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Network of parametrically driven silicon nitride mechanical membranes

Luis Mestre1,2, Suyash Singh1,2, Gabriel Margiani1,2, Letizia Catalini1,2,3, Alexander Eichler1,2, and Vincent Dumont1,2,*

  • 1Laboratory for Solid State Physics, ETH Zürich, 8093 Zürich, Switzerland
  • 2Quantum Center, ETH Zürich, 8093 Zürich, Switzerland
  • 3Center for Nanophotonics, AMOLF, 1098 XG Amsterdam, The Netherlands

  • *Contact author: vdumont@phys.ethz.ch

Phys. Rev. Applied 24, 044072 – Published 23 October, 2025

DOI: https://doi.org/10.1103/kx2w-czjf

Abstract

Networks of nonlinear resonators offer a promising platform for analog computing and the emulation of complex systems. However, realizing such networks remains challenging, as it requires resonators with high quality factors, individual frequency tunability, and strong interresonator coupling. In this work, we present a system that meets all these criteria. Our system is based on metalized silicon nitride membranes that are coupled via their common substrate and controlled capacitively via electrodes. We demonstrate individual frequency tuning and strong parametric driving of each membrane. Notably, we tune membrane frequencies through avoided crossings and demonstrate tunability of the coupled membrane’s parametric response. This platform provides a scalable and controllable setting for exploring collective phenomena, dynamical phase transitions, nonlinear topology, and analog computing.

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