Langevin Diffusion Samplers with a C++ Backend R package LangevinFlow version 0.1.0 Provides lightweight, dependency-minimal implementations of Langevin diffusion based Markov chain Monte Carlo samplers, including the Unadjusted Langevin Algorithm (ULA) and the Metropolis-Adjusted Langevin Algorithm (MALA). The core sampling loops are written in C++ via 'Rcpp' and 'RcppArmadillo' for performance, while exposing a simple R-level interface where the user supplies the gradient of the negative log-density (and, for MALA, the negative log-density itself). Intended as a building block for Bayesian inference and stochastic optimization rather than a full probabilistic programming framework. Methods follow Roberts and Tweedie (1996) <doi:10.2307/3318418> and Roberts and Rosenthal (1998) <doi:10.1111/1467-9868.00123>. Software Depends: R (>= 3.5.0) Imports: Rcpp (>= 1.0.0), stats, graphics LinkingTo: Rcpp, RcppArmadillo Suggests: testthat (>= 3.0.0), knitr, rmarkdown, covr Behrooz Moosavi <bem159@pitt.edu> Comprehensive R Archive Network (CRAN) Behrooz Moosavi [aut, cre] (ORCID: <https://orcid.org/0000-0003-4378-3167>) MIT + file LICENSE (https://CRAN.R-project.org/package=LangevinFlow/LICENSE) 2026-05-29 application/tgz https://CRAN.R-project.org/package=LangevinFlow doi:10.32614/CRAN.package.LangevinFlow