Bases of Generalized Eigenvectors

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Discussion Overview

The discussion revolves around the process of finding a basis of generalized eigenvectors for operators that are not diagonalizable. Participants explore the steps involved in identifying eigenvalues, eigenspaces, and generalized eigenspaces, while addressing specific points of confusion regarding calculations and definitions.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant outlines a method involving finding eigenvalues, eigenspaces, and generalized eigenspaces, but expresses confusion about calculating the nullspace of the operator raised to a power.
  • Another participant requests a specific example of a non-diagonalizable operator to illustrate the initial steps of the proposed method.
  • A third participant suggests that finding the lowest integer p such that (T-λI)^p has the entire eigenspace as its kernel is crucial, but questions the interpretation of (T-λI)^(p-1) as an eigenvector.
  • A fourth participant inquires about the availability of online resources for computing generalized eigenvectors.

Areas of Agreement / Disagreement

Participants generally agree on the importance of working through a specific example to clarify the steps involved, but there is disagreement and confusion regarding the interpretation of certain mathematical expressions and the process of calculating generalized eigenspaces.

Contextual Notes

There are unresolved aspects regarding the definitions and calculations involved in finding generalized eigenvectors, particularly concerning the interpretation of powers of the operator and their relation to eigenvectors.

quasar_4
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Hi all.

So I'm a bit confused about finding a basis of generalized eigenvectors for an operator that is not diagonalizable. I have some "steps" in mind, but maybe someone can help me out here:

1) Find the eigenvalues of the matrix/operator
2) Find the eigenspaces corresponding to each eigenvector; for those which do not have a "big enough" basis, we must compute the generalized eigenspace for that eigenvalue
3) Here's where I'm confused! I know that the generalized eigenspace is given by kernel((T-λI)^p) for some positive integer p, and that (T-λI)^(p-1) is an eigenvector of T. I guess I'm lost with calculating this nullspace.

Are we literally taking the matrix (T-λI) and raising it to the power p? Because it doesn't seem to work on any problems I've attempted so far... anyone know? :eek:
 
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Could you show us first a small example of an operator that is not diagonalizable.
Take then the opportunity to illustrate the steps 1 and 2.
Then we can discuss maybe step 3.
 
I recommend you do what lalbatross suggests- looking at a specific simple example might help you see what is happening.

You first find the lowest integer p such that (T-λI)^p has the entire eigenspace of [itex]\lamba[/itex] as kernel. But I don't understand what you mean by "(T-λI)^(p-1) is an eigenvector of T". (T-λI)^(p-1) isn't a vector, it is a linear transformation. Did you mean to apply it to something?
 
I wonder if there is any online document available to show us how to compute all the generalized eigenvectors?
 

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