格罗弗和相位估计算法的噪声分析以小数量的杂量子比特的量子奇数值转换来实现
Muhammad Abdullah Ijaz1, Muhammad Faryad2
1Department of Physics, Lahore University of Management Sciences, Lahore, 54792, Pakistan.
Scientific reports
|November 18, 2023
概括
噪音显著影响量子奇数值转换 (QSVT) 算法. 格罗弗搜索和量子相估计的QSVT实现显示了比原始版本更糟糕的噪声依赖性,成功概率随着错误率呈指数级下降.
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
- 算法分析 算法分析
背景情况:
- 量子奇数值转换 (QSVT) 是量子算法的一种多功能框架.
- 了解噪声影响对于开发实用的量子计算机至关重要.
- 目前的量子硬件受到噪音和少量量子比特的限制.
研究的目的:
- 调查各种噪音模型对QSVT实施的影响.
- 为了比较基于QSVT的格罗弗搜索和量子相估计 (QPE) 与它们的原始对应器的噪声弹性.
- 分析算法性能对错误概率和量子位数的依赖性.
主要方法:
- 模拟了格罗弗搜索和QPE算法的QSVT实现.
- 在四种噪声模型下进行分析:比特翻转,相位翻转,比特相位翻转和去极化噪声.
- 使用少量量子比特进行评估,以模仿当前杂的量子设备.
主要成果:
- 在所有测试模型中,与原始算法相比,QSVT实现对噪声的依赖程度始终较差.
- 格罗弗搜索的成功概率和QPE的准确性随着错误概率的增加而呈指数级降低.
- 性能降低显示对量子位数的线性依赖,但对错误概率的指数依赖.
结论:
- 虽然QSVT框架很强大,但比传统的Grover搜索和QPE实现更容易受到噪音的影响.
- 噪音对基于QSVT的量子算法构成了重大挑战,需要强大的错误缓解策略.
- 未来的研究应该专注于开发耐噪声的QSVT变体或错误纠正技术.
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