Poster

Microwave optomechanics with a carbon nanotube nano-electromechanical resonator

Andreas K. Hüttel1, Akong Loh1, Katrin Burkert1, Furkan Özyigit1, Fabian Stadler1, Niklas Hüttner1

Presenting Author:

andreas.huettel@ur.de

Carbon nanotube (CNT) nanomechanical resonators have been used as ultrasensitive force, mass, and charge sensors [1]. In addition, the nanoscale nature of CNTs makes them excellent for studying and exploiting quantum phenomena in nanomechanics. When suspended on source and drain leads and gated, a CNT nano-electromechanical resonator can at low temperature also be operated as a quantum dot. The motion of the nanotube is then strongly coupled to single electron tunneling processes, allowing extreme tunability of the nano-electromechanical parameters including resonance frequency, nonlinearity, and dissipation.

Using this configuration, we have realized optomechanical coupling of a single wall CNT nanomechanical resonator to a microwave cavity and quantified it through optomechanically induced transparency (OMIT) measurements [2,3]. The nonlinearity of Coulomb blockade in the CNT significantly enhances the coupling strength, reaching a single-photon optomechanical coupling of g0 ∼100 Hz [2,3]; also back-action of the CNT on the microwave cavity has been demonstrated.

Ongoing work is directed towards strong coupling, motion read-out, and ground state cooling of the nanomechanical resonator. Updated chip design and fabrication techniques have led to larger geometric coupling capacitances as well as a significantly higher microwave cavity quality factor. The coherent optomechanical limit brings the possibility of building a mechanical “quantum switchboard” where quantum information could be transferred between the subsystems; suspended CNTs have been proposed as long-lived nano-electromechanical qubits [4]. Mechanical quantum computation platforms remain a topic of great interest [5], and a strongly coupled optomechanical system will be essential for the realization of a full CNT based quantum computation platform.

[1] A. K. Hüttel et al., Nano Lett. 9, 2547 (2009); G. A. Steele et al., Science 325, 1103 (2009).
[2] S. Blien et al., Nat. Comm. 11, 1636 (2020).
[3] N. Hüttner et al., Phys. Rev. Applied 20, 064019 (2023).
[4] F. Pistolesi et al., PRX 11, 031027 (2021).
[5] Y. Yang et al., Science 386, 783 (2024).