English

Quantum error correction at ultra-low overhead

Quantum Physics 2026-08-03 v1

Abstract

Suppressing errors is the central challenge for useful large-scale quantum computing. While quantum error correction promises a viable solution to this challenge, existing codes typically suffer from trade-offs among encoding efficiency, error threshold, and hardware feasibility. Here, we introduce Cornucopia codes, a family of practical, hardware-efficient quantum low-density parity-check codes that achieve an ultra-high encoding rate exceeding 1/21/2 while maintaining a pseudo-threshold exceeding 0.4%0.4\% under the standard circuit-level noise model. Inspired by recent affine-permutation-based code constructions and the long-range connectivity available in reconfigurable neutral-atom arrays, we adopt a structured code geometry in which the code layout, atom rearrangement, and syndrome-extraction schedule are co-designed. This structure enables nonlocal syndrome measurements through simple, parallel atom rearrangements. A complete syndrome extraction cycle measures all XX- and ZZ-type checks in parallel with 1212 entangling layers, independent of the code size. The resulting threshold is comparable to those of the surface code and bivariate bicycle codes. In particular, a single code block [[2844,1426,18]][[2844,1426,18]] encodes 1,4261{,}426 distance-1818 logical qubits, achieving an extrapolated logical error rate of 2.6×10162.6\times10^{-16} (1.9×10311.9\times10^{-31}) per logical qubit per cycle, assuming the physical error rate of 0.1%0.1\% (0.01%0.01\%). By comparison, a bivariate bicycle code implementation would require more than 68,00068{,}000 physical qubits to encode the same number of logical qubits at a comparable logical error rate. These results bring demonstrations of ultra-low overhead quantum error correction within the reach of near-term quantum processors.

Cite

@article{arxiv.2608.02773,
  title  = {Quantum error correction at ultra-low overhead},
  author = {Zhide Lu and Weikang Li and Dong-Ling Deng},
  journal= {arXiv preprint arXiv:2608.02773},
  year   = {2026}
}