Event-activated biological-inspired subwavelength (sub-λ) optical neural networks are of paramount importance for energy-efficient and high-bandwidth artificial intelligence (AI) systems. Despite the significant advances to build active optical artificial neurons using for example phase-change materials, lasers, photodetectors, and modulators, miniaturized integrated sources and detectors suited for few-photon spike-based operation and of interest for neuromorphic optical computing are still lacking. In this invited paper we outline the main challenges, opportunities, and recent results towards the development of interconnected neuromorphic nanoscale light-emitting diodes (nanoLEDs) as key-enabling artificial spiking neuron circuits in photonic neural networks. This method of spike generation in neuromorphic nanoLEDs paves the way for sub-λ incoherent neural circuits for fast and efficient asynchronous brain-inspired computation.
III-V semiconductor nanowires allow easy hetero-integration of optoelectronic components onto silicon due to efficient strain relaxation, well-understood design approaches and scalability. However continuous room temperature lasing has proven elusive. A key challenge is performing repeatable single-wire characterization { each wire can be different due to local growth conditions present during bottom-up growth. Here, we describe an approach using large-scale population studies which exploit inherent inhomogeneity to understand the complex interplay of geometric design, crystal structure, and material quality. By correlating nanowire length with threshold for hundreds of nanowire lasers, this technique reveals core-reabsorption as the critical limiting process in multiple-quantum-well nanowire lasers. By incorporating higher band-gap nanowire core, this effect is eliminated, providing reflectivity dominated behavior.
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