Normal nxn Matrices: 1 Eigenvalue Case (Complex #s)

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Discussion Overview

The discussion focuses on the properties of normal nxn matrices that possess exactly one eigenvalue, specifically in the context of complex numbers. Participants explore various types of matrices and their characteristics related to eigenvalues.

Discussion Character

  • Debate/contested

Main Points Raised

  • One participant inquires about generalizations regarding normal nxn matrices with exactly one eigenvalue.
  • Another participant suggests that such matrices could be scalar multiples of the identity matrix.
  • A different participant proposes that they might be permutation matrices.
  • A subsequent reply challenges the permutation matrix idea, stating that permutation matrices can have multiple eigenvalues.
  • One participant provides examples of matrices but is later corrected regarding their eigenvalues, indicating that they allow for more than one eigenvalue.
  • A participant argues that if a matrix is normal and has one eigenvalue, it must be proportional to the identity matrix when expressed in a suitable coordinate system aligned with its eigenvectors.
  • A later reply acknowledges confusion regarding the previous statements about permutation matrices and clarifies the intent to refer to matrices similar to the identity matrix.

Areas of Agreement / Disagreement

Participants express differing views on the types of matrices that can have exactly one eigenvalue, with no consensus reached on the correct characterization of such matrices.

Contextual Notes

Some assumptions about the nature of normal matrices and their eigenvalues remain unresolved, particularly regarding the implications of matrix similarity and the definitions of specific matrix types.

mind0nmath
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Hey. What can be said about all the normal nxn matrices that have exactly 1 eigenvalue? I'm interested in the case where the entries are in C (complex #'s). what sort of generalizations can we make?
thanks.
 
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sounds like scalar multiples of the identity no?
 
they are permutation matrices?
 
Nope -- a permutation matrix can have more than one eigenvalue. mathwonk got it.
 
I meant these kind,
[tex] \left[ {\begin{array}{*{20}c}<br /> 1 & 0 & 0 \\<br /> 0 & 0 & 1 \\<br /> 0 & 1 & 0 \\<br /> \end{array}} \right],\left[ {\begin{array}{*{20}c}<br /> 0 & 0 & 1 \\<br /> 1 & 0 & 0 \\<br /> 0 & 1 & 0 \\<br /> \end{array}} \right][/tex]
 
Trambolin, looking at your first matrix the characteristic equation is

[tex](1-\lambda)(\lambda^2-1) = 0 \Rightarrow \lambda = \pm 1[/tex]

That permits two unique eigenvalues, not one.

Besides if you simply choose the coordinate system aligned with the eigenvectors, in that coordinate system the matrix (call it A) will be proportional to the identity matrix. Then the matrix [tex]A-\lambda I[/tex] will vanish in that coordinate system for some complex number [tex]\lambda[/tex], but then it would have to vanish in all coordinate systems and therefore the matrix is proportional to the identity matrix.
 
DavidWhitbeck said:
Trambolin, looking at your first matrix the characteristic equation is

[tex](1-\lambda)(\lambda^2-1) = 0 \Rightarrow \lambda = \pm 1[/tex]

That permits two unique eigenvalues, not one.

Besides if you simply choose the coordinate system aligned with the eigenvectors, in that coordinate system the matrix (call it A) will be proportional to the identity matrix. Then the matrix [tex]A-\lambda I[/tex] will vanish in that coordinate system for some complex number [tex]\lambda[/tex], but then it would have to vanish in all coordinate systems and therefore the matrix is proportional to the identity matrix.

Yep, I don't really know what was I thinking, because I use a lot of row\column permutations recently, suddenly I thought that you can do anything with them... Sorry for that. Probably I meant matrices similar to identity matrix...
 

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