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Improving conditional generative adversarial networks for inverse design of plasmonic nanostructures using label projection and embedding methods
Umeå University, Faculty of Science and Technology, Department of Physics.
Umeå University, Faculty of Science and Technology, Department of Physics.ORCID iD: 0000-0003-0992-9871
Umeå University, Faculty of Science and Technology, Department of Physics.ORCID iD: 0000-0002-0143-1510
2025 (English)In: 2025 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2025, Institute of Electrical and Electronics Engineers (IEEE), 2025Conference paper, Published paper (Refereed)
Abstract [en]

We introduce label projection and embedding methods to improve generative adversarial networks. As proof of concept, we generate images of plasmonic nanostructures with different shapes by using a model trained on their linear optical response.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2025.
National Category
Atom and Molecular Physics and Optics
Identifiers
URN: urn:nbn:se:umu:diva-244576DOI: 10.1109/CLEO/EUROPE-EQEC65582.2025.11110418Scopus ID: 2-s2.0-105016177524ISBN: 9798331512521 (electronic)OAI: oai:DiVA.org:umu-244576DiVA, id: diva2:2005574
Conference
2025 Conference on Lasers and Electro-Optics Europe and European Quantum Electronics Conference, CLEO/Europe-EQEC 2025, Munich, Germany, 23-27 June, 2025.
Available from: 2025-10-10 Created: 2025-10-10 Last updated: 2025-10-10Bibliographically approved

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Persson, PetterHenriksson, NilsMaccaferri, Nicolò

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