Generating accurate density matrices on the tangent space of a Grassmann manifold

被引:3
|
作者
Tan, Jake A. [1 ]
Lao, Ka Un [1 ]
机构
[1] Virginia Commonwealth Univ, Dept Chem, Richmond, VA 23284 USA
来源
JOURNAL OF CHEMICAL PHYSICS | 2023年 / 158卷 / 05期
关键词
WAVE-FUNCTION; CONVERGENCE; ACCELERATION; FERROCENE; GEOMETRY; SYSTEMS;
D O I
10.1063/5.0137775
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Interpolating a density matrix from a set of known density matrices is not a trivial task. This is because a linear combination of density matrices does not necessarily correspond to another density matrix. In this Communication, density matrices are examined as objects of a Grassmann manifold. Although this manifold is not a vector space, its tangent space is a vector space. As a result, one can map the density matrices on this manifold to their corresponding vectors in the tangent space and then perform interpolations on that tangent space. The resulting interpolated vector can be mapped back to the Grassmann manifold, which can then be utilized (1) as an optimal initial guess for a self-consistent field (SCF) calculation or (2) to derive energy directly without time-consuming SCF iterations. Such a promising approach is denoted as Grassmann interpolation (G-Int). The hydrogen molecule has been used to illustrate that the described interpolated method in this work preserves the essential attributes of a density matrix. For phosphorus mononitride and ferrocene, it was demonstrated numerically that reference points for the definition of the corresponding tangent spaces can be chosen arbitrarily. In addition, the interpolated density matrices provide a superior and essentially converged initial guess for an SCF calculation to make the SCF procedure itself unnecessary. Finally, this accurate, efficient, robust, and systematically improved G-Int strategy has been used for the first time to generate highly accurate potential energy surfaces with fine details for the difficult case, ferrocene.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] TANGENT SPACE TO A CK MANIFOLD
    TAYLOR, LE
    BULLETIN OF THE AMERICAN MATHEMATICAL SOCIETY, 1973, 79 (04) : 746 - 746
  • [2] The space of linear maps into a Grassmann manifold
    Ben Hammouda, Walid
    Kallel, Sadok
    Salvatore, Paolo
    FORUM MATHEMATICUM, 2013, 25 (06) : 1181 - 1215
  • [3] TANGENT SPACE TO A CK MANIFOLD
    TAYLOR, LE
    NOTICES OF THE AMERICAN MATHEMATICAL SOCIETY, 1973, 20 (01): : A170 - A170
  • [4] Methods of density estimation on the Grassmann manifold
    Chikuse, Y
    LINEAR ALGEBRA AND ITS APPLICATIONS, 2002, 354 (1-3) : 85 - 102
  • [5] Representing the space of linear programs as the Grassmann manifold
    Zhao, Gongyun
    MATHEMATICAL PROGRAMMING, 2010, 121 (02) : 353 - 386
  • [6] Representing the space of linear programs as the Grassmann manifold
    Gongyun Zhao
    Mathematical Programming, 2010, 121 : 353 - 386
  • [7] Tangent-Bundle Maps on the Grassmann Manifold: Application to Empirical Arithmetic Averaging
    Fiori, Simone
    Kaneko, Tetsuya
    Tanaka, Toshihisa
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2015, 63 (01) : 155 - 168
  • [8] Stable Embedding of Grassmann Manifold via Gaussian Random Matrices
    Shi, Hailong
    Zhang, Hao
    Li, Gang
    Wang, Xiqin
    IEEE TRANSACTIONS ON INFORMATION THEORY, 2015, 61 (05) : 2924 - 2941
  • [9] Stable Grassmann Manifold Embedding via Gaussian Random Matrices
    Shi, Hailong
    Zhang, Hao
    Li, Gang
    Wang, Xiqin
    2014 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT), 2014, : 2629 - 2633
  • [10] TSBP: Tangent Space Belief Propagation for Manifold Learning
    Cohn, Thomas
    Jenkins, Odest Chadwicke
    Desingh, Karthik
    Zeng, Zhen
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2020, 5 (04) : 6694 - 6701