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强关联通过有效哈密顿量和微扰理论处理。

Strong correlation treated via effective hamiltonians and perturbation theory.

机构信息

Department of Physical Chemistry, Sciences II, University of Geneva, Quai E. Ansermet 30, 1211 Geneva, Switzerland.

出版信息

J Chem Phys. 2011 Jan 21;134(3):034114. doi: 10.1063/1.3532927.

Abstract

We propose a new approach to determine a suitable zeroth-order wavefunction for multiconfigurational perturbation theory. The same ansatz as in complete active space (CAS) wavefunction optimization is used but it is split in two parts, a principal space (A) and a much larger extended space (B). Löwdin's partitioning technique is employed to map the initial eigenvalue problem to a dimensionality equal to that of (A) only. Combined with a simplified expression for the (B) portion of the wavefunction, we are able to drastically reduce the storage and computational demands of the wavefunction optimization. This scheme is used to produce reference wavefunctions and energies for subsequent second-order perturbation theory (PT2) corrections. Releasing the constraint of computing the exact CAS energy and wavefunction prior to the PT2 treatment introduces a nonstandard paradigm for multiconfigurational methods. Based on the results of test calculations, we argue that principal parts with only few percents of the total number of CAS configurations could provide final multiconfigurational PT2 energies of the same accuracy as in the standard paradigm. In the future, algorithmic improvements for this scheme will bring into reach active spaces much beyond the present limit of CAS-based methods, therefore allowing for accurate studies of systems featuring strong correlation.

摘要

我们提出了一种新方法来确定多组态微扰理论的合适的零阶波函数。使用与完全活性空间(CAS)波函数优化相同的假设,但将其分为两部分,主空间(A)和更大的扩展空间(B)。采用 Löwdin 分区技术将初始特征值问题映射到仅与(A)维度相等的问题。结合波函数(B)部分的简化表达式,我们能够大大降低波函数优化的存储和计算需求。该方案用于生成参考波函数和能量,以进行后续的二阶微扰理论(PT2)校正。在 PT2 处理之前释放计算精确 CAS 能量和波函数的约束条件,为多组态方法引入了一种非标准范例。基于测试计算的结果,我们认为仅包含总 CAS 配置数的几个百分比的主要部分就可以提供与标准范例相同精度的最终多组态 PT2 能量。在未来,这种方案的算法改进将使活性空间远远超出基于 CAS 方法的现有限制,从而可以对具有强相关性的系统进行准确研究。

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