PULS
Foto: Matthias Friel
Inverse theory can be seen as the mathematical formalisation of the process of data interpretation. It is about the inference of properties (parameters) of a (hypothesized) physical system (model) from observed data.
We know what we (believe to) know about the Earth (and other physical systems) applying inverse problem techniques to those system observables we are capable to measure and quantify. Unfortunately, observations in earth sciences are often noisy, spatially or temporally sparse and sometimes even contradictory or inconsistent. Further, the physical systems we want to describe are often not well understood and thus simplified models are often used to allow quantification at all. It is therefore clear that within inverse problem theory model parameter uncertainty estimates are also of key interest as well as techniques allowing for selecting reasonable/appropriate models from a number of hypothesis regarding the physical system.
In the course, students will be introduced to the principal ideas of the formal treatment of inverse problems and will learn the application of inversion techniques to problems in geophysics and geosciences with hands-on examples.
1) William Menke, Geophysical data analysis, discrete inverse theory
2) Andreas Fichter, Lecture notes on inverse theory (doi: 10.33774/coe-2021-qpq2j)
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