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mikaem committed Jun 25, 2024
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Expand Up @@ -45,6 +45,19 @@ Shenfun can also be used to approximate analytical functions with global spectra
.. image:: https://cdn.jsdelivr.net/gh/spectralDNS/spectralutilities@master/figures/seashell3.png
:alt: The surface of a seashell

Some recent papers using Shenfun
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- `Effective control of two-dimensional Rayleigh–Bénard convection: Invariant multi-agent reinforcement learning is all you need <https://pubs.aip.org/aip/pof/article/35/6/065146/2900730>`_ C. Vignon, J. Rabault, J. Vasanth, F. Alcántara-Ávila, M. Mortensen, R. Vinuesa, Physics of Fluids 35, 065146 (2023)
- `Solving Partial Differential Equations with Equivariant Extreme Learning Machines <https://www.researchgate.net/profile/Sebastian-Peitz/publication/380897446_Solving_Partial_Differential_Equations_with_Equivariant_Extreme_Learning_Machines/links/66544d0fbc86444c7205cbdb/Solving-Partial-Differential-Equations-with-Equivariant-Extreme-Learning-Machines.pdf>`_, H. Harder, J. Rabault, R. Vinuesa, M. Mortensen, S. Peitz. preprint (2024)
- `A global spectral-Galerkin investigation of a Rayleigh–Taylor instability in plasma using an MHD–Boussinesq model <https://pubs.aip.org/aip/adv/article/13/10/105319/2917415>`_ A. Piterskaya, Wojciech J. Miloch, M. Mortensen, AIP Advances 13, 105319 (2023)
- `A Generic and Strictly Banded Spectral Petrov–Galerkin Method for Differential Equations with Polynomial Coefficients <https://epubs.siam.org/doi/full/10.1137/22M1492842>`_ M. Mortensen, SIAM J. on Scientific Computing, 45, 1, A123-A146, (2023)
- `Variance representations and convergence rates for data-driven approximations of Koopman operators <https://arxiv.org/abs/2402.02494>`_ F. M. Philipp, M. Schaller, S. Boshoff, S. Peitz, F. Nüske, K. Worthmann, preprint (2024)
- `Partial observations, coarse graining and equivariance in Koopman operator theory for large-scale dynamical systems <https://arxiv.org/abs/2307.15325>`_, S. Peitz, H. Harder, F. Nüske, F. Philipp, M. Schaller, K. Worthmann, preprint (2024)
- `Koopman-Based Surrogate Modelling of Turbulent Rayleigh-Bénard Convection <https://arxiv.org/abs/2405.06425>`_ T. Markmann, M. Straat, B. Hammer, preprint (2024)
- `Shenfun: High performance spectral Galerkin computing platform <https://joss.theoj.org/papers/10.21105/joss.01071.pdf>`_, M. Mortensen, Journal of Open Source Software, 3(31), 1071 (2018)


Installation
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