Silicon opto-electro-mechanics for bridging the gap between photonics and microwaves

Conversion between electrical and optical signals enabled the use of near-infrared (near-IR) photons for high data rate transmission through optical fibre networks.

Likewise, coherent conversion between microwave and optical photons stands as a promising solution to transfer quantum states between remote quantum processors, thus enabling the development of large-scale quantum networks.

However, the vast frequency difference between microwave (GHz) and near-IR (200 THz) optical photons hampers direct coherent conversion.

This limitation could be circumvented by phonon-mediated transduction, which is a coherent two-step process, comprising electromechanical and optomechanical conversions.

On-chip microwave-optical conversion mediated by GHz phonons has the potential to be extremely efficient due to the large optomechanical response of common materials, and the similar wavelength of GHz phonons and near-IR photons.

Yet, it is an open challenge to achieve efficient electromechanical and optomechanical conversion simultaneously in a single integrated circuit.

State-of-the-art demonstrations show that surface acoustic waves (SAWs) allow efficient electromechanical conversion, while cavity optomechanics utilize tightly confined optical and mechanical modes to yield strong optomechanical coupling. However, combining these two approaches is still considered challenging, if not impossible.

The SPRING project will overcome these limitations by developing a fundamentally new optomechanical coupling approach to bridge SAW electromechanics and cavity optomechanics.

The original idea is to use subwavelength nanostructuration of silicon cavities to couple tightly confined optical modes and SAWs.

The SPRING strategy will be used to demonstrate coherent microwave-optical conversion of single photons and quantum state transfer between superconducting qubits, monolithically integrated in a silicon chip, opening a new path for applications in communications, sensing and computing.