Fast edge detection in time-series using photonic-electronic spiking resonant tunnelling diode neurons

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Owen-Newns, Dafydd and Donati, Giovanni and Adair, Andrew and Black, Dylan and Wasige, Edward and Figueiredo, José M L and Romeira, Bruno and Robertson, Joshua and Hurtado, Antonio; (2025) Fast edge detection in time-series using photonic-electronic spiking resonant tunnelling diode neurons. In: 2025 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC). 2025 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) . IEEE, DEU. ISBN 979-8-3315-1252-1 (https://doi.org/10.1109/cleo/europe-eqec65582.2025...)

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Abstract

Neuromorphic (brain-inspired) computing, implemented on optoelectronic photonic hardware, has strong potential to transform the way we perform processing due to the low power requirements and high operating speed of the platform. Resonant Tunnelling Diodes (RTDs) are one such optoelectronic device that has previously demonstrated the neuron-like spiking dynamics required for neuromorphic processing [1], [2]. RTDs have a highly non-linear IV relationship (due to quantum tunnelling across the double barrier quantum well) that can be exploited electrically or optically, to achieve their neuromorphic functionality.

ORCID iDs

Owen-Newns, Dafydd, Donati, Giovanni ORCID logoORCID: https://orcid.org/0000-0001-6156-8394, Adair, Andrew, Black, Dylan, Wasige, Edward, Figueiredo, José M L, Romeira, Bruno, Robertson, Joshua ORCID logoORCID: https://orcid.org/0000-0001-6316-5265 and Hurtado, Antonio ORCID logoORCID: https://orcid.org/0000-0002-4448-9034;
  • Item type:Book Section
    ID code:93916
    Dates:
    Date
    Event
    15 August 2025
    Published
    Subjects:Science > Physics
    Department:Faculty of Science > Physics
    Depositing user: Pure Administrator
    Date deposited:25 Aug 2025 11:57
    Last modified:03 Nov 2025 08:48
    URI:https://strathprints.strath.ac.uk/id/eprint/93916
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