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在NISQ云中的西蒙算法.

Reece Robertson1,2,3, Emery Doucet1,2, Ernest Spicer4

  • 1Department of Physics, University of Maryland, Baltimore County (UMBC), Baltimore, MD 21250, USA.

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概括
此摘要是机器生成的。

这项研究使用西蒙算法对量子云设备进行了基准测试,揭示了超导芯片的关键错误率和架构洞察力. 了解量子硬件是未来量子优势的关键.

关键词:
在 NISQ 计算中,NISQ 是一个计算器.西蒙的算法是Simon的算法.这是一个量子优势.

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科学领域:

  • 量子计算是一种量子计算.
  • 量子信息科学 量子信息科学
  • 计算复杂性理论 计算复杂性理论

背景情况:

  • 西蒙的算法提供了理论上的量子优势,但需要容错量子比特.
  • 目前的量子云平台提供了对杂的中等规模量子 (NISQ) 设备的访问.
  • 对这些NISQ设备进行基准测试对于评估其实际能力至关重要.

研究的目的:

  • 通过量子云对商用量子计算设备的错误率进行基准测试.
  • 为了比较不同物理量子计算平台的性能,特别是IBM和IonQ.
  • 调查设备架构和拓对量子算法执行的影响.

主要方法:

  • 在量子云平台上实现西蒙的算法.
  • 对算法输出进行分析,以量化量子位错误率.
  • 对IBM的超导和IonQ的被困离子量子处理器进行比较研究.
  • 检查转载策略及其对绩效的影响.

主要成果:

  • 在IBM和IonQ量子硬件之间对错率的客观比较.
  • 证明在超导架构中空间分离的量子位上进行双量子位运算是有害的.
  • 确定运行量子算法的平台特定挑战和优势.
  • 基于量子位连接和拓学的性能变化的量化.

结论:

  • 西蒙的算法作为一个有效的工具,用于基准测试当前的量子硬件.
  • 设备架构和量子比特连接性显著影响量子算法性能.
  • 仔细考虑硬件拓对于高效的转换和在NISQ设备上实现量子优势至关重要.
  • 该研究为选择适合特定算法任务的量子硬件提供了有价值的数据.