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Updated: Sep 15, 2025

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多项式缩放本地化活动空间单元化选择性合集群单元和双元
Shreya Verma1, Ruhee D'Cunha1, Abhishek Mitra1
1Department of Chemistry, University of Chicago, Chicago, Illinois 60637, United States.
Journal of chemical theory and computation
|July 16, 2025
概括
一个新的多项式缩放算法用于局部化的活跃空间单元选择性合集群单双 (LAS-USCCSD) 改进了量子模拟. 这种方法准确地预测了分子特性,为模拟更大,化学上相关的系统铺平了道路.
科学领域:
- 量子化学 是一个量子化学.
- 计算化学计算化学
- 量子计算算法 量子计算算法
背景情况:
- 准确的量子化学计算对于理解分子行为至关重要.
- 结合集群方法,如CCSD,是非常准确的,但在计算上昂贵.
- 量子计算为加速复杂化学模拟提供了潜力.
研究的目的:
- 为本地化活性空间单元选择性合集群单双 (LAS-USCCSD) 方法开发一个多项式缩放算法.
- 为了实现更高效,更准确的化学相关系统的量子模拟.
- 评估量子模拟对于具有大活性空间的系统的可行性.
主要方法:
- 为 LAS-USCCSD 开发了一种多项式缩放算法,其中具有 O (6) 记忆缩放.
- 用广义化的维克定理来计算多引用波函数的衍生梯度表达式.
- 在量子模拟器上使用一个变量量子自溶解器来优化集群激发.
- 通过计算聚链的能量误差和分子系统的异构化/合能量来验证该方法.
主要成果:
- 建立了能量误差和幅度选择值 (ε) 之间的关系,用于聚链.
- 精确计算了 stilbene 和磁性合在二元体中的 cis-trans 异体化能量.
- 估计的量子资源用于模拟一个具有挑战性的 (30e,22o) 活跃空间在二元体中,目前无法达到.
结论:
- 多项式缩放LAS-USCCSD算法为量子化学模拟提供了准确和更有效的方法.
- 该方法证明了在量子硬件上模拟分子性能的实际可行性.
- 需要进一步开发,以满足非常大的活跃空间对量子资源的需求.
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