The standard method for benchmarking quantum error-correction is randomized fault-injection testing. The state-of-the-art tool stim is efficient for error correction implementations with distances of up to 10, but scales poorly to larger distances for low physical error rates. In this paper, we present a scalable approach that combines stratified fault injection with extrapolation. Our insight is that some of the fault space can be sampled efficiently, after which extrapolation is sufficient to complete the testing task. As a result, our tool scales to distance 17 for a physical error rate of 0.0005 with a two-hour time budget on a desktop. For this case, it estimated a logical error rate of 1.51×10−11 with high confidence.
@article{arxiv.2602.04921,
title = {Scalable testing of quantum error correction},
author = {John Zhuoyang Ye and Jens Palsberg},
journal= {arXiv preprint arXiv:2602.04921},
year = {2026}
}