Institute of Systems and Physical Biology, Shenzhen Bay Laboratory, Shenzhen518055, China.
Department of Chemistry and Supercomputing Institute, University of Minnesota, Minneapolis, Minnesota55455, United States.
J Chem Theory Comput. 2022 Dec 13;18(12):7403-7411. doi: 10.1021/acs.jctc.2c00859. Epub 2022 Nov 8.
Complementary to the theorems of Hohenberg and Kohn for the ground state, Theophilou's subspace theory establishes a one-to-one relationship between the total eigenstate energy and density ρ() of the subspace spanned by the lowest eigenstates. However, the individual eigenstate energies are not directly available from such a subspace density functional theory. Lu and Gao ( , , 7762) recently proved that the Hamiltonian projected on to this subspace is a matrix functional of the multistate matrix density () and that variational optimization of the trace of the Hamiltonian matrix functional yields exactly the individual eigenstates and densities. This study shows that the matrix density () is the necessary fundamental variable in order to determine the exact energies and densities of the individual eigenstates. Furthermore, two ways of representing the matrix density are introduced, making use of nonorthogonal and orthogonal orbitals. In both representations, a multistate active space of auxiliary states can be constructed to exactly represent () with which an explicit formulation of the Hamiltonian matrix functional is presented. Importantly, the use of a common set of orthonormal orbitals makes it possible to carry out multistate self-consistent-field optimization of the auxiliary states with singly and doubly excited configurations (MS-SDSCF).
与 Hohenberg 和 Kohn 的基态定理互补,Theophilou 的子空间理论在由最低本征态张成的子空间的总本征态能量和密度 ρ()之间建立了一一对应关系。然而,这样的子空间密度泛函理论并不能直接得到各个本征态能量。Lu 和 Gao(,, 7762)最近证明,投影到这个子空间上的哈密顿量是一个多态矩阵密度 ()的矩阵泛函,并且哈密顿量矩阵泛函的迹的变分优化恰好给出了各个本征态和密度。这项研究表明,矩阵密度 ()是确定各个本征态的精确能量和密度的必要基本变量。此外,还引入了两种表示矩阵密度的方法,利用非正交和正交轨道。在这两种表示中,都可以构建一个辅助态的多态活性空间,以精确表示 (),从而给出了哈密顿量矩阵泛函 的显式公式。重要的是,使用一组公共的正交轨道使得对辅助态进行单激发和双激发构型的多态自洽场优化(MS-SDSCF)成为可能。