PyTurbo_SF: An Adaptive Bootstrap Framework for Efficient Structure Function Analysis in Turbulent Flows

Jupyter Notebook Python Submitted 01 October 2025 • Published 10 April 2026
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Authors

Adam Ayouche (0009-0001-9075-5911), Baylor Fox-Kemper (0000-0002-2871-2048), Momme Hell (0000-0002-5754-3925), Brodie Pearson (0000-0002-0202-0481), Cassidy Wagner (0000-0002-1186-2082)

Citation

Ayouche et al., (2026). PyTurbo_SF: An Adaptive Bootstrap Framework for Efficient Structure Function Analysis in Turbulent Flows. Journal of Open Source Software, 11(120), 9876, https://doi.org/10.21105/joss.09876

@article{Ayouche2026, doi = {10.21105/joss.09876}, url = {https://doi.org/10.21105/joss.09876}, year = {2026}, publisher = {The Open Journal}, volume = {11}, number = {120}, pages = {9876}, author = {Ayouche, Adam and Fox-Kemper, Baylor and Hell, Momme and Pearson, Brodie and Wagner, Cassidy}, title = {PyTurbo_SF: An Adaptive Bootstrap Framework for Efficient Structure Function Analysis in Turbulent Flows}, journal = {Journal of Open Source Software} }
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turbulence structure functions fluid dynamics bootstrap statistics oceanography atmospheric science energy cascade geophysical flows

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

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ISSN 2475-9066