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
收藏
页码:385 / 400
页数:16
相关论文
共 50 条
  • [31] Uncertainty Quantification for the BGK Model of the Boltzmann Equation Using Multilevel Variance Reduced Monte Carlo Methods
    Hu, Jingwei
    Pareschi, Lorenzo
    Wang, Yubo
    SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 2021, 9 (02) : 650 - 680
  • [32] Uncertainty quantification analysis and statistical estimation for LBLOCA in a PWR using Monte-Carlo and alternative methods
    Kang, Dong Gu
    ANNALS OF NUCLEAR ENERGY, 2021, 150
  • [33] Modeling and simulations of multicellular aggregate self-assembly in biofabrication using kinetic Monte Carlo methods
    Sun, Yi
    Wang, Qi
    SOFT MATTER, 2013, 9 (07) : 2172 - 2186
  • [34] ELECTRONIC STRUCTURE QUANTUM MONTE CARLO
    Bajdich, Michal
    Mitas, Lubos
    ACTA PHYSICA SLOVACA, 2009, 59 (02) : 81 - 168
  • [35] Combining tensor networks with Monte Carlo methods for lattice gauge theories
    Zohar, Erez
    Cirac, J. Ignacio
    PHYSICAL REVIEW D, 2018, 97 (03)
  • [36] Multiparameter estimation along quantum trajectories with sequential Monte Carlo methods
    Ralph, Jason F.
    Maskell, Simon
    Jacobs, Kurt
    PHYSICAL REVIEW A, 2017, 96 (05)
  • [37] Pairing in Cold Atoms and other Applications for Quantum Monte Carlo methods
    Bajdich, M.
    Kolorenc, J.
    Mitas, L.
    Reynolds, P. J.
    PROCEEDINGS OF THE 22TH WORKSHOP ON COMPUTER SIMULATION STUDIES IN CONDENSED MATTER PHYSICS (CSP 2009), 2010, 3 (03): : 1397 - 1410
  • [38] Monte Carlo Filtering Using Kernel Embedding of Distributions
    Kanagawa, Motonobu
    Nishiyama, Yu
    Gretton, Arthur
    Fukumizu, Kenji
    PROCEEDINGS OF THE TWENTY-EIGHTH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2014, : 1897 - 1903
  • [39] Variational path integral molecular dynamics and hybrid Monte Carlo algorithms using a fourth order propagator with applications to molecular systems
    Kamibayashi, Yuki
    Miura, Shinichi
    JOURNAL OF CHEMICAL PHYSICS, 2016, 145 (07)
  • [40] Quantum Monte Carlo applied to solids
    Shulenburger, Luke
    Mattsson, Thomas R.
    PHYSICAL REVIEW B, 2013, 88 (24):