Bunny Codes: Broadening Superconducting Quantum Error Correction Capability through Advanced Control Engineering
Abstract
Drawing on advances in superconducting qubit control schemes that unlock enriched native gate sets at the hardware level, we systematically examine how harnessing this enlarged physical two-qubit gate pool---specifically CNOT and CXSWAP---streamlines syndrome extraction for certain qLDPC codes with nonlocal stabilizers. Through an exhaustive search, we discover a set of qLDPC codes with various stabilizer weights and distances that can be implemented on the two-dimensional nearest-neighbor qubit connectivity native to superconducting hardware while achieving performance equivalent to that of the direct CNOT implementation requiring long-range interactions. We refer to those codes as Bunny codes. Across all code distances we examine, the best Bunny codes with weight-6 stabilizers in periodic boundary conditions have a code rate approximately 3× that of the toric code; when converted to open boundary conditions, they retain an approximately 2× code rate advantage over the rotated surface code. In circuit-level simulation, we find that some Bunny codes exhibit logical error rates an order of magnitude lower than toric codes with comparable code rates. Our results demonstrate that high-performance quantum error correction can be achieved using an expanded gate set rather than long-range couplers, thereby significantly reducing hardware complexity.
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BibTeX
@misc{zhou2026bunny,
title = {{Bunny Codes: Broadening Superconducting Quantum Error Correction Capability through Advanced Control Engineering}},
author = {Runshi Zhou and Xingye Yuan and Linghang Kong and Fang Zhang and Kai Zhang and Zhaohui Yang and Jianxin Chen},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2606.22853},
eprint = {2606.22853},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2606.22853},
}
RIS
TY - UNPB
TI - Bunny Codes: Broadening Superconducting Quantum Error Correction Capability through Advanced Control Engineering
AU - Runshi Zhou
AU - Xingye Yuan
AU - Linghang Kong
AU - Fang Zhang
AU - Kai Zhang
AU - Zhaohui Yang
AU - Jianxin Chen
PY - 2026
DA - 2026/08/28
PB - arXiv
DO - 10.48550/arxiv.2606.22853
UR - https://arxiv.org/abs/2606.22853
AB - Drawing on advances in superconducting qubit control schemes that unlock enriched native gate sets at the hardware level, we systematically examine how harnessing this enlarged physical two-qubit gate pool---specifically CNOT and CXSWAP---streamlines syndrome extraction for certain qLDPC codes with nonlocal stabilizers. Through an exhaustive search, we discover a set of qLDPC codes with various stabilizer weights and distances that can be implemented on the two-dimensional nearest-neighbor qubit connectivity native to superconducting hardware while achieving performance equivalent to that of the direct CNOT implementation requiring long-range interactions. We refer to those codes as Bunny codes. Across all code distances we examine, the best Bunny codes with weight-6 stabilizers in periodic boundary conditions have a code rate approximately 3× that of the toric code; when converted to open boundary conditions, they retain an approximately 2× code rate advantage over the rotated surface code. In circuit-level simulation, we find that some Bunny codes exhibit logical error rates an order of magnitude lower than toric codes with comparable code rates. Our results demonstrate that high-performance quantum error correction can be achieved using an expanded gate set rather than long-range couplers, thereby significantly reducing hardware complexity.
ER -