Magnetization reversal by multiple optical pulses for photonic spiking neuron with the leaky integrate and fire model

Abstract

Photonic accelerators are anticipated to be the next generation of hardware processors, replacing traditional electronic accelerators. In current photonic accelerators based on artificial neural networks, photonic integrated circuits are incorporated with electronic integrated circuits to leverage their strengths: photonic circuits are used to perform linear calculations, while electronic circuits are used to perform nonlinear calculations. However, this architecture requires optoelectric conversion at each layer and is unable to leverage the superiority of light. We propose a novel photonic spiking neuron with a magneto-optical synapse and an all-optical spiking neural network. This study experimentally demonstrates that the magnetization reversal of CoFeB, which occurs during thermal accumulation owing to multiple optical pulses, is similar to the behavior of the leaky integrated and fire model of spiking neurons.