Eigenvalues and Eigenvectors uniquely define a matrix

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Discussion Overview

The discussion centers on whether a set of eigenvalues and eigenvectors uniquely defines a matrix. Participants explore the implications of diagonalization and the conditions under which this holds true, particularly in relation to matrices with complex eigenvalues and specific examples.

Discussion Character

  • Debate/contested

Main Points Raised

  • One participant suggests that eigenvalues and eigenvectors do uniquely define a matrix, referencing the construction of a matrix M from its eigenvectors and eigenvalues.
  • Another participant expresses certainty in this assertion, indicating agreement with the first post.
  • A different viewpoint is presented, noting that the uniqueness holds only if the matrix can be diagonalized, and highlights issues with matrices that have complex eigenvalues and the concept of algebraic versus geometric multiplicity of eigenvectors.
  • A challenge is posed to test the assertion using a specific 2x2 matrix example, [0, 1; 0, 0], implying it may not conform to the initial claim.

Areas of Agreement / Disagreement

Participants do not reach a consensus. While some agree that eigenvalues and eigenvectors can define a matrix, others raise complications that suggest this is not universally true.

Contextual Notes

The discussion highlights limitations related to diagonalizability, the nature of eigenvalues (real vs. complex), and the multiplicity of eigenvectors, which remain unresolved.

zeebo17
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Do a set of Eigenvalues and Eigenvectors uniquely define a matrix since you can produce a matrix [tex]M[/tex] from a matrix of its eigenvectors as columns [tex]P[/tex] and a diagonal matrix of the eigenvalues [tex]E[/tex] through [tex]M=P E P^{\dagger}[/tex]?
 
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i'm pretty sure the answer is yes
 
It is a bit more complicated. What you say is true if you can diagonalize the matrix. But take a matrix with complex eigenvalues and you are quickly missing eigenvectors. look up algebraic vs. geometric multiplicity of eigenvectors
 
Try it with 2 x 2 matrix [0, 1; 0, 0]
 

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