Arrangement of eigenvalues in a Diagonal matrix

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SUMMARY

In the discussion regarding the arrangement of eigenvalues in a diagonal matrix, it is established that there is no requirement to arrange eigenvalues in increasing order. The example provided illustrates that different arrangements of eigenvalues, such as -2, -1, 1 versus -1, 1, -2, lead to different diagonal matrices (D). The consensus is that multiple matrices P can diagonalize matrix A, allowing for flexibility in the order of eigenvalues along the diagonal.

PREREQUISITES
  • Understanding of eigenvalues and eigenvectors
  • Familiarity with diagonalization of matrices
  • Basic knowledge of linear algebra concepts
  • Experience with matrix operations
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  • Study the properties of diagonal matrices in linear algebra
  • Learn about the process of diagonalization of matrices
  • Explore the implications of eigenvalue arrangement on matrix transformations
  • Investigate the role of matrix P in the diagonalization process
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Students of linear algebra, mathematicians, and anyone involved in matrix theory or eigenvalue analysis will benefit from this discussion.

coconut62
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Homework Statement



Is it necessary to arrange the eigenvalues in increasing value order?

As shown in the image attached, if I arrange my eigenvalues -2, -1, 1 diagonally, my D would be
2^8 , 1, 1 diagonally.

However if i arrange it as, say, -1, 1, -2, my D would be different.

Just want to make sure of it, thanks.
 

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coconut62 said:

Homework Statement



Is it necessary to arrange the eigenvalues in increasing value order?

As shown in the image attached, if I arrange my eigenvalues -2, -1, 1 diagonally, my D would be
2^8 , 1, 1 diagonally.

However if i arrange it as, say, -1, 1, -2, my D would be different.

Just want to make sure of it, thanks.

Good work. Yes, there is more than one matrix P that will diagonalize A. You can arrange the eigenvectors in P in a different order and get the eigenvalues in a different order along the diagonal. I don't think anyone order is more correct than another.
 

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