Reservoir computing based on solitary-like waves dynamics of film flows: a proof of concept
This provides a proof-of-concept for using solitary-like waves in reservoir computing, which could benefit researchers in neuromorphic computing and analog physical systems, though it appears incremental as it builds on prior theoretical work.
The authors tackled the problem of implementing reservoir computing using physical systems by proposing and experimentally validating a novel system based on solitary-like waves on a liquid film, demonstrating its ability to forecast chaotic time series and pass benchmark tests like memory capacity and Mackey-Glass model.
Several theoretical works have shown that solitons -- waves that self-maintain constant shape and velocity as they propagate -- can be used as a physical computational reservoir, a concept where machine learning algorithms designed for digital computers are replaced by analog physical systems that exhibit nonlinear dynamical behaviour. Here we propose and experimentally validate a novel reservoir computing (RC) system that for the first time employs solitary-like (SL) waves propagating on the surface of a liquid film flowing over an inclined surface. We demonstrate the ability of the SL wave RC system (SLRC) to forecast chaotic time series and to successfully pass essential benchmark tests, including a memory capacity test and a Mackey-Glass model test.