eigentools: A Python package for studying differential eigenvalue problems with an emphasis on robustness

Python Submitted 14 January 2021 • Published 23 June 2021
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Authors

Jeffrey S. Oishi (0000-0001-8531-6570), Keaton J. Burns (0000-0003-4761-4766), S. E. Clark (0000-0002-7633-3376), Evan H. Anders (0000-0002-3433-4733), Benjamin P. Brown (0000-0001-8935-219X), Geoffrey M. Vasil (0000-0002-8902-5030), Daniel Lecoanet (0000-0002-7635-9728)

Citation

Oishi et al., (2021). eigentools: A Python package for studying differential eigenvalue problems with an emphasis on robustness. Journal of Open Source Software, 6(62), 3079, https://doi.org/10.21105/joss.03079

@article{Oishi2021, doi = {10.21105/joss.03079}, url = {https://doi.org/10.21105/joss.03079}, year = {2021}, publisher = {The Open Journal}, volume = {6}, number = {62}, pages = {3079}, author = {Jeffrey S. Oishi and Keaton J. Burns and S. E. Clark and Evan H. Anders and Benjamin P. Brown and Geoffrey M. Vasil and Daniel Lecoanet}, title = {eigentools: A Python package for studying differential eigenvalue problems with an emphasis on robustness}, journal = {Journal of Open Source Software} }
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eigenvalue problems partial differential equations fluid dynamics magnetohydrodynamics pseudospectra

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