# Neural Echo State Network using oscillations of gas bubbles in water

arXiv: https://arxiv.org/abs/2112.11592 · HTML: https://mlsanity.com/paper/2112.11592/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 3 of its 50 references that are in the map.
- First posted on arXiv 22 Dec 2021.

## Builds on (most cited first, 3 of 3)

- [Next Generation Reservoir Computing](https://mlsanity.com/paper/2106.07688/) (2021)
- [Physical reservoir computing -- An introductory perspective](https://mlsanity.com/paper/2005.00992/) (2020)
- [Efficient implementations of echo state network cross-validation](https://mlsanity.com/paper/2006.11282/) (2020)

## Built on by (most cited first, 6 of 6)

- [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)
- [Quantum-Inspired Neural Network Model of Optical Illusions](https://mlsanity.com/paper/2312.03447/) (2023)
- [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)

In the framework of physical reservoir computing (RC), machine learning algorithms designed for digital computers are executed using analog computer-like nonlinear physical systems that can provide energy-efficient computational power for predicting time-dependent quantities that can be found using nonlinear differential equations. We suggest a bubble-based RC (BRC) system that combines the nonlinearity of an acoustic response of a cluster of oscillating gas bubbles in water with a standard Echo State Network (ESN) algorithm that is well-suited to forecast chaotic time series. We confirm the plausibility of the BRC system by numerically demonstrating its ability to forecast certain chaotic time series similarly to or even more accurately than ESN.