Optical computing with multimode fiber nonlinearities
Uğur Teğin, Mustafa Yildirim, İlker Oğuz, Christophe Moser, Demetri Psaltis · 2021
A novel optical computing framework is presented by harnessing spatiotemporal nonlinear effects of multimode fibers for machine learning. With linear and nonlinear interactions of spatial fiber modes, a powerful computation engine is experimentally realized. We demonstrated excellent performance with the present optical scheme for various classification tasks. We demonstrated that spatiotemporal fiber nonlinearities perform as well as digital neural network structures for challenging computational tasks. With better energy efficiency and easy scalability, our method presents a novel path toward powerful optical computation.