Deterministic multi-phonon entanglement between two mechanical resonators on separate substrates

TL;DR

This paper demonstrates a modular platform for generating and analyzing multi-phonon entanglement between two mechanical resonators on separate substrates, achieving high-fidelity entangled states and paving the way for complex phonon-based quantum computing.

Contribution

The authors introduce a novel modular system capable of rapid multi-phonon entanglement and tomographic analysis between separate mechanical resonators, advancing phonon-based quantum information processing.

Findings

Generated a mechanical Bell state with fidelity 0.872

Created a multi-phonon N=2 N00N state with fidelity 0.748

Platform shows potential for scalable phononic quantum computing

Abstract

Mechanical systems have emerged as a compelling platform for applications in quantum information, leveraging recent advances in the control of phonons, the quanta of mechanical vibrations. Several experiments have demonstrated control and measurement of phonon states in mechanical resonators integrated with superconducting qubits, and while entanglement of two mechanical resonators has been demonstrated in some approaches, a full exploitation of the bosonic nature of phonons, such as multi-phonon entanglement, remains a challenge. Here, we describe a modular platform capable of rapid multi-phonon entanglement generation and subsequent tomographic analysis, using two surface acoustic wave resonators on separate substrates, each connected to a superconducting qubit. We generate a mechanical Bell state between the two mechanical resonators, achieving a fidelity of $\mathcal{F} = 0.872\pm 0.002$, and further demonstrate the creation of a multi-phonon entangled state (N=2 N00N state), shared between the two resonators, with fidelity $\mathcal{F} = 0.748\pm 0.008$. This approach promises the generation and manipulation of more complex phonon states, with potential future applications in bosonic quantum computing in mechanical systems. The compactness, modularity, and scalability of our platform further promises advances in both fundamental science and advanced quantum protocols, including quantum random access memory and quantum error correction.