Temporal Information Processing with an Integrated Laser Neuron

Spiking neural networks enable efficient information processing in real-time. Excitable lasers can exhibit ultrafast spiking dynamics, and when preceded by a photodetector in an O/E/O link, can process optical spikes at different wavelengths and thus be interconnected in large neural networks. Here, we experimentally demonstrate and numerically simulate the spiking dynamics of a laser neuron fabricated in a photonic integrated circuit. Our spiking laser neuron is shown to perform coincidence detection with nanosecond time resolution, and we observe refractory periods in the order of 0.1 ns. We propose a method to implement XOR classification using our laser neurons, and simulations of the resultant dynamics indicate robust tolerance to timing jitter.