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有效的量子想象时间进化通过漂流实时进化:一种低门和测量复杂度的方法.
Yifei Huang1, Yuguo Shao1,2, Weiluo Ren1
1ByteDance Research, Zhonghang Plaza, No. 43, North Third Ring West Road, Haidian District, Beijing 100089, China.
Journal of chemical theory and computation
|June 15, 2023
概括
量子想象时间进化 (QITE) 可以更有效地找到量子哈密尔顿. 我们的新漂移方案减少了电路深度和测量,改善了分子模拟的量子计算.
科学领域:
- 量子计算是一种量子计算.
- 量子化学是一种量子化学.
- 计算物理学的计算物理.
背景情况:
- 量子想象时间演化 (QITE) 是一个关键的量子算法,用于确定哈密尔顿的固有值和固有状态.
- 原始的QITE方法面临着深度量子电路和广泛测量的挑战,这是由于庞大的保利操作员池和Trotterization造成的.
研究的目的:
- 通过减少电路深度和测量开销来开发更高效的QITE算法.
- 提高QITE在量子化学和材料科学方面的实用性.
主要方法:
- 引入了一个以qDRIFT算法为灵感的时间依赖漂移方案,以减轻电路深度要求.
- 开发了一种确定性算法,用于选择主导的保利项,以尽量减少基本状态准备过程中的波动.
- 在Trotter步骤中实施了一种高效的测量减少方案,以降低计算成本.
主要成果:
- 拟议的漂移方案消除了对操作者池大小的深度依赖,并显示与步数的数量相反的收.
- 确定性算法和测量减少方案分别显著降低了波动和测量成本.
- 包括LiH在内的基准分子的数值模拟表明,可与先进的自适应VQE方法相比较的电路深度,测量次数要少得多.
结论:
- 增强的QITE算法为量子自值问题提供了实用和高效的方法.
- 这种方法显著减少了量子模拟的资源需求,使其在当前的量子硬件上更容易获得.
- 这些改进为更准确和可行的量子计算化学研究铺平了道路.
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