Inverse Problems and Parameter Estimation
GEOS 627/427 — Spring 2024
Instructor: Carl Tape
ctape@alaska.edu
Type: in-person
Time: Tues 8:30–10:30
Thur 8:30–11:30
Location: Elvey Auditorium
Prereqs.: Linear Algebra +
Calculus 3; or
instructor perm.
Credits: 3
Computational lab: Labs will be conducted on JupyterHub, which requires only an internet connection. Python will be the coding language.
Course goals: We will explore the ubiquitous realm of inverse problems in the sciences: how to use observations to make inferences about underlying physical quantities or processes. Our ultimate goal is to be able to recognize the fundamental components of an inverse problem—measurements, model parameters, misfit function, forward model—then to pose an approach to solving the problem, then solve the problem with computational algorithms.
Parameter Estimation and Inverse Problems, 3rd ed., 2019
Aster, Borchers, Thurber
Inverse Problem Theory and Methods for Model Parameter Estimation, 2005, Tarantola
Got data?
Got a physical model?
Then you’ve got a problem...
An inverse problem!
Key question:
How can data (observations) be used to estimate unknown model parameters and associated uncertainties?