651-4096-00L  Inverse Theory I: Basics

SemesterSpring Semester 2021
LecturersA. Fichtner
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
651-4096-00 VInverse Theory I: Basics
For students attending Geothermal Energy: Note that Geothermal Energy starts at 12:30
28s hrs
Wed/108:15-12:00NO C 44 »
08:15-12:00NO F 11 »
A. Fichtner

Catalogue data

AbstractInverse theory is the art of inferring properties of a physical system from noisy and sparse observations. It is used to transform observations of waves into 3D images of a medium seismic tomography, medical imaging and material science; to constrain density in the Earth from gravity; to obtain probabilities of life on exoplanets ... . Inverse theory is at the heart of many natural sciences.
ObjectiveThe goal of this course is to enable students to develop a mathematical formulation of specific inference (inverse) problems that may arise anywhere in the physical sciences, and to implement suitable solution methods. Furthermore, students should become aware that nearly all relevant inverse problems are ill-posed, and that their meaningful solution requires the addition of prior knowledge in the form of expertise and physical intuition. This is what makes inverse theory an art.
ContentThis first of two courses covers the basics needed to address (and hopefully solve) any kind of inverse problem. Starting from the description of information in terms of probabilities, we will derive Bayes' Theorem, which forms the mathematical foundation of modern scientific inference. This will allow us to formalise the process of gaining information about a physical system using new observations. Following the conceptual part of the course, we will focus on practical solutions of inverse problems, which will lead us to study Monte Carlo methods and the special case of least-squares inversion.

In more detail, we aim to cover the following main topics:

1. The nature of observations and physical model parameters
2. Representing information by probabilities
3. Bayes' theorem and mathematical scientific inference
4. Random walks and Monte Carlo Methods
5. The Metropolis-Hastings algorithm
6. Simulated Annealing
7. Linear inverse problems and the least-squares method
8. Resolution and the nullspace
9. Basic concepts of iterative nonlinear inversion methods

While the concepts introduced in this course are universal, they will be illustrated with numerous simple and intuitive examples. These will be complemented with a collection of computer and programming exercises.

Prerequisites for this course include (i) basic knowledge of analysis and linear algebra, (ii) basic programming skills, for instance in Matlab or Python, and (iii) scientific curiosity.
Lecture notesPresentation slides and detailed lecture notes will be provided.
Prerequisites / NoticeThis course is offered as a half-semester course during the first part of the semester

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits3 credits
ExaminersA. Fichtner
Typegraded semester performance
Language of examinationEnglish
RepetitionRepetition possible without re-enrolling for the course unit.
Additional information on mode of examinationWritten Exams and Exercises

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Offered in

ProgrammeSectionType
Applied Geophysics MasterPeriod ETHZOInformation
Earth Sciences MasterGeophysics: Methods IOInformation
Earth Sciences MasterLithosphere Structure and TectonicsOInformation
Computational Science and Engineering BachelorGeophysics: Subject 7WInformation
Computational Science and Engineering MasterGeophysics: Subject 7WInformation