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Coherent dimension reduction with integrated photonic circuits exploiting tailored disorder

The number of systems that are investigated for computation in the physical domain has increased substantially in the recent past. Optical and photonic systems have drawn high interest due to their potential for carrying out energy-efficient linear operations and perceived advantages in latency and...

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Hauptverfasser: Wendland, Daniel (VerfasserIn) , Becker, Marlon (VerfasserIn) , Brückerhoff-Plückelmann, Frank (VerfasserIn) , Bente, Ivonne (VerfasserIn) , Busch, Kurt (VerfasserIn) , Risse, Benjamin (VerfasserIn) , Pernice, Wolfram (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: February 24, 2023
In: Journal of the Optical Society of America. B, Optical physics
Year: 2023, Jahrgang: 40, Heft: 3, Pages: B35-B40
ISSN:1520-8540
DOI:10.1364/JOSAB.479898
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1364/JOSAB.479898
Verlag, lizenzpflichtig, Volltext: https://opg.optica.org/josab/abstract.cfm?uri=josab-40-3-B35
Volltext
Verfasserangaben:Daniel Wendland, Marlon Becker, Frank Brückerhoff-Plückelmann, Ivonne Bente, Kurt Busch, Benjamin Risse, and Wolfram H.P. Pernice
Beschreibung
Zusammenfassung:The number of systems that are investigated for computation in the physical domain has increased substantially in the recent past. Optical and photonic systems have drawn high interest due to their potential for carrying out energy-efficient linear operations and perceived advantages in latency and general computation speed. One of the main challenges remains to scale up integrated photonic designs to integration densities required for meaningful computation, in particular for matrix-vector multiplications. To address upscaling for photonic computing, here we propose an on-chip scheme for dimension reduction of the input data using random scattering. Exploiting tailored disorder allows us to reduce the incoming dimensionality by more than an order of magnitude, which a shallow subsequent network can use to perform image recognition tasks with high accuracy.
Beschreibung:Gesehen am 21.04.2023
Beschreibung:Online Resource
ISSN:1520-8540
DOI:10.1364/JOSAB.479898

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