Wang-landau Sampling

Wang-Landau Sampling is a Monte Carlo method that iteratively refines the estimation of the density of states by adaptively modifying the energy histogram weights to achieve a flat energy sampling distribution, thereby enabling accurate computation of thermodynamic properties in complex systems.

174

Publications

8.6K

Citations

304

Authors

181

Institutions

Publications per year

2017–2026

18

Variants

Wang-landau Algorithm

Authors

304

  1. DP
    D. P. Landau

    University of Georgia, United States

    17 publications · 1.2K citations

    15

    h-index

  2. TW
    Thomas Wüst

    University of Georgia, United States

    11 publications · 569 citations

    11

    h-index

  3. JD
    Jérôme Delhommelle

    University of North Dakota, United States

    8 publications · 280 citations

    9

    h-index

  4. CD
    Caroline Desgranges

    University of North Dakota, United States

    8 publications · 280 citations

    9

    h-index

  5. NG
    Nikolaos G. Fytas

    Coventry University, United Kingdom

    7 publications · 260 citations

    7

    h-index

1–5 of 304

Venues

  1. Physical Review E

    PRE · 38 publications · 2K citations

    24

    h-index

  2. The Journal of Chemical Physics

    26 publications · 1.3K citations

    20

    h-index

  3. Physical Review Letters

    PRL · 14 publications · 1.5K citations

    14

    h-index

  4. Computer Physics Communications

    8 publications · 262 citations

    8

    h-index

  5. Physical review. E

    PRE · 6 publications · 84 citations

    6

    h-index

1–5