# Reservoir computing based on solitary-like waves dynamics of film flows: a proof of concept

arXiv: https://arxiv.org/abs/2303.01801 · HTML: https://mlsanity.com/paper/2303.01801/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 1 of its 11 references that are in the map.
- First posted on arXiv 3 Mar 2023.

## Builds on (most cited first, 1 of 1)

- [Efficient implementations of echo state network cross-validation](https://mlsanity.com/paper/2006.11282/) (2020)

## Built on by (most cited first, 5 of 5)

- [Analogue and Physical Reservoir Computing Using Water Waves](https://mlsanity.com/paper/2306.09095/) (2023)
- [Classical and Quantum Physical Reservoir Computing for Onboard Artificial Intelligence Systems: A Perspective](https://mlsanity.com/paper/2407.04717/) (2024)
- [Reservoir Computing Using Measurement-Controlled Quantum Dynamics](https://mlsanity.com/paper/2403.01024/) (2024)
- [Physical Reservoir Computing Enabled by Solitary Waves and Biologically-Inspired Nonlinear Transformation of Input Data](https://mlsanity.com/paper/2402.03319/) (2024)
- [Reservoir Computing with a Single Oscillating Gas Bubble: Emphasizing the Chaotic Regime](https://mlsanity.com/paper/2504.07221/) (2025)

## Abstract (arXiv)

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.