Error estimates for SUPG-stabilised Dynamical Low Rank Approximations
<|reference_start|>Error estimates for SUPG-stabilised Dynamical Low Rank Approximations: We perform an error analysis of a fully discretised Streamline Upwind Petrov Galerkin Dynamical Low Rank (SUPG-DLR) method for random time-dependent advection-dominated problems. The time integration scheme has a splitting-like nature, allowing for potentially efficient computations of the factors characterising the discretised random field. The method allows to efficiently compute a low-rank approximation of the true solution, while naturally "inbuilding" the SUPG stabilisation. Standard error rates in the L2 and SUPG-norms are recovered. Numerical experiments validate the predicted rates.<|reference_end|>
@article{nobile2024error,
    title={Error estimates for SUPG-stabilised Dynamical Low Rank Approximations},
    author={Fabio Nobile and Thomas Trigo Trindade},
    journal={arXiv preprint arXiv:2402.03586},
    year={2024},
    archivePrefix={arXiv},
    eprint={2402.03586},
    primaryClass={math.NA cs.NA}
}