Kerr microcombs based on soliton crystals for high-speed, scalable
optical neural networks
Optical artificial neural networks (ONNs) have significant potential for
ultra-high computing speed and energy efficiency. We report a new
approach to ONNs based on integrated Kerr micro-combs that is
programmable, highly scalable and capable of reaching ultra-high speeds,
demonstrating the building block of the ONN — a single neuron
perceptron — by mapping synapses onto 49 wavelengths to achieve a
single-unit throughput of 11.9 Giga-OPS at 8 bits per OP, or 95.2 Gbps.
We test the perceptron on handwritten-digit recognition and cancer-cell
detection — achieving over 90% and 85% accuracy, respectively. By
scaling the perceptron to a deep learning network using off-the-shelf
telecom technology we can achieve high throughput operation for matrix
multiplication for real-time massive data processing.