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The rapid growth of brain-inspired computing coupled with the inefficienciesin the CMOS implementations of neuromrphic systems has led to intenseexploration of efficient hardware implementations of the functional units ofthe brain, namely, neurons and synapses. However, efforts have largely beeninvested in implementations in the electrical domain with potential limitationsof switching speed, packing density of large integrated systems andinterconnect losses. As an alternative, neuromorphic engineering in thephotonic domain has recently gained attention. In this work, we demonstrate apurely photonic operation of an Integrate-and-Fire Spiking neuron, based on thephase change dynamics of Ge$_2$Sb$_2$Te$_5$ (GST) embedded on top of amicroring resonator, which alleviates the energy constraints of PCMs inelectrical domain. We also show that such a neuron can be potentiallyintegrated with on-chip synapses into an all-Photonic Spiking Neural networkinferencing framework which promises to be ultrafast and can potentially offera large operating bandwidth.

Toward Fast Neural Computing using All-Photonic Phase Change Spiking Neurons