This work provides a first report of ultrafast and compact photonic-electronic neuromorphic temporal leaky integrate-and-fire neuronal circuits built with Resonant Tunnelling Diodes (RTDs). We demonstrate experimentally that multiple fast ( 100-200 ps) optical input pulses, arriving within a short (sub-ns long) temporal window, control the triggering of excitable responses in two different photonic-electronic RTD circuit architectures. These architectures are an electronic RTD coupled externally to a photodetector (referred to as a PD-RTD), and an integrated opto-electronic RTD device with inherent photodetection capability at infrared telecom wavelengths (referred to as an Optical RTD-PD). For both RTD systems, we reveal that the high-speed optically-triggered integrate-and-fire spiking operation can be precisely controlled by acting on the voltage bias applied to the RTD devices, or via the intensity of incoming optical pulses. Finally, we demonstrate the application of the leaky integrate-and-fire behaviour to a pattern recognition task at high-speed, with the systems triggering fast ns-long electrical spikes in response to optical inputs of weighted 4-bit digital headers.

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 microW, 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. This work therefore paves the way for innovative high-speed, photonic-electronic, and spike-based neuromorphic sensing and computing systems and artificial intelligence hardware.

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.

In this paper, we present characterization of a compact flat microwave lens operating between 6 GHz and 14 GHz using a near field scanning system. An X-band horn antenna and open-end rectangular waveguide were used as an illumination source and probe, respectively. |S21| is measured as the probe antenna moves on a plane orthogonal to the optical axis vertically and horizontally. The lens is made of a metasurface layer that is sandwiched by two layers of cross-oriented gratings. The overall dimension of the lens is 10 cm in diameter and 0.57 cm in thickness. The measurement results show that the lens's focal length is 8 cm, and the beamwidth (full width at half maximum (FWHM)) is 3.5 cm, A transmission efficiency of over 90% and a cross-polarization gain of 25 dB were achieved over the entire bandwidth. The measurement results at room temperature are in good agreement with numerical simulations. The proposed lens will be used in a cryogenic environment e.g. dilution refrigerators for quantum computing systems. More results at cryogenic temperature e.g, below 30 K will be shown at the conference.

This work reports a nanostructure resonant tunnelling diode-photodetector (RTD-PD) device and demonstrates its operation as a controllable, optically-triggered excitable spike generator. The top contact layer of the device is designed with a nanopillar structure 500 nm in diameter) to restrain the injection current, yielding therefore lower energy operation for spike generation. We demonstrate experimentally the deterministic optical triggering of controllable and repeatable neuron-like spike patterns in the nanostructure RTD-PDs. Moreover, we show the device's ability to deliver spiking responses when biased in both regions adjacent to the negative differential conductance (NDC) region, the so-called 'peak' and 'valley' points of the current-voltage (I-V) characteristic. This work also demonstrates experimentally key neuron-like dynamical features in the nanostructure RTD-PD, such as a well-defined threshold (in input optical intensity) for spike firing, as well as the presence of spike firing refractory time. The optoelectronic and chip-scale character of the proposed system together with the deterministic, repeatable and well controllable nature of the optically-elicited spiking responses render this nanostructure RTD-PD element as a highly promising solution for high-speed, energy-efficient optoelectronic artificial spiking neurons for novel light-enabled neuromorphic computing hardware.

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.

In this work, we study multiple epitaxial layer structures incorporating a resonant tunneling diode photodetector utilizing the In0.53Ga0.47As/InP material system for operation at the near-infrared region of 1.55 and 1.31 micrometers. We study the photodetection speed of response for these devices and the physical limitations affecting their bandwidth. We show that resonant tunneling diode-based photodetectors have bandwidth limitations due to the charge accumulation near the barriers and report on an operating bandwidth reaching up to 1.75 GHz in particular structures, which is the highest number reported for such detectors to the authors' best knowledge.

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.

In this paper, we present a low-cost, high-gain lens antenna operating at X-band that consists of a metasurface-based flat lens and a standard patch antenna. The flat lens comprises three layers, including two outer layers of cross-polarized gratings and a meta-atom-based middle layer. The feed antenna is a standard patch antenna operating in the near field. By designing the meta-atoms appropriately, the lens can achieve a relative phase shift range from 0° to 360°, which is crucial for directing the feed antenna's spherical wavefronts towards the lens. The lens area measures 160 mm × 160 mm, with a separation of 3 mm between the layers. The patch antenna is situated 100 mm away from the lens. Simulation and experimental results demonstrate that the focal length is 50 mm, the beam diameter at the focal point is 10 mm, and the gain is 13.5 dB at 10 GHz. These compact, low-cost lens antennas have the potential to be utilized in environments where space is limited.

We report an optoelectronic neuromorphic synaptic link built with high-speed nanoscale resonant tunnelling diode-photodetectors (RTD-PDs), which reproduces temporal-coded spike generation and transmissions in biological neurons and synapses. The artificial optoelectronic neuron is composed of a nanoscale RTD-PD built with a double barrier quantum well (DBQW) structure for nonlinearity and excitability, and an optical-sensitive layer to enable light-triggered spike firing. Due to the resonant tunnelling effect, RTDs exhibit a typical N-shaped current-voltage (I-V) curve with a nonlinear negative differential conductance (NDC) region bringing about a number of distinct functionalities, such as high-speed self-oscillations and controllable excitability [1]. For optical excitability, the nanoscale RTD-PD consist of an InAlGaAs light-sensitive spacer layer to receive infrared optical stimuli [2]. Due to the photodetection and carrier accumulation in the device, the optical stimuli can shift the I-V curve and trigger an optically-induced spiking event (provided the RTD-PD is biased in the vicinity of its NDC region) [1]. We have demonstrated that RTD-PDs are capable of implementing neuromorphic excitability with well-defined thresholding and refractoriness [3–5]. We build an optoelectronic synaptic link based on two nanoscale RTD-PD (pre-synaptic and post-synaptic) neurons to reproduce the generation, weighting and propagation of spiking signals. Fig.1 illustrates the schematic diagram of the experimental optical synaptic link. Optical pulses are injected into the pre-synaptic nanoscale RTD-PD neuron which in response elicits electrical spikes in an all-or-nothing manner. Information is coded in sparse temporal intervals. The electrical spikes are converted into the optical domain via direct modulation of a 1550nm vertical cavity surface emitting laser (VCSEL) and then the amplitude (weight) of the optical spikes is tuned by bespoke intensity modulation waveforms (created with an arbitrary waveform generator, AWG) via a Mach-Zehnder modulator (MZM). Subsequently, the weighted optical spikes are injected into the post-synaptic nano RTD-PD neuron. Due to the thresholding spike-firing property of RTDs, only weighted spikes with sufficient intensity can be regenerated by the post-synaptic neuron. This first report of nanoscale RTD-PD neurons and optoelectronic synaptic link demonstrates a promising solution for the core component of optical neuromorphic networks for high-speed, energy-efficient AI computation.

Spike-based neuromorphic devices promise to alleviate the energy greed of the artificial intelligence hardware by using spiking neural networks (SNNs), which employ neuron like units to process information through the timing of the spikes. These neuron-like devices only consume energy when active. Recent works have shown that resonant tunnelling diodes (RTDs) incorporating optoelectronic functionalities such as photodetection and light emission can play a major role on photonic SNNs. RTDs are devices that display an N-shaped current-voltage characteristics capable of providing negative differential conductance (NDC) over a range of the operating voltages. Specifically, RTD photodetectors (RTD-PDs) show promise due to their unique mixture of the structural simplicity while simultaneously providing highly complex non-linear behavior. The goal of this work is to present a systematic study of the how the thickness of the RTD-PD light absorption layers (100, 250, 500 nm) and the device size impacts on the performance of InGaAs RTD-PDs, namely on its responsivity and time response when operating in the third (1550 nm) optical transmission window. Our focus is on the overall characterization of the device optoelectronic response including the impact of the light absorption on the device static current-voltage characteristic, the responsivity and the photodetection time response. For the static characterization, the devices I-V curves were measured under dark conditions and under illumination, giving insights on the light induced I-V tunability effect. The RTD-PD responsivity was compared to the response of a commercial photodetector. The characterization of the temporal response included its capacity to generate optical induced neuronal-like electrical spike, that is, when working as an opto-to-electrical spike converter. The experimental data obtained at each characterization phase is being used for the evaluation and refinement of a behavioral model for RTD-PD devices under construction.

We report a spiking artificial optoelectronic neuron based on a resonant tunnelling diode (RTD) coupled to a photodetector (receiver) and a vertical cavity surface emitting laser (VCSEL, transmitter). We experimentally realize this O/E/O system, and demonstrate optical spiking with a well-defined, adjustable excitability threshold.

This paper describes the systematic approach to develop low power consumption excitable neuromorphic spike generators using nano-sized resonant tunnelling diode (RTD), including fabrication, characterization and device modelling and spike circuit simulation. The fabrication process of nano sized RTDs has been developed and devices exhibit peak currents of up to 100 μA. The energy efficiency of the RTD spike generator can reach as low as 0.09 fJ per spike. An accurate small signal model of nano RTD has also been developed and is described. This nano-RTD technology could underpin the development of energy efficient neuromorphic computing in the very near future.

Excitable optoelectronic devices represent one of the key building blocks for implementation of artificial spiking neurons in neuromorphic (brain-inspired) photonic systems. This work introduces and experimentally investigates an opto-electro-optical (O/E/O) artificial neuron built with a resonant tunnelling diode (RTD) coupled to a photodetector as a receiver and a vertical cavity surface emitting laser as a transmitter. We demonstrate a well-defined excitability threshold, above which the neuron produces optical spiking responses with characteristic neural-like refractory period. We utilise its fan-in capability to perform in-device coincidence detection (logical AND) and exclusive logical OR (XOR) tasks. These results provide first experimental validation of deterministic triggering and tasks in an RTD-based spiking optoelectronic neuron with both input and output optical (I/O) terminals. Furthermore, we also investigate in simulation the prospects of the proposed system for nanophotonic implementation in a monolithic design combining a nanoscale RTD element and a nanolaser; therefore demonstrating the potential of integrated RTD-based excitable nodes for low footprint, high-speed optoelectronic spiking neurons in future neuromorphic photonic hardware.

We present an electroabsorption modulated laser based on an identical epitaxial scheme, side-wall grating, on- chip microwave probe interface, and a new low-permittivity planarization method. The modulation speed is significantly increased by reducing the electrode capacitance by planarizing with a 5- $\mu \text{m}$ -thick HSQ layer. Furthermore, implementing the electrode with a direct ground-signal-ground probe interface provides a straightforward interconnection that obviates the need for an external circuit and bonding wires. The device operates at 1565 nm wavelength with stable single-mode lasing, no mode-hopping, and a side mode suppression ratio above 35 dB. An extinction ratio of 19.5 dB was recorded at the maximum modulator bias of −4 V. The electrical to optical power response of the modulated signal at–3-dBo demonstrated a 19 GHz bandwidth at an extinction ratio of 7 dB, which supports error-free data transmission up to 27 Gbit/s.

Electroabsorption modulated lasers (EMLs), comprising a distributed feedback (DFB) laser and electroabsorption modulator (EAM) monolithically integrated into the same chip, are attractive because of their compact size, low fabrication cost, and their capability to offer a high modulation speed with low drive voltage, low chirp, and high extinction ratio [1] , [2] . The modulation speed of the EML is limited by the RC constant of the EAM electrode, which is conventionally configured with either a lumped or travelling-wave (TW) electrode. The latter approach overcomes the RC limit by including the EAM in a microwave circuit matched to the source [3] . However, due to restrictions imposed by size and materials, TW EAMs have to date been integrated externally using a specifically designed material structure or monolithically using selective area growth.

In this paper, we report on the fabrication of micrometre and nanometre-sized resonant tunnelling diode (RTD) devices which may be used as excitable neuromorphic spike generators. The fabrication processes using photolithography were applied for micro-sized RTDs, while for nano-RTDs the fabrication was optimised to achieve accurate nano-sized mesas through a multi-exposure step based on e-beam lithography. The results show a large decrease in the peak currents from 41 mA to 27 mu A for micro- and nano-RTDs, respectively, peak and valley voltages of around 0.6 V and 0.8 V and a peak to valley current ratio of around 2.4. For the smallest fabricated RTD of 300 nm diameter, the expected energy consumption per oscillation cycle (if used in an oscillator) will be 1.55 fJ. DC characterisation of the devices show that the nano-RTDs are stable and have smooth current voltage (I-V) characteristics compared with micro-RTDs. The nano-RTD technology could be employed to realise highly sensitive photodetectors that can be operated as spike generators and so they could underpin the development of energy efficient neuromorphic computing.

Low-cost solutions for delivering high communication bandwidths in both short- and long-haul systems are urgently required. Electroabsorption modulated lasers (EMLs), comprising a distributed feedback (DFB) laser and electroabsorption modulator (EAM), can address this. They are compact and offer a high modulation speed with low drive voltage, low chirp, and high extinction ratio [1] . To the best of our knowledge, the EAM in EMLs based on identical epitaxial layer technology has so far been configured with a lumped electrode. This can take the form of either a circular-pad, a rectangular-pad or the centre electrode of a ground-signal-ground (GSG) configuration. All result in a high capacitance, which in turn limits the modulation speed. Although the GSG choice has a similar configuration to that of a coplanar waveguide (CPW), it still behaves as a lumped electrode because of the lack of impedance matching. A planarized film of low- k material can be used to reduce the capacitance, however standard methods such as Benzocyclobutene or polyimide-based planarization are very difficult to implement as they are incompatible with many photonic integration steps [2] .

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.

In this paper, we report on a simple test structure which can be used to accurately extract the specific contact resistivity rho(c) associated with metal-n++ InGaAs-based low-resistance Ohmic contacts through the transfer length method (TLM). The structure was designed to avoid common measurement artifacts that typically affect standard layouts. Moreover, microfabrication was optimised to achieve an accurate short minimum gap spacing of 1 mu m through a dual-exposure step based on e-beam lithography, which is required for a reliable rho(c) estimation. Ohmic contacts based on a Ti/Pd/Au metal stack were fabricated and characterised using the proposed structure, resulting in an extracted rho(c) similar or equal to 1.37x10(-7) Omega cm(2) = 13.7 Omega mu m(2). This work will assist in increasing the quality of Ohmic contacts in high-power InGaAs/AlAs double-barrier resonant tunnelling diodes (RTDs), and so help to overcome one of the bottlenecks to the output power capability of RTD-based oscillators at terahertz frequencies.