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
504
<tt>emcee</tt>: The MCMC Hammer
Publications of the Astronomical Society of the Pacific · 2013 · 11.9K citations · Full text
Computing, Computer Science, Physics +14
Parallel tempering: Theory, applications, and new perspectives
Physical Chemistry Chemical Physics · 2005 · 1.3K citations · Full text
Computing, Computer Science, Physics +13
1–5 of 504
1.3K
6
h-index
6
h-index
5
h-index
5
h-index
5
h-index
1–5 of 1.3K
563
Los Alamos National Laboratory
Los Alamos, United States
13 h-index
23 publications
2K citations

Centre National de la Recherche Scientifique
Paris, France
10 h-index
35 publications
1.9K citations

University of Edinburgh
Edinburgh, United Kingdom
9 h-index
17 publications
1.1K citations
Massachusetts Institute of Technology
Cambridge, United States
8 h-index
25 publications
6.1K citations
University of Cambridge
Cambridge, United Kingdom
8 h-index
19 publications
3.9K citations

Imperial College London
London, United Kingdom
8 h-index
21 publications
939 citations
Harvard University
Cambridge, United States
8 h-index
15 publications
419 citations
University of Michigan
Ann Arbor, United States
8 h-index
16 publications
1.7K citations
1–8 of 563
22 publications · 1.1K citations
17
h-index
20 publications · 1.3K citations
16
h-index
Repository · 18 publications · 644 citations
12
h-index
13 publications · 442 citations
11
h-index
10 publications · 229 citations
10
h-index
1–5