Ultra-weak least squares discretizations for unique continuation and Cauchy problems
<|reference_start|>Ultra-weak least squares discretizations for unique continuation and Cauchy problems: In this paper, conditional stability estimates are derived for unique continuation and Cauchy problems associated to the Poisson equation in ultra-weak variational form. Numerical approximations are obtained as minima of regularized least squares functionals. The arising dual norms are replaced by discretized dual norms, which leads to a mixed formulation in terms of trial- and test-spaces. For stable pairs of such spaces, and a proper choice of the regularization parameter, the $L_2$-error on a subdomain in the obtained numerical approximation can be bounded by the best possible fractional power of the sum of the data error and the error of best approximation. Compared to the use of a standard variational formulation, the latter two errors are measured in weaker norms. To avoid the use of $C^1$-finite element test spaces, nonconforming finite element test spaces can be applied as well. They either lead to the qualitatively same error bound, or in a simplified version, to such an error bound modulo an additional data oscillation term. Numerical results illustrate our theoretical findings.<|reference_end|>
@article{monsuur2024ultra-weak,
    title={Ultra-weak least squares discretizations for unique continuation and
  Cauchy problems},
    author={Harald Monsuur and Rob Stevenson},
    journal={arXiv preprint arXiv:2407.04571},
    year={2024},
    archivePrefix={arXiv},
    eprint={2407.04571},
    primaryClass={math.NA cs.NA}
}