一句话：提出软硬件协同设计方法 ACQC，通过分解–布局协同设计与优化布局，大幅加速 qLDPC 码上的容错量子计算。
容错量子计算依赖量子纠错码在含噪量子计算机上运行大规模量子程序。量子低密度奇偶校验（qLDPC）码相比表面码可节省一个数量级的量子比特，但其仅支持有限的操作集合，程序必须被分解为大量 qLDPC 支持的操作，导致执行时间长达数十天，严重阻碍其实用化。本文提出 ACQC——一种软硬件协同设计方法，以加速 qLDPC 码中的计算。作者首先提出新颖的分解–布局协同设计，以量子比特开销为代价显著缩短执行时间；随后利用 qLDPC 码特性与所提分解技术降低量子比特开销；最后通过设计最优的 qLDPC 码布局来减少魔态蒸馏的开销。由于目前尚无 qLDPC 码硬件，作者采用全面的模拟进行评估。结果表明，ACQC 相对基线 qLDPC 码容错量子计算平均取得 4.4 倍加速，并相对表面码容错量子计算平均减少 18.3 倍量子比特。
Fault-tolerant quantum computing (FTQC) uses quantum error correction (QEC) codes to execute large-scale quantum programs on noisy quantum computers. Quantum low-density parity-check (qLDPC) codes are promising as they use an order of magnitude fewer qubits than widely used surface codes. However, as qLDPC codes support only a limited set of operations, they require programs to be decomposed into many qLDPC-supported operations. This prohibitively increases the execution time of FTQC applications to tens of days, hindering the practical viability of qLDPC codes. In this paper, we propose ACQC, a software–hardware co-design approach to accelerate computation in qLDPC codes, realizing the practical use of qLDPC codes for FTQC. To achieve this goal, we first introduce a novel decomposition–layout co-design that significantly reduces execution time at the cost of qubit overhead. Then, we reduce the qubit overhead by exploiting characteristics of qLDPC codes and our decomposition technique. Lastly, we reduce the qubit overhead of magic state distillation by designing an optimal qLDPC code layout. As there is currently no available hardware for qLDPC codes, we evaluate ACQC with a comprehensive simulation. The results show that ACQC achieves 4.4× speedup over the baseline qLDPC code FTQC and 18.3× qubit reduction over the surface code FTQC on average.
@inproceedings{ChoJKCHK26,
title = {Accelerating Computation in Quantum LDPC Code},
author = {Jungmin Cho and Hyeonseong Jeong and Junpyo Kim and Junhyuk Choi and Juwon Hong and Jangwoo Kim},
booktitle = {ASPLOS},
year = {2026},
doi = {10.1145/3779212.3790122}
}