The R Journal: article published in 2021, volume 13:1

RLumCarlo: Simulating Cold Light using Monte Carlo Methods PDF download
Sebastian Kreutzer, Johannes Friedrich, Vasilis Pagonis, Christian Laag, Ena Rajovic and Christoph Schmidt , The R Journal (2021) 13:1, pages 351-365.

Abstract The luminescence phenomena of insulators and semiconductors (e.g., natural minerals such as quartz) have various application domains. For instance, Earth Sciences and archaeology exploit luminescence as a dating method. Herein, we present the R package RLumCarlo implementing sets of luminescence models to be simulated with Monte Carlo (MC) methods. MC methods make a powerful ally to all kinds of simulation attempts involving stochastic processes. Luminescence production is such a stochastic process in the form of charge (electron-hole pairs) interaction within insulators and semiconductors. To simulate luminescence-signal curves, we distribute single and independent MC processes to virtual MC clusters. RLumCarlo comes with a modularized design and consistent user interface: (1) C++ functions represent the modeling core and implement models for specific stimulations modes. (2) R functions give access to combinations of models and stimulation modes, start the simulation and render terminal and graphical feedback. The combination of MC clusters supports the simulation of complex luminescence phenomena.

Received: 2020-07-06; online 2021-06-07, supplementary material, (2.4 Kb)
CRAN packages: RLumCarlo, BayLum, Luminescence, numOSL, RLumModel, RLumShiny, tgcd, scales, ggplot2, Rcpp, parallel, doParallel, foreach
CRAN Task Views implied by cited CRAN packages: HighPerformanceComputing, Graphics, NumericalMathematics, Phylogenetics, TeachingStatistics


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@article{RJ-2021-043,
  author = {Sebastian Kreutzer and Johannes Friedrich and Vasilis
          Pagonis and Christian Laag and Ena Rajovic and
          Christoph Schmidt},
  title = {{RLumCarlo: Simulating Cold Light using Monte Carlo Methods}},
  year = {2021},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2021-043},
  url = {https://doi.org/10.32614/RJ-2021-043},
  pages = {351--365},
  volume = {13},
  number = {1}
}