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Professur Numerische Mathematik
Publications
Professur Numerische Mathematik 
Oliver Ernst publications

Refereed Journal Articles

[1] O. G. Ernst, B. Sprungk, and C. Zhang, “Uncertainty modeling and propagation for groundwater flow: A comparative study of surrogates,” International Journal on Geomathematics, vol. 15, no. 1, Article 11, 2024. [ bib | DOI | pdf ]
[2] K. Kurgyis, P. Achtziger-Zupančič, M. Bjorge, M. S. Boxberg, M. Broggi, J. Buchwald, O. G. Ernst, J. Flügge, A. Ganopolski, T. Graf, P. Kortenbruck, J. Kowalski, P. Kreye, P. Kukla, S. Mayr, S. Miro, T. Nagel, W. Nowak, S. Oladyshkin, A. Renz, J. Rienäcker-Burschil, K.-J. Röhlig, O. Sträter, J. Thiedau, F. Wagner, F. Wellmann, M. Wengler, J. Wolf, and W. Rühaak, “Uncertainties and robustness with regard to the safety of a repository for high-level radioactive waste: introduction of a research initiative,” Environmental Earth Sciences, vol. 83, no. 2, p. 82, 2024. [ bib | DOI | pdf ]
[3] J. Blechta and O. G. Ernst, “Efficient solution of parameter identification problems with H1 regularization,” SIAM Journal on Scientific Computing, vol. 46, no. 2, pp. A1160-A1185, 2024. [ bib | DOI | pdf ]
[4] O. G. Ernst, A. Pichler, and B. Sprungk, “Wasserstein sensitivity of risk and uncertainty propagation,” SIAM/ASA Journal on Uncertainty Quantification, vol. 10, no. 3, pp. 915-948, 2022. [ bib | DOI | pdf ]
[5] M. Eigel, O. G. Ernst, B. Sprungk, and L. Tamellini, “On the convergence of adaptive stochastic collocation for elliptic partial differential equations with affine diffusion,” SIAM Journal on Numerical Analysis, vol. 60, no. 2, pp. 659-687, 2022. [ bib | DOI | pdf ]
[6] J. Blechschmidt and O. G. Ernst, “Three ways to solve partial differential equations with neural networks: a review,” GAMM Mitteilungen, vol. 44, no. 2, p. e202100006, 2021. [ bib | DOI | pdf ]
[7] D. Gerth, S. Hannusch, O. G. Ernst, and J. Ihlemann, “Regularization for the inversion of fibre Bragg grating spectra,” Inverse Problems in Science and Engineering, vol. 29, no. 13, pp. 2629-2655, 2021. [ bib | DOI | pdf ]
[8] O. G. Ernst, B. Sprungk, and L. Tamellini, “Convergence of sparse collocation for functions of countably many Gaussian random variables (with application to elliptic PDEs),” SIAM Journal on Numerical Analysis, vol. 56, no. 2, pp. 877-905, 2018. [ bib | DOI | pdf ]
[9] O. G. Ernst, B. Sprungk, and H.-J. Starkloff, “Analysis of the ensemble and polynomial chaos Kalman filters in Bayesian inverse problems,” SIAM/ASA Journal on Uncertainty Quantification, vol. 3, no. 1, pp. 823-851, 2015. [ bib | DOI | pdf ]
[10] R.-U. Börner, O. G. Ernst, and S. Güttel, “Three-dimensional transient electromagnetic modelling using rational Krylov methods,” Geophysical Journal International, vol. 202, pp. 2025-2043, 2015. [ bib | DOI | pdf ]
[11] M. Ullmann, U. Prüfert, J. Seidel, O. G. Ernst, and C. Hasse, “Application of proper orthogonal decomposition methods in reactive pore diffusion simulations,” Canadian Journal of Chemical Engineering, vol. 92, no. 9, pp. 1552-1560, 2014. [ bib | DOI | pdf ]
[12] J. Seidel and O. G. Ernst, “Model reduction for cold rolling processes,” Steel Research, vol. 85, no. 9, pp. 1334-1339, 2014. [ bib | DOI | pdf ]
[13] H. C. Elman, O. G. Ernst, and E. Ullmann, “Efficient iterative solvers for stochastic Galerkin discretizations of log-transformed random diffusion problems,” SIAM Journal on Scientific Computing, vol. 34, no. 2, pp. A659-A682, 2012. [ bib | DOI | pdf ]
[14] O. G. Ernst, A. Mugler, H.-J. Starkloff, and E. Ullmann, “On the convergence of generalized polynomial chaos expansions,” M2AN, vol. 46, no. 2, pp. 317-339, 2012. [ bib | DOI | pdf ]
[15] I. Busch, O. G. Ernst, and E. Ullmann, “Expansion of random field gradients using hierarchical matrices,” PAMM, vol. 11, no. 1, pp. 911-914, 2011. [ bib | pdf ]
[16] M. Eiermann, O. G. Ernst, and S. Güttel, “Deflated restarting for matrix functions,” SIAM Journal on Matrix Analysis and Applications, vol. 32, no. 2, pp. 621-641, 2011. [ bib | DOI | pdf ]
[17] O. G. Ernst and E. Ullmann, “Stochastic Galerkin matrices,” SIAM Journal on Matrix Analysis and Applications, vol. 31, no. 4, pp. 1848-1872, 2010. [ bib | DOI | pdf ]
[18] O. G. Ernst, C. E. Powell, D. Silvester, and E. Ullmann, “Efficient solvers for a linear stochastic Galerkin mixed formulation of diffusion problems with random data,” SIAM Journal on Scientific Computing, vol. 31, no. 2, pp. 1424-1447, 2009. [ bib | DOI | pdf ]
[19] M. Afanasjew, M. Eiermann, O. G. Ernst, and S. Güttel, “A generalization of the steepest descent method for matrix functions,” Electronic Transactions on Numerical Analysis, vol. 28, pp. 206-222, 2008. [ bib | pdf ]
[20] M. Afanasjew, M. Eiermann, O. G. Ernst, and S. Güttel, “Implementation of a restarted Krylov subspace method for the evaluation of matrix functions,” Linear Algebra and its Applications, vol. 429, no. 10, pp. 2293-2314, 2008. [ bib | DOI | pdf ]
[21] R.-U. Börner, O. G. Ernst, and K. Spitzer, “Fast 3d simulation of transient electromagnetic fields by model reduction in the frequency domain using Krylov subspace projection,” Geophysical Journal International, vol. 173, pp. 766-780, 2008. [ bib | DOI | pdf ]
[22] M. Eiermann, O. G. Ernst, and E. Ullmann, “Computational aspects of the stochastic finite element method,” Computing and Visualization in Science, vol. 10, no. 1, pp. 3-15, 2007. [ bib | DOI | pdf ]
[23] M. Eiermann and O. G. Ernst, “A restarted Krylov subspace method for the evaluation of matrix functions,” SIAM Journal on Numerical Analysis, vol. 44, no. 6, pp. 2481-2504, 2006. [ bib | DOI | pdf ]
[24] H. C. Elman, O. G. Ernst, D. P. O'Leary, and M. Stewart, “Efficient iterative algorithms for the stochastic finite element method with applications to acoustic scattering,” Computer Methods in Applied Mechanics and Engineering, vol. 194, pp. 1037-1055, 2005. [ bib | DOI | pdf ]
[25] H. C. Elman, O. G. Ernst, and D. P. O'Leary, “A multigrid method enhanced by Krylov subspace iteration for discrete Helmholtz equations,” SIAM Journal on Scientific Computing, vol. 23, no. 4, pp. 1290-1314, 2001. [ bib | DOI | pdf ]
[26] M. Eiermann and O. G. Ernst, “Geometric aspects of the theory of Krylov subspace methods,” Acta Numerica, vol. 10, pp. 251-312, 2001. [ bib | DOI | pdf ]
[27] O. G. Ernst, “Equivalent iterative methods for p-cyclic matrices,” Numerical Algorithms, vol. 25, pp. 161-180, 2000. [ bib | DOI | pdf ]
[28] M. Eiermann, O. G. Ernst, and O. Schneider, “Analysis of acceleration strategies for restarted minimal residual methods,” Journal of Computational and Applied Mathematics, vol. 123, pp. 262-292, 2000. [ bib | DOI | pdf ]
[29] O. G. Ernst, “Residual-minimizing Krylov subspace methods for stabilized discretizations of convection-diffusion equations,” SIAM Journal on Matrix Analysis and Applications, vol. 21, no. 4, pp. 1079-1101, 2000. [ bib | DOI | pdf ]
[30] O. G. Ernst, “A finite element capacitance matrix method for exterior Helmholtz problems,” Numerische Mathematik, vol. 75, no. 2, pp. 175-204, 1996. [ bib | DOI | pdf ]

Refereed Book Chapters

[1] O. G. Ernst, B. Sprungk, and L. Tamellini, “On expansions and nodes for sparse grid collocation of lognormal elliptic PDEs,” in Sparse Grids and Applications - Munich 2018 (H.-J. Bungartz, J. Garcke, and D. Pflüger, eds.), vol. 144 of LNCSE, pp. 1-31, Cham: Springer International Publishing, 2021. [ bib | DOI | pdf ]
[2] O. G. Ernst, B. Sprungk, and H.-J. Starkloff, “Bayesian inverse problems and Kalman filters,” in Extraction of Quantifiable Information from Complex Systems (S. e. a. Dahlke, ed.), vol. 102 of Lecture Notes in Computational Science and Engineering, pp. 133-159, Springer-Verlag, 2014. [ bib | DOI | pdf ]
[3] O. G. Ernst and B. Sprungk, “Stochastic collocation for elliptic PDEs with random data - the lognormal case,” in Sparse Grids and Applications - Munich 2012 (J. Garcke and D. Pflüger, eds.), vol. 97 of Lecture Notes in Computational Science and Engineering, pp. 29-53, Springer-Verlag, 2014. [ bib | DOI | pdf ]
[4] O. G. Ernst and M. J. Gander, “Multigrid methods for Helmholtz problems: A convergent scheme in 1D using standard components,” in Direct and Inverse Problems in Wave Propagation and Applications (I. G. Graham, U. Langer, J. M. Melenk, and M. Sini, eds.), vol. 14 of Radon Series on Computational and Applied Mathematics, Berlin/Boston: Walter de Gruyter GmbH, 2013. [ bib | pdf ]
[5] O. G. Ernst and M. J. Gander, “Why it is difficult to solve Helmholtz problems with classical iterative methods,” in Numerical Analysis of Multiscale Problems (I. Graham, T. Hou, O. Lakkis, and R. Scheichl, eds.), vol. 83 of Lecture Notes in Computational Science and Engineering, (Berlin Heidelberg), pp. 325-361, Springer-Verlag, 2012. [ bib | DOI | pdf ]
[6] H. C. Elman and O. G. Ernst, “Numerical experiences with a Krylov-enhanced multigrid solver for exterior Helmholtz problems,” in Proceedings of the Fifth International Conference on Mathematical and Numerical Aspects of Wave Propagation, Waves 2000 (Santiago de Compostela) (A. Bermúdez, D. Gómez, C. Hazard, P. Joly, and J. E. Roberts, eds.), (Philadelphia), SIAM, 2000. [ bib ]
[7] O. G. Ernst and G. H. Golub, A Domain Decomposition Approach to Solving the Helmholtz Equation with a Radiation Boundary Condition, vol. 157 of Contemporary Mathematics. AMS, 1992. [ bib | pdf ]

Theses

[1] O. G. Ernst, “Minimal and orthogonal residual methods and their generalizations for solving linear operator equations.” Habilitation Thesis, TU Bergakademie Freiberg, 2001. [ bib | pdf ]
[2] O. G. Ernst, “Fast numerical solution of exterior Helmholtz problems with radiation boundary condition by imbedding.” PhD thesis, Stanford University, 1994. [ bib | pdf ]
[3] O. G. Ernst, “Über einige Anwendungen komplexer Orthogonalpolynome in der Numerik.” Diplomarbeit, Institut für Praktische Mathematik, Universität Karlsruhe, 1989. [ bib ]

Other (not refereed or for non-specialists)

[1] O. G. Ernst, F. Nobile, C. Schillings, and T. Sullivan, “Uncertainty quantification,” Oberwolfach Reports, vol. 16, no. 1, pp. 695-772, 2020. [ bib | DOI ]
[2] O. G. Ernst, “Quantifizierung von Unsicherheit: Propagation und Inferenz,” GAMM Rundbrief, vol. 2, pp. 4-9, 2017. [ bib | pdf ]
[3] O. G. Ernst and K. A. Cliffe, “Uncertainty Quantification 2012: Probabilistic UQ for PDEs with Random Data: A Case Study,” SIAM News, vol. 45, October 2012. [ bib ]
[4] M. Eiermann, O. G. Ernst, and W. Queck, “A very short finite element tutorial,” in Simulationstechniken in der Materialwissenschaft (P. Klimanek and W. Pantleon, eds.), vol. B 279 of Freiberger Forschungshefte, pp. 17-40, TU Bergakademie Freiberg, 1996. [ bib ]