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使用单个CPU的MegaQuOp量子计算机实时解码器

Real-time decoder for a MegaQuOp quantum computer using a single CPU

Min Ye, Andrii Maksymov, Nicolas Delfosse

arXiv 2608.25027首次发表:更新:

发表机构

IonQ Inc.(IonQ公司)

机构由 AI 辅助整理,请以论文原文为准。

AI 中文总结

研究针对MegaQuOp量子计算机,开发了在单个CPU上运行的端到端实时解码栈,经测试其在408个逻辑量子比特、100万个$T$门的工作负载下解码延迟满足要求,实现了MegaQuOp规模的实时解码。

AI 中文摘要

随着量子计算机向执行数百万个门的MegaQuOp机器阶段发展,能够在这类设备中实现实时纠错的解码系统将至关重要。近期研究工作主要聚焦于纠错存储器或少量逻辑操作的解码。本文展示了一种适用于通用容错囚禁离子量子计算机架构的端到端实时解码栈,该解码栈可对数百个逻辑量子比特上的数百万个逻辑门构成的实际工作负载进行解码。完整的流水线包括实时检测器误差模型生成、所有逻辑量子比特解码、逻辑操作解码以及魔态工厂解码,全部在单个CPU上运行。我们在实际相关量子应用上对该解码器进行基准测试,应用涵盖多达408个逻辑量子比特和多达100万个$T$门。假设囚禁离子架构的周期时间为1至5毫秒,在$p_{\text{CNOT}}=10^{-4}$时,解码延迟使计算增加的比例小于0.3%;在$p_{\text{CNOT}}=5\times10^{-4}$时,对所有研究的工作负载,该比例小于12%。这些结果证明了在单个常规CPU上实现MegaQuOp规模的实时解码是可行的。

英文摘要

As quantum computers advance toward the regime of MegaQuOp machines executing millions of gates, a decoding system capable of real-time error correction in such a device will be crucial. Recent efforts have been focused on decoding an error-corrected memory or a small number of logical operations. Here we demonstrate an end-to-end real-time decoding stack for a universal fault-tolerant trapped-ion quantum computer architecture capable of decoding real workloads with millions of logical gates over hundreds of logical qubits. The complete pipeline, including on the fly detector error model generation, decoding of all logical qubits, logical operations, and magic-state factories, runs on a single CPU. We benchmark the decoder on practically relevant quantum applications spanning up to 408 logical qubits, and up to one million $T$ gates. Assuming a trapped-ion architecture with 1 to 5 ms cycle time, the decoding delay stretches the computation by less than $0.3\%$ at $p_{\mathrm{CNOT}}=10^{-4}$ and less than $12\%$ at $p_{\mathrm{CNOT}}=5\times 10^{-4}$ for all workloads studied. These results demonstrate real-time decoding at MegaQuOp scale on a single conventional CPU.

CommentsIn this updated version, we corrected a typo in the description of the simulated Heisenberg Hamiltonian: the model is defined on a degree-three random regular graph, whereas the previous version incorrectly stated degree seven. We also added details on logical frame tracking, inter-block logical measurements, and the simulation of magic-state factories

论文原文

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