Eigenvalue of Sum of Eigenvectors

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Homework Help Overview

The discussion revolves around the properties of eigenvalues and eigenvectors, specifically focusing on the eigenvalue of the sum of eigenvectors. Participants are examining the implications of eigenvalues being equal or different in the context of linear transformations.

Discussion Character

  • Conceptual clarification, Assumption checking

Approaches and Questions Raised

  • The original poster attempts to demonstrate that the sum of eigenvectors is also an eigenvector under certain conditions, questioning the validity when eigenvalues differ. Others suggest exploring counterexamples to clarify the situation.

Discussion Status

Participants are actively engaging with the problem, with some offering guidance on how to approach the question of whether the statement is true or false. There is a focus on examining specific examples and counterexamples to further the discussion.

Contextual Notes

There is a noted emphasis on carefully interpreting the problem statement, as it requires determining the truth of a claim rather than proving it outright. This has led to discussions about the definitions and relationships between eigenvalues and eigenvectors.

TranscendArcu
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Homework Statement


Skjermbilde_2012_03_10_kl_10_33_27_AM.png


The Attempt at a Solution


So, first I wrote,

[itex]T(X) = λ_1 X, T(Y) = λ_2 Y[/itex]

If [itex]λ_1 = λ_2[/itex]:

[itex]T(X+Y) = T(X) + T(Y) = λ_1 X + λ_2 Y = λ_1 (X+Y)[/itex],

so this does indeed seem to be an eigenvector. But I'm less convinced for the case [itex]λ_1 ≠ λ_2[/itex]. Again, I get the transformation down to the form:

[itex]λ_1 X + λ_2 Y[/itex]

But if eigenvalues are necessarily one constant, then I don't see how I pull constants out as above. How do I go about showing this?
 
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Did you read the problem carefully? It doesn't ask you to show that this is true, it asks you to determine whether or not it is true and the show that.

Okay, if you have doubts about this being true, how about trying to show its not true? If it is not, you should be able to show a counterexample.
Obviously
[tex]\begin{bmatrix}1 & 0 \\ 0 & 2\end{bmatrix}[/tex]
has 1 and 2 as eigenvalues. What are corresponding eigenvalues? What do you get if you multiply that matrix by their sum?
 
What are corresponding eigenvalues?
I'm pretty sure HallsOfIvy meant "corresponding eigenvectors".
 
Yes, thanks.
 

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