Hybrid cat-transmon architecture for scalable, hardware-efficient quantum error correction

Dissipative cat qubits are a promising physical platform for quantum computing, since their large noise bias can enable more hardware-efficient quantum error correction. However, implementing high-fidelity, bias-preserving gates between dissipative cats is experimentally challenging, requiring both low loss and strong engineered dissipation. To circumvent these onerous experimental requirements, we propose a scalable quantum computing architecture where dissipative cat qubits are concatenated into repetition or surface codes, and syndromes are measured using ancillary transmon qubits. The use of transmons, rather than cats, as ancillary qubits significantly eases requirements on loss and engineered dissipation, while the use of cats as data qubits means the benefits of biased noise are retained. To analyze the architecture, we propose implementations of bias-preserving cat-transmon entangling gates, benchmark their performance with master equation simulations, and feed the results into error correction simulations of repetition and surface codes (both XZZX and CSS). We find a significant increase in the error correction threshold relative to an all-cat architecture, a promising sign for near-term experimental implementations.