Coherent multi-frequency photonic activation function

The advent of photonic neural networks posed a challenge of designing an activation function that would unlock the full potential of photonics (low-latency, energy-efficiency, WDM) for machine learning applications. In this work we demonstrate a coherent, multi-frequency photonic nonlinear activation function based on stimulated Brillouin scattering . These properties not only make it compatible with existing MZI mesh-based phase-reliant optical matrix multiplication schemes, but also facilitate resource-efficient frequency-basis information encoding. Our design features all-optical activation function shape tuning and is capable of providing net gain, compensating for insertion losses.