Neuromorphic Light-Responsive Organic Matter for in Materia Reservoir Computing.

Abstract

Materials able to sense and respond to external stimuli by adapting their internal state to process and store information, represent promising candidates for implementing neuromorphic functionalities and brain-inspired computing paradigms. In this context, neuromorphic systems based on light-responsive materials enable the use of light as information carrier, allowing to emulate basic functions of the human retina. In this work it is demonstrated that optically-induced molecular dynamics in azopolymers can be exploited for neuromorphic-type of data processing in the analog domain and for computing at the matter level (i.e., in materia). Besides showing that azopolymers can be exploited for data storage, it is demonstrated that the adaptiveness of these materials enables the implementation of synaptic functionalities including short-term memory, long-term memory, and visual memory. Results show that azopolymers allow event detection and motion perception, enabling physical implementation of information processing schemes requiring real-time analysis of spatio-temporal inputs. Furthermore, it is shown that light-induced dynamics can be exploited for the in materia implementation of the unconventional computing paradigm denoted as reservoir computing. This work underscores the potential of azopolymers as promising materials for developing adaptive, intelligent photo-responsive systems that mimic some of the complex processing abilities of biological systems.