton] [ORC]
dc.contributor.authorEBERT, Martin
hal.structure.identifierOptoelectronics Research Centre [Southampton] [ORC]
dc.contributor.authorZEIMPEKIS, Ioannis
hal.structure.identifierOptoelectronics Research Centre [Southampton] [ORC]
dc.contributor.authorTHOMSON, David
hal.structure.identifierOptoelectronics Research Centre [Southampton] [ORC]
dc.contributor.authorREED, Graham
hal.structure.identifierLaboratoire Photonique, Numérique et Nanosciences [LP2N]
dc.contributor.authorLALANNE, Philippe
hal.structure.identifierLaboratoire Photonique, Numérique et Nanosciences [LP2N]
dc.contributor.authorVYNCK, Kevin
hal.structure.identifierSchool of Physics and Astronomy [Southampton]
dc.contributor.authorMUSKENS, Otto
dc.date.accessioned2023-05-12T10:40:00Z
dc.date.available2023-05-12T10:40:00Z
dc.date.issued2021-01
dc.identifier.issn2330-4022
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/181597
dc.description.abstractEnRecent breakthroughs in photonics-based quantum, neuromorphic and analogue processing have pointed outthe need for new schemes for fully programmable nanophotonic devices. Universal optical elements based oninterferometer meshes are underpinning many of these new technologies, however this is achieved at the cost ofan overall footprint that is very large compared to the limited chip real estate, restricting the scalability of thisapproach. Here, we propose an ultracompact platform for low-loss programmable elements using the complextransmission matrix of a multi-port multimode waveguide. Our approach allows the design of arbitrary trans-mission matrices using patterns of weakly scattering perturbations, which is successfully achieved by means of adeep learning inverse network. The demonstrated platform allows control over both the intensity and phase in amultiport device at a four orders reduced device footprint compared to conventional technologies, thus openingthe door for large-scale integrated universal networks
dc.language.isoen
dc.publisherAmerican Chemical Society
dc.title.enDeep learning enabled design of complex transmission matrices for universal optical components
dc.typeArticle de revue
dc.identifier.doi10.1021/acsphotonics.0c01481
dc.subject.halPhysique [physics]/Physique [physics]/Optique [physics.optics]
dc.identifier.arxiv2009.11810
bordeaux.journalACS photonics
bordeaux.page283-295
bordeaux.volume8
bordeaux.hal.laboratoriesLaboratoire Photonique, Numérique et Nanosciences (LP2N) - UMR 5298*
bordeaux.issue1
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-02994029
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-02994029v1
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