Photonic reservoir computing approaches to nanoscale computation
Andrew Katumba, Peter Bienstman, Joni Dambre · 2015
This material is based on work in progress. Reservoir computing, originally a training technique for recurrent neural networks, exploits the computation that naturally occurs in physical dynamical systems. Reservoir computing with integrated nanophotonics potentially offers low-power, high-bandwidth signal processing for telecommunication applications. We present our recent results for optical signal regeneration. Our simulations show that a small-scale low-power integrated photonic reservoir achieves state-of-the-art performance for regenerating optical signals that have traversed fiber lengths of up to 200 km.