Simplified Coherent Synaptic Receptor for Filterless Optical Neural Networks

Neuromorphic computing is touted to be a game changer for existing and emerging data processing applications. Towards this direction, artificial neural network implementations have moved into the focus of research. Advancing neural networks to the optical domain offers several advantages, such as high data throughput at time-of-flight inference latency. The present work proposes coherent synaptic interconnects as a path towards filterless neural networks with increased routing flexibility. A coherent synaptic receptor with integrated weighing functionality is experimentally investigated and evaluated for a 1-GHz train of 130-ps wide spikes. Homodyne detection is accomplished through use of an optically injection locked local oscillator, while its phase and the responsivity of the co-integrated photodiode are exploited to realize a tunable weight upon reception of the incoming optical spikes. Moreover, the switching of the sign is shown for the detection weight, underpinning the feasibility to extend the allocation of synapses toward both, wavelength and time dimensions.