PHY2603H F specialized: Inverse Theory
Course Title | PHY2603H F specialized |
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Session | fall |
Year of Study | 1st year |
Time and Location |
Time: MW 11 Location: MP505 |
Qinya
Liu |
Official Description
Evolving from year to year, but addressing the problems of fitting physical models (both discreet and continuous) to data, and roughly comprising:
* What is inverse theory in physics and geophysics? When do data-consistent models even exist?
* Multivariate regression modelling of discrete models, Bayesian approaches, maximum likelihood estimation, with errors and
* hypothesis testing, both classical and resampling(e.g. bootstrap).
* Continuous models where spatial resolution is a meaningful concept (Backus-Gilbert theory).
* The Singular Value Decomposition approach to modelling.
* Answerable and unanswerable questions in modelling:
* Singular Value Decompositions, exotic norms such as L-1, L-infinity.
* Methods for non-linear modelling: e.g. Markov Chain Monte Carlo
(MCMC), simulated annealing, genetic algorithms.
Prerequisite: | Recommended: PHY308/408S & this course uses MATLAB as its programming language, and expects some knowledge on complex analysis. |
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Textbook |
No official text. Online notes will be made available as we cover the material. Other useful (but strongly overlapping) references might be: 1. Any book on multivariate regression methods in statistics; 2. Bill Menke's book on Inverse Theory; 3. Bob Parker's book on Inverse Theory; 4. Tarantola's book on Inverse Theory; 5. John Scale's web text on Inverse Theory; 6. Most importantly (for purposes of defining the syllabus), whatever I tell you in class. |