QMCPy: A Python Framework for (Quasi-)Monte Carlo Algorithms

Python C Submitted 20 November 2025 • Published 19 January 2026
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Authors

Aleksei G. Sorokin (0000-0003-1004-4632), Fred J. Hickernell (0000-0001-6677-1324), Sou-Cheng T. Choi (0000-0002-6190-2986), Jagadeeswaran Rathinavel (0009-0005-6753-4589), Pieterjan Robbe (0000-0002-6254-8245), Aadit Jain (0009-0002-4805-3665)

Citation

Sorokin et al., (2026). QMCPy: A Python Framework for (Quasi-)Monte Carlo Algorithms. Journal of Open Source Software, 11(117), 9705, https://doi.org/10.21105/joss.09705

@article{Sorokin2026, doi = {10.21105/joss.09705}, url = {https://doi.org/10.21105/joss.09705}, year = {2026}, publisher = {The Open Journal}, volume = {11}, number = {117}, pages = {9705}, author = {Sorokin, Aleksei G. and Hickernell, Fred J. and Choi, Sou-Cheng T. and Rathinavel, Jagadeeswaran and Robbe, Pieterjan and Jain, Aadit}, title = {QMCPy: A Python Framework for (Quasi-)Monte Carlo Algorithms}, journal = {Journal of Open Source Software} }
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(quasi-)Monte Carlo numerical integration randomized low-discrepancy sequences automatic error estimation object oriented Python framework

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Journal of Open Source Software is part of Open Journals, which is a NumFOCUS-sponsored project.

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