Sources of nonlinearity of a driven carbon nanotube electromechanical resonator
Journal article, 2026
Nanoelectromechanical resonators provide an ideal platform for investigating the interplay between electron transport and nonlinear mechanical motion. Externally driven suspended carbon nanotubes, containing an electrostatically defined quantum dot, are especially promising. These devices possess two main sources of nonlinearity: the electromechanical coupling and the intrinsic contributions of the resonator that induce a Duffing-like nonlinear behavior. In this work, we observe the interplay between the two sources across different driving regimes. The main nonlinear feature we observe is the emergence of archlike resonances in the electronic transport when the resonator is strongly driven. We show that our model is in good agreement with our experimental electron transport measurements on a suspended carbon nanotube. This characterization paves the way for the exploration of nonlinear phenomena using mesoscopic electromechanical resonators.
Author
Sofia Sevitz
Chalmers, Microtechnology and Nanoscience (MC2), Applied Quantum Physics
Kushagra Aggarwal
University of Oxford
Jorge Tabanera-Bravo
Complutense University
Max Planck Society
Juliette Monsel
Chalmers, Microtechnology and Nanoscience (MC2), Applied Quantum Physics
Florian Vigneau
University of Oxford
Federico Fedele
University of Oxford
Joe Dunlop
University of Exeter
Juan M. R. Parrondo
Complutense University
Gerard J. Milburn
University of Queensland
Janet Anders
University of Exeter
University of Potsdam
Natalia Ares
University of Oxford
Federico Cerisola
University of Exeter
PHYSICAL REVIEW RESEARCH
2643-1564 (eISSN)
Vol. 8 3 033237ASPECTS Quantum Thermodynamics of Precision in Electronic Devices
European Commission (EC) (101080167), 2022-11-01 -- 2025-10-31.
Terahertz quantum sensing with bilayer graphene quantum dots in resonators
Swedish Research Council (VR) (2023-06205), 2024-01-01 -- 2026-12-31.
Subject Categories (SSIF 2025)
Condensed Matter Physics
DOI
10.1103/t59c-rdnm
Related datasets
Code [dataset]
DOI: 10.5281/zenodo.20747566.