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arXiv 2201.08825quant-phcs.ARcs.DC
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为扩展超导量子计算规模的短程微波网络建模

Modeling Short-Range Microwave Networks to Scale Superconducting Quantum Computation

Nicholas LaRacuente, Kaitlin N. Smith, Poolad Imany, Kevin L. Silverman, Frederic T. Chong

AI总结:

针对超导量子计算机扩容量子比特时的噪声与串扰问题,提出基于微波链路的小芯片分布式架构,建模验证其可降低数据移动总体错误率、延迟影响小,为量子计算规模化提供新路径。

摘要:

超导量子计算机的核心挑战在于,在不增加噪声或串扰的前提下,提升每个处理器中的量子比特数量。在被称为chiplets(小芯片)的小型量子比特阵列上开展分布式量子计算,能够以可扩展的方式应对这些挑战。我们提出了一种基于微波链路的小芯片架构,该架构有望在近期硬件上超越单片式量子处理器的性能。我们用于建模和评估该小芯片架构的方法,打通了这类处理器的物理层与网络层。我们发现有证据表明,尽管跨链路传输的错误率更高,但将计算分布在多个小芯片上,可能会降低与器件内数据移动相关的总体错误率。初步分析显示,延迟不会受到显著影响,且至少部分应用和架构可以避免小芯片边界附近的瓶颈。从长远来看,短程网络可能会成为量子计算机的基础,就如同局域网是当今经典数据中心和超级计算机的基础一样。

英文摘要:

A core challenge for superconducting quantum computers is to scale up the number of qubits in each processor without increasing noise or cross-talk. Distributed quantum computing across small qubit arrays, known as chiplets, can address these challenges in a scalable manner. We propose a chiplet architecture over microwave links with potential to exceed monolithic performance on near-term hardware. Our methods of modeling and evaluating the chiplet architecture bridge the physical and network layers in these processors. We find evidence that distributing computation across chiplets may reduce the overall error rates associated with moving data across the device, despite higher error figures for transfers across links. Preliminary analyses suggest that latency is not substantially impacted, and that at least some applications and architectures may avoid bottlenecks around chiplet boundaries. In the long-term, short-range networks may underlie quantum computers just as local area networks underlie classical datacenters and supercomputers today.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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