Parallel Monte Carlo Algorithms

Parallel Monte Carlo Algorithms is a computational methodology that belongs to the class of Monte Carlo methods, distinguished by its explicit decomposition of stochastic sampling tasks into concurrently executable subproblems to leverage parallel hardware architectures for accelerated convergence and solution estimation.

504

Publications

37.7K

Citations

1.3K

Authors

563

Institutions

Publications per year

2017–2026

99

Authors

1.3K

  1. PR
    Paul Romano

    Argonne National Laboratory, United States

    6 publications · 1.2K citations

    6

    h-index

  2. ID
    Ivan Dimov

    Bulgarian Academy of Sciences, Bulgaria

    6 publications · 144 citations

    6

    h-index

  3. AK
    Aneta Karaivanova

    Bulgarian Academy of Sciences, Bulgaria

    5 publications · 112 citations

    5

    h-index

  4. PJ
    Pierre Jacob

    Harvard University Press, United States

    5 publications · 404 citations

    5

    h-index

  5. BF
    Benoit Forget

    Massachusetts Institute of Technology, United States

    5 publications · 1.2K citations

    5

    h-index

1–5 of 1.3K

Venues

  1. Computer Physics Communications

    22 publications · 1.1K citations

    17

    h-index

  2. Journal of Computational Physics

    20 publications · 1.3K citations

    16

    h-index

  3. arXiv (Cornell University)

    Repository · 18 publications · 644 citations

    12

    h-index

  4. The Journal of Chemical Physics

    13 publications · 442 citations

    11

    h-index

  5. Parallel Computing

    10 publications · 229 citations

    10

    h-index

1–5