Tunable presynaptic weighting in optoelectronic spiking neurons built with laser-coupled resonant tunneling diodes

Zhang, Weikang; Hejda, Matěj; Малышева, Е. И.; Al-Taai, Qusay Raghib Ali; Javaloyes, J.; Wasige, Edward; Figueiredo, J. M. L.; Calzadilla, V.M. Dolores; Romeira, Bruno; Hurtado, Antonio

doi:10.1088/1361-6463/aca914

Cited by 6 publications

(1 citation statement)

References 38 publications

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“…phase-change materials [5], optical modulators [6,7], and semiconductor lasers [8][9][10][11], are a few highlight photonic devices that have achieved neuromorphic or neuromimetic operation. Similarly, electro-optic technologies such quantum resonant tunnelling structures [12,13], amongst others (see [14] for a review), have now also been proposed as suitable device platforms for brain-inspired computing hardware components. With one of the major benefits of photonics being the highly-reduced energy requirements, the recent demonstrations of photonic artificial neural networks (pANNs) [15][16][17][18][19] and reservoir computing systems [20][21][22][23] make an exciting case for photonics being the platform at the forefront of potentially sustainable neuromorphic computing.…”

Section: Introductionmentioning

confidence: 99%

VCSEL-based photonic spiking neural networks for ultrafast detection and tracking

Robertson,

Kirkland,

Di Caterina

et al. 2024

Neuromorph. Comput. Eng.

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Inspired by efficient biological spike-based neural networks, we demonstrate for the first time the detection and tracking of target patterns in image and video inputs at high-speed rates with networks of multiple artificial spiking optical neurons. Using photonic systems of in-parallel spiking Vertical Cavity Surface Emitting Lasers (VCSELs), we demonstrate the implementation of multiple convolutional kernel operators which, in combination with optical spike signalling, enable the detection and tracking of target features in images/video feeds at an ultrafast photonic operation speed of 1 ns per pixel. Alongside a single layer optical Spiking Neural Network (SNN) demonstration, a multi-layer network of photonic (GHz-rate) spike-firing neurons is reported where the photonic system successfully tracks a large complex feature (Handwritten Digit 3). The consecutive photonic layers perform spike-enabled image reduction and convolution operations, and interact with a software-implemented SNN, that learns the feature patterns that best identify the target to provide a high detection efficiency even in the presence of a distractor feature. This work therefore highlights the effectiveness of combining neuromorphic photonic hardware and software SNNs, for efficient learning and ultrafast operation, thanks to the use of spiking light signals, towards tackling complex AI and computer vision problems.

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Section: Introductionmentioning

confidence: 99%

VCSEL-based photonic spiking neural networks for ultrafast detection and tracking

Robertson,

Kirkland,

Di Caterina

et al. 2024

Neuromorph. Comput. Eng.

Self Cite

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Programmable Optical Synaptic Linking of Neuromorphic Photonic-Electronic RTD Spiking Circuits

Hejda,

Zhang,

Al-Taai

et al. 2024

ACS Photonics

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Interconnectivity between functional building blocks (such as neurons and synapses) represents a fundamental functionality for realizing neuromorphic systems. However, in the domain of neuromorphic photonics, synaptic interlinking and cascadability of spiking optical artificial neurons remains challenging and mostly unexplored in experiments. In this work, we report an optical synaptic link between optoelectronic spiking artificial neurons based upon resonant tunneling diodes (RTDs) that allows for cascadable spike propagation. First, deterministic spiking is triggered using multimodal (electrical and optical) inputs in RTD-based spiking artificial neurons, which are optoelectronic (OE) circuits incorporating either micron-scale RTDs or photosensitive nanopillar-based RTDs. Second, feedforward linking with dynamical weighting of optical spiking signals between pre- and postsynaptic RTD artificial neurons is demonstrated, including cascaded spike activation. By dynamically weighting the amplitude of optical spikes, it is shown how the cascaded spike activation probability in the postsynaptic RTD node directly follows the amplitude of the weighted optical spikes. This work therefore provides the first experimental demonstration of programmable synaptic optical link and spike cascading between multiple fast and efficient RTD OE spiking artificial neurons, therefore providing a key functionality for photonic-electronic spiking neural networks and light-enabled neuromorphic hardware.

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Photonic-electronic spiking neuron with multi-modal and multi-wavelength excitatory and inhibitory operation for high-speed neuromorphic sensing and computing

Zhang,

Hejda,

Al-Taai

et al. 2024

Neuromorph. Comput. Eng.

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We report a multi-modal spiking neuron that allows optical and electronic input and control, and wavelength-multiplexing operation, for use in novel high-speed neuromorphic sensing and computing functionalities. The photonic-electronic neuron is built with a micro-scale, nanostructure resonant tunnelling diode (RTD) with photodetection (PD) capability. Leveraging the advantageous intrinsic properties of this RTD PD- system, namely highly nonlinear characteristics, photo-sensitivity, light-induced I-V curve shift, and the ability to deliver excitable responses under electrical and optical inputs, we successfully achieve flexible neuromorphic spike activation and inhibition regimes through photonic-electrical control. We also demonstrate the ability of this RTD-PD spiking sensing-processing neuron to operate under the simultaneous arrival of multiple wavelength-multiplexed optical signals, due to its large photodetection spectral window (covering the 1310 and 1550 nm telecom wavelength bands). Our results highlight the potential of RTD photonic-electronic neurons to reproduce multiple key excitatory and inhibitory spiking regimes, at high speed (ns-rate spiking responses, with faster sub-ns regimes theoretically predicted) and low energy (requiring only ~10 mV and ~150 µW, electrical and optical input amplitudes, respectively), similar in nature to those commonly found in the biological neurons of the visual system and the brain. This work offers a highly promising approach for the realisation of high-speed, energy-efficient photonic-electronic spiking neurons and spiking neural networks, enabling multi-modal and multi-wavelength operation for sensing and information processing tasks, whilst also yielding enhanced system capacity, performance and parallelism. This work therefore paves the way for innovative high-speed, photonic-electronic, and spike-based neuromorphic sensing and computing systems and artificial intelligence hardware.

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Tunable presynaptic weighting in optoelectronic spiking neurons built with laser-coupled resonant tunneling diodes

Cited by 6 publications

References 38 publications

VCSEL-based photonic spiking neural networks for ultrafast detection and tracking

VCSEL-based photonic spiking neural networks for ultrafast detection and tracking

Programmable Optical Synaptic Linking of Neuromorphic Photonic-Electronic RTD Spiking Circuits

Photonic-electronic spiking neuron with multi-modal and multi-wavelength excitatory and inhibitory operation for high-speed neuromorphic sensing and computing

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