The quantum Monte Carlo method - electron correlation from random numbers

被引:1
|
作者
Needs, Richard [1 ]
机构
[1] Univ Cambridge, Cavendish Lab, TCM Grp, Cambridge CB3 0HE, England
基金
英国工程与自然科学研究理事会;
关键词
D O I
10.1088/0953-8984/20/6/064204
中图分类号
O469 [凝聚态物理学];
学科分类号
070205 ;
摘要
The fixed-node diffusion quantum Monte Carlo (DMC) method is the most accurate method known for calculating the energies of large many-particle quantum systems. The key element of the method is the development of accurate trial many-body wavefunctions which control the statistical efficiency of the calculations and the accuracy obtained. Accurate wavefunctions can be obtained by building correlation effects on top of mean field descriptions such as density functional theory. The wavefunctions can be improved by introducing multi-determinants, pairing functions, and backflow transformations. The calculations are expensive, but the method scales well with system size and calculations on 1000 particles are possible. Some recent applications of the DMC method to atoms, molecules and solids will be presented.
引用
收藏
页数:1
相关论文
共 50 条
  • [31] A quantum Monte Carlo method for quantum Ising model
    Zhang, Q
    Gu, YW
    Wei, GZ
    PROCEEDINGS OF THE THIRD INTERNATIONAL SYMPOSIUM ON MAGNETIC INDUSTRY (ISMI'04) & FIRST INTERNATIONAL SYMPOSIUM ON PHYSICS AND IT INDUSTRY (ISITI'04), 2005, : 40 - 42
  • [32] CORRELATION-FUNCTION QUANTUM MONTE-CARLO
    BROWN, WR
    GLAUSER, WA
    LESTER, WA
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 1992, 203 : 252 - PHYS
  • [33] A Monte Carlo Method for Estimating the Correlation Exponent
    Mikosch, T.
    Wang, Q.
    Journal of Inorganic and Organometallic Polymers, 1994, 48 (4-4):
  • [34] Random numbers for large-scale distributed Monte Carlo simulations
    Bauke, Heiko
    Mertens, Stephan
    PHYSICAL REVIEW E, 2007, 75 (06)
  • [35] THE USE OF NON-RANDOM NUMBERS IN MONTE-CARLO SIMULATION
    SCULLI, D
    STATISTICIAN, 1981, 30 (02): : 143 - 151
  • [36] Quantum Monte Carlo investigation of exchange and correlation in silicon
    Hood, RQ
    Chou, MY
    Williamson, AJ
    Rajagopal, G
    Needs, RJ
    Foulkes, WMC
    PHYSICAL REVIEW LETTERS, 1997, 78 (17) : 3350 - 3353
  • [37] MONTE CARLO LEARNING/BIASING EXPERIMENT WITH INTELLIGENT RANDOM NUMBERS.
    Booth, Thomas E.
    Nuclear Science and Engineering, 1986, 92 (03): : 465 - 481
  • [38] QUASI-MONTE CARLO METHODS AND PSEUDO-RANDOM NUMBERS
    NIEDERREITER, H
    BULLETIN OF THE AMERICAN MATHEMATICAL SOCIETY, 1978, 84 (06) : 957 - 1041
  • [39] Correlation properties of FeAs-based superconductors: Quantum trajectory Monte Carlo method
    Kashurnikov, V. A.
    Krasavin, A. V.
    JETP LETTERS, 2014, 100 (01) : 16 - 23
  • [40] Correlation properties of FeAs-based superconductors: Quantum trajectory Monte Carlo method
    V. A. Kashurnikov
    A. V. Krasavin
    JETP Letters, 2014, 100 : 16 - 23