保利噪声学习用于中间电路测量
Jordan Hines1,2, Timothy Proctor2
1University of California, Department of Physics, Berkeley, California 94720, USA.
Physical review letters
|February 6, 2025
概括
新的中环测量 (MCM) 基准测量尺度用于量化随机保利噪声和相关错误. 这种方法在当前量子硬件上推进了MCM性能表征.
科学领域:
- 量子信息科学 量子信息科学
- 量子计算硬件 量子计算硬件
背景情况:
- 目前用于中电路测量 (MCM) 的基准缺乏可扩展性和全面的错误量化能力.
- 需要先进的技术来准确评估量子系统中的MCM性能.
研究的目的:
- 介绍一种新的理论,用于在MCM中学习随机保利噪声.
- 开发一种可扩展的方法,即MCM周期基准测试,用于评估MCM性能.
主要方法:
- 开发了MCM周期基准测试,这是一个可扩展的MCM绩效评估技术.
- 在MCM中应用了一种学习随机保利噪声的理论.
- 从随机编译的MCM和Clifford gate层中提取出错误率.
主要成果:
- 证明了当前量子硬件上MCM期间对相关错误的量化.
- 展示了MCM周期基准测试的可扩展性,用于详细的错误分析.
- 验证了该方法在复杂量子电路中提取错误率的能力.
结论:
- MCM周期基准测试提供了一个可扩展的方法来表征MCM错误.
- 该方法可以与现有技术集成,用于全面的量子错误分析.
- 这项工作提升了使用MCM的量子硬件量化和减轻错误的能力.
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