Multicanonical Sampling

Multicanonical Sampling is a Markov chain Monte Carlo method that belongs to the class of importance sampling techniques, distinguished by its use of a flat energy histogram prescription to enable uniform sampling across energy states and overcome barriers in systems with rugged energy landscapes.

78

Publications

5.2K

Citations

163

Authors

95

Institutions

Publications per year

2017–2026

5

Variants

MucaMulticanonical Monte Carlo

Authors

163

  1. DY
    David Yevick

    University of Waterloo, Canada

    8 publications · 196 citations

    8

    h-index

  2. YO
    Yuko Okamoto

    Institute for Molecular Science, Japan

    6 publications · 560 citations

    6

    h-index

  3. UH
    Ulrich H. E. Hansmann

    Michigan Technological University, United States

    6 publications · 568 citations

    6

    h-index

  4. HN
    Haruki Nakamura

    The University of Osaka, Japan

    6 publications · 625 citations

    6

    h-index

  5. BA
    Bernd A. Berg

    Florida State University, United States

    5 publications · 141 citations

    5

    h-index

1–5 of 163

Venues

  1. The Journal of Chemical Physics

    19 publications · 1.1K citations

    15

    h-index

  2. IEEE Photonics Technology Letters

    IPTEL · 7 publications · 181 citations

    7

    h-index

  3. Journal of Computational Chemistry

    6 publications · 322 citations

    6

    h-index

  4. Physical Review E

    PRE · 6 publications · 208 citations

    6

    h-index

  5. 4

    h-index

1–5