评估工业相关量子计算的需求
Assessing the Requirements for Industry Relevant Quantum Computation
AI总结：
本文利用开源量子资源估算工具，基于制造业工业排班问题和 QISS 算法评估工业量子计算需求，指出量子门与测量时间及错误率要求排除了近期量子优势。
摘要：
在本文中，我们使用开源工具进行量子资源估算，以评估工业相关量子计算的需求。我们的分析采用制造业中的工业排班问题以及 Quantum Industrial Shift Scheduling（量子工业排班）算法。我们将性能指标建立在当前技术以及超导量子比特平台的理论高保真场景之上。我们发现，量子门和测量操作的执行时间对总体计算运行时间的决定性强于系统错误率。此外，实现量子加速不仅需要较低的系统错误率（$10^{-6}$ 或更优），还需要执行时间低于 10ns 的测量操作。这排除了该用例在近期实现量子优势的可能性，并表明在实现此类优势之前，需要在技术或算法上取得重大进展。
英文摘要：
In this paper, we use open-source tools to perform quantum resource estimation to assess the requirements for industry-relevant quantum computation. Our analysis uses the problem of industrial shift scheduling in manufacturing and the Quantum Industrial Shift Scheduling algorithm. We base our figures of merit on current technology, as well as theoretical high-fidelity scenarios for superconducting qubit platforms. We find that the execution time of gate and measurement operations determines the overall computational runtime more strongly than the system error rates. Moreover, achieving a quantum speedup would not only require low system error rates ($10^{-6}$ or better), but also measurement operations with an execution time below 10ns. This rules out the possibility of near-term quantum advantage for this use case, and suggests that significant technological or algorithmic progress will be needed before such an advantage can be achieved.
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