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Implementation of reservoir computing using coupled microelectromechanical drum resonators via sideband-pumped
Theresa Farah1, Loïc Flis1, Pierre Laly1
1CNRS, University of Lille, Centrale Lille, Univ. Polytechnique Hauts-de-France, UMR 8520 IEMN, Lille, France.
Microsystems & Nanoengineering
|May 7, 2026
Summary
This study demonstrates a novel microelectromechanical system for reservoir computing using coupled drum resonators. This integrated platform efficiently processes temporal information with potential for advanced sensing applications.
Area of Science:
- Physics
- Engineering
- Computer Science
Background:
- Reservoir computing is a machine learning technique using nonlinear system dynamics for temporal processing.
- Microelectromechanical systems (MEMS) offer potential for integrated sensing and computing due to their inherent nonlinear and temporal properties.
Purpose of the Study:
- To experimentally demonstrate a physical reservoir computing platform using coupled MEMS resonators.
- To explore a sideband pumping scheme for creating nonlinear dynamics in a multimode architecture.
Main Methods:
- Utilized two capacitively coupled drum resonators operating in the MHz regime.
- Employed phonon-cavity electromechanics with sideband pumping and time-delay feedback for reservoir computing.
- Evaluated performance using parity and Normalized Auto-Regressive Moving Average benchmarks.
Main Results:
- Successfully implemented reservoir computing on a compact MEMS platform.
- Demonstrated nonlinear dynamics through pump amplitude modulation and energy transfer between resonators.
- Validated the effectiveness of the sideband pumping scheme for multimode reservoir computing.
Conclusions:
- The coupled drum resonator MEMS platform is suitable for integrated sensing and reservoir computing.
- The sideband pumping approach enables the extension of reservoir computing to multimode systems.
- This work paves the way for advanced, compact, and integrated information processing devices.
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