论文标题
在群集状态张量产品的基础上选择的配置互动
Selected Configuration Interaction in a Basis of Cluster State Tensor Products
论文作者
论文摘要
由于最近的几个进展提高了总体计算效率或所产生的SCI矢量的紧凑性，因此当前所选的配置交互（SCI）方法正在享受复苏。与常规方法相比，这些最近的进步使得为更大的轨道活动空间获得全CI（FCI）质量结果成为可能。但是，由于开始假设FCI载体只有少数重要的Slater决定因素，因此SCI对于具有较强相关性的系统变得棘手。本文介绍了一种以一种利用局部分子结构来显着减少SCI变量数量的方式来开发科幻算法的方法。提出的方法是通过首先将轨道分组到簇中来定义的，我们可以在其上定义许多粒子簇状态。然后，我们直接以簇状态的张量产物而不是Slater决定因素的张量来执行SCI算法。尽管该方法对于任意定义的聚类状态是一般的，但我们通过通过全局（和稀疏）SCI向量的塔克分解来定义群集状态，从而显着提高了性能。为了证明这种方法的潜力，称为张量产品所选的配置相互作用（TPSCI），我们为各种示例提供了数值结果：1）具有不同的相互间隔和内部群集跳跃术语的修改后的Hubbard模型，2）与N2和F2中的键突出的键突出的键突出的键断裂，以及42个基于3）的粘结率，以及42个基于3）的Electors Introke in2 soctive in 2）In2 soctive in 2）In2 soctive in 2）In2 ockative in 2）。轨道。这些数值结果表明，TPSCI可用于显着减少变化空间中的SCI变量数量，从而铺平了将这些确定性和变分SCI方法扩展到更广泛的物理系统的路径。
Selected configuration interaction (SCI) methods are currently enjoying a resurgence due to several recent developments which improve either the overall computational efficiency or the compactness of the resulting SCI vector. These recent advances have made it possible to get full CI (FCI) quality results for much larger orbital active spaces, compared to conventional approaches. However, due to the starting assumption that the FCI vector has only a small number of significant Slater determinants, SCI becomes intractable for systems with strong correlation. This paper introduces a method for developing SCI algorithms in a way which exploits local molecular structure to significantly reduce the number of SCI variables. The proposed method is defined by first grouping the orbitals into clusters over which we can define many particle cluster states. We then directly perform the SCI algorithm in a basis of tensor products of cluster states instead of Slater determinants. While the approach is general for arbitrarily defined cluster states, we find significantly improved performance by defining cluster states through a Tucker decomposition of the global (and sparse) SCI vector. To demonstrate the potential of this method, called tensor product selected configuration interaction (TPSCI), we present numerical results for a diverse set of examples: 1) modified Hubbard model with different inter- and intra-cluster hopping terms, 2) less obviously clusterable cases of bond breaking in N2 and F2, and 3) ground state energies of large planar π-conjugated systems with active spaces of up to 42 electrons in 42 orbitals. These numerical results show that TPSCI can be used to significantly reduce the number of SCI variables in the variational space, and thus paving a path for extending these deterministic and variational SCI approaches to a wider range of physical systems.
