Resonate-and-fire photonic-electronic spiking neurons for fast and efficient light-enabled neuromorphic processing systems

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Adair, Andrew and Owen-Newns, Dafydd and Donati, Giovanni and Robertson, Joshua and Figueiredo, Jose and Wasige, Edward and Al-Taai, Qusay and Romeira, Bruno and Hejda, Matěj and Hurtado, Antonio (2026) Resonate-and-fire photonic-electronic spiking neurons for fast and efficient light-enabled neuromorphic processing systems. Communications Physics. ISSN 2399-3650 (In Press) (https://doi.org/10.1038/s42005-026-02694-5)

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Abstract

Neuromorphic computing seeks to replicate the spiking dynamics of biological neurons for brain-inspired computation. While electronic implementations of artificial spiking neurons have dominated to date, photonic approaches are attracting increasing research interest as they promise ultrafast, energy-efficient operation with low-crosstalk and high bandwidth. Nevertheless, existing pho-tonic neurons largely mimic integrate-and-fire models, but neuroscience shows that neurons also encode information through richer mechanisms, such as the frequency and temporal patterns of spikes. Here, we present a photonic–electronic resonate-and-fire (R&F) spiking neuron that responds to the temporal structure of high-speed optical inputs. This is based on a light-sensitive resonant tunnelling diode that produces excitable spikes in response to nanosecond, low-power (< 100 µW) optical signals at infrared telecom wavelengths. We experimentally demonstrate control of R&F dynamics through inter-pulse timing of the optical stimuli and applied bias voltage, achieving bandpass filtering of both analogue and digital inputs. The R&F neuron also supports optical fan-in via wavelength-division multiplexed inputs from four vertical-cavity surface-emitting lasers (VCSELs). This photonic-electronic neuron exhibits key functionalities — including spike-frequency filtering, temporal pattern recognition, and digital-to-spiking conversion — critical for neuromorphic optical processing. Our approach establishes a pathway toward low-power, high-speed temporal information processing for light-enabled neuromorphic computing.

ORCID iDs

Adair, Andrew ORCID logoORCID: https://orcid.org/0009-0006-7205-9695, Owen-Newns, Dafydd ORCID logoORCID: https://orcid.org/0000-0001-6592-8465, Donati, Giovanni ORCID logoORCID: https://orcid.org/0000-0001-6156-8394, Robertson, Joshua ORCID logoORCID: https://orcid.org/0000-0001-6316-5265, Figueiredo, Jose, Wasige, Edward, Al-Taai, Qusay, Romeira, Bruno, Hejda, Matěj and Hurtado, Antonio ORCID logoORCID: https://orcid.org/0000-0002-4448-9034;
CORE (COnnecting REpositories)