Hybrid cat-transmon architecture for scalable, hardware-efficient quantum error correction
Connor T. Hann, Kyungjoo Noh, Harald Putterman, Matthew H. Matheny, Joseph K. Iverson, Michael T. Fang, Christopher Chamberland, Oskar Painter, Fernando G.S.L. Brand\~ao

TL;DR
This paper proposes a scalable hybrid quantum computing architecture combining dissipative cat qubits and transmon qubits, enabling efficient quantum error correction with significant overhead reduction and practical implementation prospects.
Contribution
It introduces a cat-transmon entangling gate and demonstrates how to scale beyond repetition codes to surface codes for improved quantum error correction.
Findings
Logical error rates can be suppressed by increasing code distance.
Overhead reductions are significant compared to unbiased noise architectures.
Achievable physical error rates are within current experimental capabilities.
Abstract
Dissipative cat qubits are a promising physical platform for quantum computing, since their large noise bias can enable more hardware-efficient quantum error correction. In this work we theoretically study the long-term prospects of a hybrid cat-transmon quantum computing architecture where dissipative cat qubits play the role of data qubits, and error syndromes are measured using ancillary transmon qubits. The cat qubits' noise bias enables more hardware-efficient quantum error correction, and the use of transmons allows for practical, high-fidelity syndrome measurement. While correction of the dominant cat Z errors with a repetition code has recently been demonstrated in experiment, here we show how the architecture can be scaled beyond a repetition code. In particular, we propose a cat-transmon entangling gate that enables the correction of residual cat X errors in a thin rectangular…
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