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P2 Codesign of quantum error-correcting codes and modular chiplets in the presence of defects

缺陷存在下量子纠错码与模块化 chiplet 的协同设计
ASPLOS Proceedings of the 29th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 22024匹配度 0/10 · 论文聚焦量子纠错码与模块化芯片在制造缺陷下的协同设计,属于量子计算体系结构,与用户关注的PL/AI、静态分析、LLM/Agent、浮点程序分析及贝叶斯程序分析方向无直接关联。引用 39 inbox
Sophia Fuhui Lin, Joshua Viszlai, Kaitlin N. Smith, Gokul Subramanian Ravi, Charles Yuan, Frederic T. Chong, Benjamin J. Brown
crossref: 2026-09-12dblp: 2026-09-12arxiv: 2026-09-12

AI 速览

一句话:通过适配表面码纠错电路并优化 chiplet 尺寸,在制造缺陷下显著降低容错量子计算的资源开销。

制造缺陷阻碍固态量子器件扩展到容错规模。本文将模块化 chiplet 架构与面向缺陷的量子纠错结合:把表面码伴随式读出电路适配到任意缺陷分布,模拟缺陷对保真度的影响。模拟表明该策略可指数抑制逻辑失败,非缺陷量子比特错误率约 0.1%。作者据此给出缺陷 chiplet 的后选择准则,并以每个逻辑量子比特所需平均物理量子比特数评估开销。缺陷率 1% 且 chiplet 尺寸最优时,两种缺陷模型的开销分别低于 3 倍和 6 倍;不容忍缺陷时开销随码距和缺陷率快速增长。码距 27 时,不容忍缺陷的模块化方案比 super-stabilizer 方案在 0.1% 和 0.3% 缺陷率下高 45 倍和逾 105 倍。

问题
制造误差使固态量子器件难以扩展到容错量子应用所需的规模,并带来额外纠错资源开销。
方法
模拟适配到缺陷量子比特阵列的表面码,调整伴随式读出电路以处理任意缺陷分布,并研究模块化 chiplet 架构中的后选择准则与资源开销。
评估
通过数值模拟评估逻辑失败率、后选择准则,以及达到目标逻辑错误率所需的平均物理量子比特数,并比较不同 chiplet 尺寸、缺陷率和方案。
原文摘要(Abstract)

Fabrication errors pose a significant challenge in scaling up solid-state quantum devices to the sizes required for fault-tolerant (FT) quantum applications. To mitigate the resource overhead caused by fabrication errors, we combine two approaches: (1) leveraging the flexibility of a modular architecture, (2) adapting the procedure of quantum error correction (QEC) to account for fabrication defects. We simulate the surface code adapted to defective qubit arrays to find metrics that characterize how defects affect fidelity. We then use our simulations to determine the impact of defects on the resource overhead of realizing a fault-tolerant quantum computer on a chiplet-based modular architecture. Our QEC simulation adapts the syndrome readout circuit for the surface code to account for an arbitrary distribution of defects. Our simulations show that our strategy for dealing with fabrication defects demonstrates an exponential suppression of logical failure, where error rates of non-defective physical qubits are ~ 0.1% for a circuit-based noise model. This is a typical regime on which we imagine running the defect-free surface code. We use our numerical results to establish post-selection criteria for assembling a device with defective chiplets. Using our criteria, we then evaluate the resource overhead in terms of the average number of physical qubits fabricated for a logical qubit to obtain a target logical error rate. We find that an optimal choice of chiplet size, based on the defect rate and target performance, is essential to limiting any additional error correction overhead due to defects. When the optimal chiplet size is chosen, at a defect rate of 1% the resource overhead can be reduced to below 3X and 6X respectively for the two defect models we use, for a wide range of target performance. Without tolerance to defects, the overhead grows exponentially as we increase the number of physical qubits in each logical qubit to achieve better performance, and also grows faster with an increase in the defect rate. When the target code distance is 27, the resource overhead of the defect-intolerant, modular approach is 45X and more than 105X higher than the super-stabilizer approach, respectively, at a defect rate of 0.1% and 0.3%. We also determine cutoff fidelity values that help identify whether a qubit should be disabled or kept as part of the QEC code.

链接与引用

DOI 原文 · arXiv · PDF(开放获取) · DBLP

BibTeX
@inproceedings{LinVSRYCB24,
  title = {Codesign of quantum error-correcting codes and modular chiplets in the presence of defects},
  author = {Sophia Fuhui Lin and Joshua Viszlai and Kaitlin N. Smith and Gokul Subramanian Ravi and Charles Yuan and Frederic T. Chong and Benjamin J. Brown},
  booktitle = {ASPLOS},
  year = {2024},
  doi = {10.1145/3620665.3640362}
}