# A New Paradigm of Reservoir Computing Exploiting Hydrodynamics

arXiv: https://arxiv.org/abs/2302.01978 · HTML: https://mlsanity.com/paper/2302.01978/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Feb 2023.

## 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)

Nonlinear waves have played a historical role in laying the foundations of the science of complexity. Recently, they have also allowed the development of a new reservoir computing paradigm: neuromorphic computing by waves. In these systems, the information transmission acts as the excitation of wave dynamics, whose evolution processes the information to perform complex tasks at low energy consumption. To enable nonlinear hydrodynamic waves to do computing, we designed the Aqua-Photonic-Advantaged Computing Machine by Artificial Neural Networks (Aqua-PACMANN), a system where wave propagation in shallow water is the leading physical phenomenon, and the presence of electronics can be reduced to a CCD camera in detection. We show the realization of an XNOR logic gate as proof of concept of the Aqua-PACMANN's architecture and pave the way to a new class of fluid dynamic neuromorphic computing.