Collective and synchronous dynamics of photonic spiking neurons

TL;DR

This paper demonstrates that photonic spiking neurons, implemented with nonlinear optical oscillators, can be controlled to produce bio-realistic spiking patterns and exhibit collective dynamics useful for solving complex optimization problems.

Contribution

It introduces a method to control photonic spiking neurons and shows how their collective dynamics can be harnessed for computational tasks.

Findings

Photonic neurons can generate two modes of spiking dynamics controlled by pump amplitude.

Coupled photonic neurons exhibit synchronization-dependent effective changes in spiking behavior.

Collective dynamics enable efficient heuristics for NP-hard combinatorial optimization problems.

Abstract

Nonlinear dynamics of spiking neural networks has recently attracted much interest as an approach to understand possible information processing in the brain and apply it to artificial intelligence. Since information can be processed by collective spiking dynamics of neurons, the fine control of spiking dynamics is desirable for neuromorphic devices. Here we show that photonic spiking neurons implemented with paired nonlinear optical oscillators can be controlled to generate two modes of bio-realistic spiking dynamics by changing the optical pump amplitude. When they are coupled in a network, we found that the interaction between the photonic neurons induces an effective change in the pump amplitude depending on the order parameter that characterizes synchronization. The experimental results show that the effective change causes spontaneous modification of the spiking modes and firing rates of clustered neurons, and such collective dynamics can be utilized to realize efficient heuristics for solving NP-hard combinatorial optimization problems.