Nanophotonic spiking neural networks (SNNs) based on neuron-like excitable subwavelength (submicrometre) devices are of key importance for realizing brain-inspired, power-efficient artificial intelligence (AI) systems with high degree of parallelism and energy efficiency. Despite significant advances in neuromorphic photonics, compact and efficient nanophotonic elements for spiking signal emission and detection, as required for spike-based computation, remain largely unexplored. In this invited perspective, we outline the main challenges, early achievements, and opportunities toward a key-enabling photonic neuro-architecture using III–V/Si integrated spiking nodes based on nanoscale resonant tunnelling diodes (nanoRTDs) with folded negative differential resistance. We utilize nanoRTDs as nonlinear artificial neurons capable of spiking at high-speeds. We discuss the prospects for monolithic integration of nanoRTDs with nanoscale light-emitting diodes and nanolaser diodes, and nanophotodetectors to realize neuron emitter and receiver spiking nodes, respectively. Such layout would have a small footprint, fast operation, and low power consumption, all key requirements for efficient nano-optoelectronic spiking operation. We discuss how silicon photonics interconnects, integrated photorefractive interconnects, and 3D waveguide polymeric interconnections can be used for interconnecting the emitter-receiver spiking photonic neural nodes. Finally, using numerical simulations of artificial neuron models, we present spike-based spatio-temporal learning methods for applications in relevant AI-based functional tasks, such as image pattern recognition, edge detection, and SNNs for inference and learning. Future developments in neuromorphic spiking photonic nanocircuits, as outlined here, will significantly boost the processing and transmission capabilities of next-generation nanophotonic spike-based neuromorphic architectures for energy-efficient AI applications. This perspective paper is a result of the European Union funded research project ChipAI in the frame of the Horizon 2020 Future and Emerging Technologies Open programme.

We report on the direct intensity modulation characteristics of a high-speed resonant tunneling diode-photodetector (RTD-PD) with an oscillation frequency of 79 GHz. This work demonstrates both electrical and optical modulation and shows that RTD-PD oscillators can be utilized as versatile optoelectronic/radio interfaces. This is the first demonstration of optical modulation of an RF carrier using integrated RTD-PD oscillators at microwave frequencies.

We report on the characterization and analysis of a GaN-based distributed feedback laser diode (DFB-LD) with 3 ^rd -order laterally etched sidewall gratings centered at a wavelength of 420 nm. We also compare the device parameters with two commonly used Fabry-Perot (FP) devices operating at 450 nm and 520 nm. Intrinsic properties of the devices were extracted, including damping factor, carrier and photon lifetimes, modulation efficiency, differential gain, and parasitic capacitance. These parameters showed that the DFB exhibits a lower damping rate and parasitic capacitance while demonstrating a higher modulation efficiency, indicating that the DFB shows good potential for communications applications. Additionally, spectral linewidth of a GaN DFB is reported. To the authors' knowledge, this is the first demonstration of parameter extraction and spectral linewidth measurement for GaN-based DFB-LDs.

We investigate the dynamic behaviour of resonant tunneling diode-photodetectors (RTD-PDs) in which the excitability can be activated by either electrical noise or optical signals. In both cases, we find the characteristics of the stochastic spiking behavior are not only dependent on the biasing positions but also controlled by the intensity of the input perturbations. Additionally, we explore the ability of RTD-PDs to perform optical signal transmission and neuromorphic spike generation simultaneously. These versatile functions indicate the possibility of making use of RTD-PDs for innovative applications, such as optoelectronic neuromorphic circuits for spike-encoded signaling and data processing.

Optoelectronic artificial spiking neurons are regarded as promising core elements for novel photonic neuromorphic computing hardware. In this work, we investigate a modular optoelectronic spiking neuron built with an excitable resonant tunneling diode (RTD) coupled to a photodetector and a vertical-cavity surface-emitting laser (VCSEL). This work provides the first experimental demonstration of amplitude control of the fired optical spikes in the electrical-to-optical part of the artificial neuron, therefore introducing a simple way of weighting of the presynaptic spikes. This is achieved by tuning the VCSEL bias current, hence providing a straightforward, high-speed, hardware-friendly option for the weighting of optical spiking signals. Furthermore, we validate the feasibility of this layout using a simulation of a monolithically integrated, RTD-based nanoscale optoelectronic spiking neuron model, which confirms the system’s capability to deliver weighted optical spiking signals at GHz firing rates. These results demonstrate a high degree of flexibility of RTD-based artificial optoelectronic spiking neurons and highlight their potential towards compact, high-speed photonic spiking neural networks and light-enabled neuromorphic hardware.

This paper represents the experimental results of optical modulation characteristics of a resonant tunneling diode-photodiode (RTD-PD) device and novel microwave oscillators employing such RTD-PD. Different from a pure electronic RTD oscillator, the RTD-PDs in this work contain photoconductive layers which make it able to operate in optical conditions. A beam of intensity modulated light with a wavelength of 1310 nm was sent to the free running oscillator via an optical fiber whilst the RTD device was biased in the oscillation condition, and the corresponding electrical data can be extracted from the output port of the oscillator. A square wave signal at data rates up to 10 Gbit/s, and a pseudo random binary sequence (PRBS) signal with a data rate of 100 Mbit/s were preliminarily implemented for modulation.