通过能量分类来减少单元合集群的电路深度
Yi Fan1,2, Changsu Cao3, Xusheng Xu1
1Central Research Institute, 2012 Laboratories, Huawei Technologies, Shenzhen 518129, China.
The journal of physical chemistry letters
|October 20, 2023
概括
这项研究介绍了一种能量分类策略,以减少噪音量子设备上的量子化学计算的电路深度. 这种方法大大减少了准确能源估计所需的操作人员数量.
科学领域:
- 量子计算是一种量子计算.
- 量子化学 是一个量子化学.
- 计算科学 计算科学
背景情况:
- 量子计算为复杂的量子化学问题提供了一种新的方法.
- 目前的噪音中等尺度量子 (NISQ) 设备的资源有限,这给大规模量子算法带来了挑战.
- 变量量子自溶解器 (VQE) 算法通常使用基于单元合集群 (UCC) 的算法.
研究的目的:
- 为了显著减少单元合集群 (UCC) 和基于UCC的ansatzes在变量量子自溶解器 (VQE) 算法中的电路深度.
- 为解决量子化学应用当前NISQ设备的局限性.
- 开发一种更有效的量子算法来计算分子和周期系统能量.
主要方法:
- 开发了一种能源分类策略,以根据其能源贡献预先选激发运营商.
- 量子电路模型是使用选定的运算符代构建的,直到能量趋同.
- 该方法适用于分子和周期系统.
主要成果:
- 电路深度大大减少,需要的操作人员减少了50%-98%.
- 保持了原始单元合集群单双 (UCCSD) 运营商池的准确性.
- 该策略在分子和周期系统中被证明是有效的.
结论:
- 能量分类策略为量子化学量子算法的效率提供了显著的改进.
- 这种方法有效地减少了NISQ设备上VQE算法的资源需求.
- 这种方法可以将其推广到量子计算中的其他参数变量分析中.
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