Running seismic simulations is an important application of computational seismology to better understand the dynamics of earthquakes. Our goal is to utilize observational seismological receiver data to find an approximation of possible source coordinates of an earthquake. Due to not knowing every single parameter and numerical inaccuracies of the simulation we apply Uncertainty Quantification (UQ) to infer possible locations of the source. We use the open-source software SeisSol on a high-performance Linux cluster to simulate earthquakes as well as to determine whether the source fits its receiver data in the wrapper program UQ_SeisSol. In the previous work, an approach to the Bayesian inverse problem with Markov Chain Monte-Carlo (MCMC) methods was already implemented utilizing the parallel Generalized Metropolis-Hastings (GMH) algorithm combined with fused simulations of SeisSol. However, the GMH algorithm rejected every sample proposed by the Metropolis adjusted Langevin algorithm (MALA) and infinite-dimensional MALA (Inf-MALA). For that reason, we conduct a hyperparameter study to find configurations of the MALA and InfMALA proposals to obtain an acceptance rate greater than 0. Furthermore, we compare these results with the random walk proposal and conduct a performance analysis of SeisSol to determine the optimal number of fused simulations for UQ_SeisSol. Our findings include that changing the step size for the MALA and the β factor for the InfMALA proposal leads to the GMH algorithm accepting proposed states and 8 fused simulations being the most efficient configuration performance-wise. We could not prove that the MALA and InfMALA proposals yield better results than the random walk proposal regarding acceptance rate and the number of independent samples.      «

Running seismic simulations is an important application of computational seismology to better understand the dynamics of earthquakes. Our goal is to utilize observational seismological receiver data to find an approximation of possible source coordinates of an earthquake. Due to not knowing every single parameter and numerical inaccuracies of the simulation we apply Uncertainty Quantification (UQ) to infer possible locations of the source. We use the open-source software SeisSol on a high-perfor...     »