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Photonic perceptron at Giga-OP/s speeds with Kerr microcombs for scalable optical neural networks
  • David J. Moss
David J. Moss

Corresponding Author:[email protected]

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Optical artificial neural networks (ONNs) have significant potential for ultra-high computing speed and energy efficiency. We report a novel approach to ONNs that uses integrated Kerr optical micro-combs. This approach is programmable and scalable and is capable of reaching ultra-high speeds. We demonstrate the basic building block ONNs-a single neuron perceptron-by mapping synapses onto 49 wavelengths to achieve an operating speed of 11.9 x 10 9 operations per second, or Giga-OPS, at 8 bits per operation, which equates to 95.2 gigabits/s (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.