Diagonalizability of 3x3 Matrices with 3 Distinct Eigenvalues

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SUMMARY

A 3x3 matrix with exactly three distinct eigenvalues is guaranteed to be diagonalizable due to the presence of three independent eigenvectors corresponding to each eigenvalue. This conclusion is supported by the fundamental theorem of linear algebra, which states that the dimension of the eigenspace must equal the number of distinct eigenvalues for diagonalizability. The transformation represented by the matrix can be expressed in a diagonal form using the eigenvalues along the diagonal, confirming the matrix's diagonalizability.

PREREQUISITES
  • Understanding of eigenvalues and eigenvectors
  • Familiarity with linear transformations
  • Knowledge of diagonalization of matrices
  • Basic concepts of vector spaces
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  • Study the proof of the diagonalization theorem for matrices
  • Learn about the relationship between eigenvalues and eigenspaces
  • Explore the implications of having repeated eigenvalues on diagonalizability
  • Investigate the Jordan form for matrices that are not diagonalizable
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Students studying linear algebra, mathematicians focusing on matrix theory, and educators teaching concepts of eigenvalues and diagonalization.

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Homework Statement



quick question, if there is a 3x3 matrix which has exactly 3 distinct eigenvalues why must it be diagonalizable?

Homework Equations





The Attempt at a Solution

 
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How is diagolization related to the dimension of the eigenspace? Why would distinct eigenvalues let you satisfy this dimension criteria?
 
well since its a 3x3 matrix, the most eigenvalues it could have is 3? so since there is 3 unique eigenvalues, then it is definitely diagonalizable?
 
You need two theorems to show this is true and I hinted at them in my post.
 
I think it is better to think in terms of linear transformations- any linear transformation can be represented as a matrix in a given basis: Apply the linear tranformation to each of the basis vectors in turn, the write the result as a linear combination of the basis vectors- the coefficients are the columns of the matrix.

The three distinct eigenvalues must have 3 independent eigenvectors. Using those eigenvectors as a basis for the vector space, the linear operator is represented by a diagonal matrix with the eigenvalues on the diagonal.

Equivalently, if A is a matrix with three distinct eigenvalues, B is the matrix having those three eigenvectors as columns, then B-1AB is the diagonal matrix having the eigenvalues on the diagonal.

By the way, having three independent eigenvectors is a necessary condition for a matrix to be diagonalizable. Having three distinct eigenvalues is not necessary.
 
so what if a 3x3 matrix only has two eigenvalues, does that mean its not able to be diagonalized?
 
No, reread what Halls wrote. One of the eigenvalues could have a two dimensional eigenspace.
 
Thanks guys, I think its making sense, we will see on finals week lol.
 

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