RLumCarlo: Simulating Cold Light using Monte Carlo Methods

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.

Sebastian Kreutzer , Johannes Friedrich , Vasilis Pagonis , Christian Laag , Ena Rajovic , Christoph Schmidt

CRAN packages used

RLumCarlo, BayLum, Luminescence, numOSL, RLumModel, RLumShiny, tgcd, scales, ggplot2, Rcpp, parallel, doParallel, foreach

CRAN Task Views implied by cited packages

HighPerformanceComputing, Graphics, NumericalMathematics, Phylogenetics, TeachingStatistics


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For attribution, please cite this work as

Kreutzer, et al., "The R Journal: RLumCarlo: Simulating Cold Light using Monte Carlo Methods", {The R Journal}, 2020

BibTeX citation

  author = {Kreutzer, Sebastian and Friedrich, Johannes and Pagonis, Vasilis and Laag, Christian and Rajovic, Ena and Schmidt, Christoph},
  title = {The R Journal: RLumCarlo: Simulating Cold Light using Monte Carlo Methods},
  journal = {{The R Journal}},
  year = {2020},
  note = {https://doi.org/10.32614/RJ-2021-043},
  doi = {10.32614/RJ-2021-043},
  volume = {13},
  issue = {1},
  issn = {2073-4859},
  pages = {351-365}