Resonate-and-Fire Photonic-Electronic Spiking Neuron with a Photo-Detecting Resonant Tunnelling Diode
As the popularity of artificial intelligence (AI) continues to grow exponentially, so does the demand for efficient and fast (state-of-the-art) computing hardware. Neuromorphic (brain-inspired) systems, specifically in photonics, have the capability to improve processing for AI by leveraging the low operating powers and inherent high-speed of lasers and opto-electronic devices. Several different neuronal models exist for artificial neurons, and one opto-electronic device that has shown promise in realising spike-based neuronal functionality is the resonant tunnelling diode (RTD) [1]. Thresholding, refractoriness, and integration have been achieved with RTDs (optically and electrically), thanks to their non-linear properties. Further, opto-electronic networks and different processing tasks have been proposed in theory by coupling spiking RTDs to lasers and photodetectors [2].
Authors
- J. M. L. Figueiredo (ORCID: https://orcid.org/0000-0001-5668-7073)
- Bruno Romeira (ORCID: https://orcid.org/0000-0002-1485-6665)
- Joshua Robertson (ORCID: https://orcid.org/0000-0001-6316-5265)
- Antonio Hurtado (ORCID: https://orcid.org/0000-0002-4448-9034)
- Edward Wasige (ORCID: https://orcid.org/0000-0001-5014-342X)
- Andrew Adair
- Dafydd Owen-Newns (ORCID: https://orcid.org/0000-0001-6592-8465)
Institutions
- University of Lisbon (PT)
- University of Strathclyde (GB)
- International Iberian Nanotechnology Laboratory (PT)
- University of Glasgow (GB)
- Universidade Nova de Lisboa (PT)
Publication Details
- Published
- 2025-06-23
- DOI
- https://doi.org/10.1109/cleo/europe-eqec65582.2025.11110901
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- UK Research and Innovation