Little question about eigenvalues

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Discussion Overview

The discussion revolves around the properties of eigenvalues, particularly focusing on the scenario where one eigenvalue is zero and whether non-zero eigenvalues can also exist. The scope includes theoretical aspects of linear algebra and eigenvalue computation.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant questions if having an eigenvalue of zero implies that non-zero eigenvalues cannot exist.
  • Another participant notes that for diagonal matrices, eigenvalues are simply the diagonal elements, prompting further consideration of the implications of a zero eigenvalue.
  • A participant acknowledges their earlier question as naive, suggesting that non-zero eigenvalues can indeed coexist with a zero eigenvalue.
  • It is proposed that eigenvalues are roots of the characteristic polynomial, raising the question of whether a zero root allows for other non-zero roots.
  • A specific example is provided where a cubic characteristic polynomial has one eigenvalue equal to zero and another eigenvalue that is non-zero, illustrating that both can exist simultaneously.
  • Clarification is made regarding the relationship between the determinant being zero and the existence of eigenvalues, with emphasis on the process of finding eigenvalues through the determinant of a matrix.
  • Another participant states that having a zero determinant indicates the matrix is not invertible, questioning the implications of this fact.

Areas of Agreement / Disagreement

Participants express differing views on the implications of having a zero eigenvalue, with some asserting that non-zero eigenvalues can coexist while others explore the relationship between eigenvalues and the determinant. The discussion remains unresolved regarding the broader implications of these properties.

Contextual Notes

There are nuances regarding the definitions of eigenvalues and their relationship to the determinant that are not fully explored, including the implications of multiple eigenvalues and the specific characteristics of different types of matrices.

Kubilay Yazoglu
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Hey there, I'm thinking about if one of the eigenvalues is zero (means determinant is 0. right?) So, is there any possibility to non-zero eigenvalue also exists?
 
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for a diagonal matrix, the eigenvalues are the numbers on the diagonal. so what do you think can happen?
 
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Well, now that I'm more inside of these things, I realized that I've asked a stupid question :D Of course there is.
 
another point of view is that eigenvalues are roots of the characteristic polynomial. so if one root is zero can other roots be non zero?
 
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mathwonk said:
another point of view is that eigenvalues are roots of the characteristic polynomial. so if one root is zero can other roots be non zero?
Yes
 
Well, you could have something like:
## \lambda^3 + 18\lambda^2 + 81\lambda##
Where you have eigenvalues ##\lambda_1 = 0## and ##\lambda_2 = -9##.
So, I certainly think you can have an eigenvalue of zero and other nonzero eigenvalues. And also, I'm not sure what you mean by the determinant being zero; to get a characteristic polynomial, you have to take the determinant and set it equal to zero to solve for the eigenvalues in the first place.
In other words, you find eigenvalues using:
##\det(A - \lambda I_A) = 0## (Given a matrix A and its identity matrix, IA).
 
*EDIT*
I misspoke above; I listed two eigenvalues, whereas a ##3 \times 3## matrix (with a cubic characteristic polynomial) would have three eigenvalues. Of course, in the case I listed above, two of the eigenvalues, ##\lambda_2## and ##\lambda_3## would be the same (λ2 = λ3 = -9). I was treating them as roots of a cubic, where (with three solutions) there are only two roots, given two of them are the same. In the context of matrix algebra, though, all eigenvalues should be accounted for.
 
Well, if there is an eigenvalue ## \lambda=0 ##, then Det(A-0I_A)=Det(A)=0.
 
Why is that a problem? Having zero determinant just means that it's not invertible.
 

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