Visualizing Molecular Wavefunctions Using Monte Carlo Methods

被引:5
|
作者
Alexander, S. A. [1 ]
Coldwell, R. L. [2 ]
机构
[1] Southwestern Univ, Dept Phys, Georgetown, TX 78626 USA
[2] Univ Florida, Dept Phys, Gainesville, FL 32611 USA
关键词
intracule density; extracule density; electron density; Laplacians; EXTRACULE DENSITY DISTRIBUTIONS; HYDROGEN MOLECULE; GROUND-STATE; INTRACULE; SYSTEMS; LOCALIZATION; LAPLACIAN;
D O I
10.1002/qua.21774
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
Using explicitly correlated wavefunctions and variational Monte Carlo we calculate the electron density, the electron density difference, the intracule density, the extracule density, two forms of the kinetic energy I density, the Laplacian of the electron density, the Laplacian of the intracule density, and the Laplacian of the extracule density on a dense grid of points for the ground state of the hydrogen molecule at three internuclear distances (0.6, 1.4, 8.0). With these values we construct a contour plot of each function and describe how it can be used to Visualize the distribution of electrons in this molecule. We also examine the influence of electron correlation on each expectation value by calculating each function with a Hartree-Fock wavefunction and then comparing these values With Our explicitly correlated values. (C) 2008 Wiley Periodicals, Inc. Int J Quantum Chem 109: 385-400, 2009
引用
下载
收藏
页码:385 / 400
页数:16
相关论文
共 50 条
  • [31] Using the approximation functional bases in Monte Carlo methods
    Voytishek, AV
    Kablukova, EG
    RUSSIAN JOURNAL OF NUMERICAL ANALYSIS AND MATHEMATICAL MODELLING, 2003, 18 (06) : 521 - 542
  • [32] Nonlinear and nonnormal filters using Monte Carlo methods
    Tanizaki, H
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 1997, 25 (04) : 417 - 439
  • [33] Inverse kinematics using sequential Monte Carlo methods
    Courty, Nicolas
    Arnaud, Elise
    ARTICULATED MOTION AND DEFORMABLE OBJECTS, PROCEEDINGS, 2008, 5098 : 1 - +
  • [34] Extended object tracking using Monte Carlo methods
    Angelova, Donka
    Mihaylova, Lyudmila
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2008, 56 (02) : 825 - 832
  • [35] Tomographic reconstruction using heuristic Monte Carlo methods
    R. Barbuzza
    M. Vénere
    A. Clausse
    Journal of Heuristics, 2007, 13 : 227 - 242
  • [36] Reconstruction of random media using Monte Carlo methods
    Manwart, C.
    Hilfer, R.
    Physical Review E. Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics, 1999, 59 (5 pt B):
  • [37] Discrete range clustering using Monte Carlo methods
    Chatterji, GB
    Sridhar, B
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS, 1996, 26 (06): : 832 - 837
  • [38] Modelling dynamic accessories using Monte Carlo methods
    Siljamaeki, S.
    Tillikainen, L.
    Helminen, H.
    Pesola, K.
    Frei, D.
    Volken, W.
    RADIOTHERAPY AND ONCOLOGY, 2006, 81 : S83 - S84
  • [39] Analysis of magnetic aftereffect by using Monte Carlo methods
    Andrei, Petru
    Adedoyin, Ayodeji
    MATHEMATICS AND COMPUTERS IN SIMULATION, 2010, 80 (06) : 1045 - 1055
  • [40] Bayesian Geosteering Using Sequential Monte Carlo Methods
    Veettil, Dilshad R. Akkam
    Clark, Kit
    PETROPHYSICS, 2020, 61 (01): : 99 - 111