Multireference configuration interaction and perturbation theory without reduced density matrices
Multireference configuration interaction and perturbation theory without reduced density matrices
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DOI：
10.1063/1.5128115
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发表时间：
2019-12-07
影响因子：
4.4
通讯作者：
Sharma, Sandeep
中科院分区：
文献类型：
--
作者：
Mahajan, Ankit;Blunt, Nick S.;Sharma, Sandeep
高阶降密度矩阵（RDM）的计算成本高昂的评估和存储一直是大型活动空间中多参考波函数动态相关性计算的瓶颈。我们提出了多参考配置交互和微扰理论的随机公式，避免了对这些昂贵的 RDM 的需要。这里介绍的算法足够灵活，可以合并各种主动空间参考波函数，包括选定的配置相互作用、矩阵乘积状态和对称投影贾斯特罗平均场波函数。它具有蒙特卡罗方法通常有吸引力的特征，例如令人尴尬的并行性和低内存成本。我们发现，对于包含少至 14 个轨道的小型活动空间，随机算法已经可以与确定性算法竞争。我们使用基准应用程序来说明随机公式的实用性。由 AIP Publishing 许可发布。
The computationally expensive evaluation and storage of high-rank reduced density matrices (RDMs) has been the bottleneck in the calculation of dynamic correlation for multireference wave functions in large active spaces. We present a stochastic formulation of multireference configuration interaction and perturbation theory that avoids the need for these expensive RDMs. The algorithm presented here is flexible enough to incorporate a wide variety of active space reference wave functions, including selected configuration interaction, matrix product states, and symmetry-projected Jastrow mean field wave functions. It enjoys the usual attractive features of Monte Carlo methods, such as embarrassing parallelizability and low memory costs. We find that the stochastic algorithm is already competitive with the deterministic algorithm for small active spaces, containing as few as 14 orbitals. We illustrate the utility of our stochastic formulation using benchmark applications. Published under license by AIP Publishing.