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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.

Event-activated biological-inspired subwavelength (sub-λ) photonic neural networks are of key importance for future energy-efficient and high-bandwidth artificial intelligence systems. However, a miniaturized light-emitting nanosource for spike-based operation of interest for neuromorphic optical computing is still lacking. In this work, we propose and theoretically analyze a novel nanoscale nanophotonic neuron circuit. It is formed by a quantum resonant tunneling (QRT) nanostructure monolithic integrated into a sub-λ metal-cavity nanolight-emitting diode (nanoLED). The resulting optical nanosource displays a negative differential conductance which controls the all-or-nothing optical spiking response of the nanoLED. Here we demonstrate efficient activation of the spiking response via high-speed nonlinear electrical modulation of the nanoLED. A model that combines the dynamical equations of the circuit which considers the nonlinear voltage-controlled current characteristic, and rate equations that takes into account the Purcell enhancement of the spontaneous emission, is used to provide a theoretical framework to investigate the optical spiking dynamic properties of the neuromorphic nanoLED. We show inhibitory- and excitatory-like optical spikes at multi-gigahertz speeds can be achieved upon receiving exceptionally low (sub-10 mV) synaptic-like electrical activation signals, lower than biological voltages of 100 mV, and with remarkably low energy consumption, in the range of 10–100 fJ per emitted spike. Importantly, the energy per spike is roughly constant and almost independent of the incoming modulating frequency signal, which is markedly different from conventional current modulation schemes. This method of spike generation in neuromorphic nanoLED devices paves the way for sub-λ incoherent neural elements for fast and efficient asynchronous neural computation in photonic spiking neural networks.

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. [ABSTRACT FROM AUTHOR]

We investigate the generation of high-speed spiking and bursting signals in a long time-delayed broadband optoelectronic oscillator (OEO). The OEO is configured in a delayed feedback loop employing a long optical fiber delay line and other elements including a tunable laser, a phase modulator (PM) and a linearly chirped fiber Bragg grating (LCFBG), a photodetector, and an electrical amplifier. The joint operation of the PM and the LCFBG forms an ultrawideband microwave photonic filter (MFP). Taking advantage of the multiple time scales arising from the MPF and the long optical fiber delay line, we are able to generate subnanosecond neuron-like spiking and bursting signals that emulate the response found to be the primary mode of electrical firing in biological neurons. Since our OEO can operate at a much higher speed and can be controlled using both time-delayed feedback employing low-loss optical fiber and electrical/optical injection locking techniques, it has interest in emerging photonics applications such as neuromorphic information processing and reservoir computing tasks. [ABSTRACT FROM AUTHOR]

We report on photo-detectors consisting of an optical waveguide that incorporates a resonant tunneling diode (RTD). Operating at wavelengths around 1.55 µm in the optical communications C band we achieve maximum sensitivities of around 0.29 A/W which is dependent on the bias voltage. This is due to the nature of RTD nonlinear current-voltage characteristic that has a negative differential resistance (NDR) region. The resonant tunneling diode photo-detector (RTD-PD) can be operated in either non-oscillating or oscillating regimes depending on the bias voltage quiescent point. The oscillating regime is apparent when the RTD-PD is biased in the NDR region giving rise to electrical gain and microwave self-sustained oscillations Taking advantage of the RTD's NDR distinctive characteristics, we demonstrate efficient detection of gigahertz (GHz) modulated optical carriers and optical control of a RTD GHz oscillator. RTD-PD based devices can have applications in generation and optical control of GHz low-phase noise oscillators, clock recovery systems, and fiber optic enabled radio frequency communication systems. [ABSTRACT FROM AUTHOR]

With the recent exponential growth of applications using artificial intelligence (AI), the development of efficient and ultrafast brain-like (neuromorphic) systems is crucial for future information and communication technologies. While the implementation of AI systems using computer algorithms of neural networks is emerging rapidly, scientists are just taking the very first steps in the development of the hardware elements of an artificial brain, specifically neuromorphic microchips. In this review article, we present the current state of the art of neuromorphic photonic circuits based on solid-state optoelectronic oscillators formed by nanoscale double barrier quantum well resonant tunneling diodes. We address, both experimentally and theoretically, the key dynamic properties of recently developed artificial solid-state neuron microchips with delayed perturbations and describe their role in the study of neural activity and regenerative memory. This review covers our recent research work on excitable and delay dynamic characteristics of both single and autaptic (delayed) artificial neurons including all-or-none response, spike-based data encoding, storage, signal regeneration and signal healing. Furthermore, the neural responses of these neuromorphic microchips display all the signatures of extended spatio-temporal localized structures (LSs) of light, which are reviewed here in detail. By taking advantage of the dissipative nature of LSs, we demonstrate potential applications in optical data reconfiguration and clock and timing at high-speeds and with short transients. The results reviewed in this article are a key enabler for the development of high-performance optoelectronic devices in future high-speed brain-inspired optical memories and neuromorphic computing.

We propose and demonstrate a simple and stable low-phase noise optoelectronic oscillator (OEO) that uses a laser diode, an optical fiber delay line and a resonant tunneling diode (RTD) free-running oscillator that is monolithic integrated with a waveguide photo-detector. The RTD-OEO exhibits single-side band phase noise power below -100 dBc/Hz with more than 30 dB noise suppression at 10 kHz from the center free-running frequency for fiber loop lengths around 1.2 km. The oscillator power consumption is below 0.55 W, and can be controlled either by the injected optical power or the fiber delay line. The RTD-OEO stability is achieved without using other high-speed optical/optoelectronic components and amplification.