Optical next generation reservoir computing.

ABSTRACT: Artificial neural networks with internal dynamics exhibit remarkable capability in processing information. Reservoir computing (RC) is a canonical example that features rich computing expressivity and compatibility with physical implementations for enhanced efficiency. Recently, a new RC paradigm known as next generation reservoir computing (NGRC) further improves expressivity but compromises its physical openness, posing challenges for realizations in physical systems. Here we demonstrate optical NGRC with computations performed by light scattering through disordered media. In contrast to conventional optical RC implementations, we directly and solely drive our optical reservoir with time-delayed inputs. Much like digital NGRC that relies on polynomial features of delayed inputs, our opti

SUBMITTER: Wang H 

PROVIDER: S-EPMC12280216 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature