Similar Matrices & Geometric Multiplicity

In summary, the conversation discusses how to prove that if two matrices are similar, then they have the same eigenvalues with the same algebraic and geometric multiplicities. It is shown that the characteristic polynomials of the two matrices are the same, but to prove the same geometric multiplicities, it is necessary to show that the eigenspaces of the two matrices are related by the similarity transformation. With the help of a hint, it is shown that if an eigenvector of one matrix is transformed by the similarity matrix, it becomes an eigenvector of the other matrix with the same eigenvalue. Therefore, the geometric multiplicities are the same.
  • #1
Whatever123
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Homework Statement


Prove that if two matrices are similar then they have the same eigenvalues with the same algebraic and geometric multiplicity.

Homework Equations


Matrices A,B are similar if A = C[tex]\breve{}[/tex]BC for some invertible C (and C inverse is denoted C[tex]\breve{}[/tex] because I tried for a long time to figure out how to get an inverse sign in latex but couldn't figure it out...).

The Attempt at a Solution


To show that two similar matrices have the same eigenvalues with the same geometric multiplicities, I need to show that their characteristic polynomials are the same.
Let A,B be similar matrices. Then,
A = C(inverse)BC
A-[tex]\lambda[/tex]I = C[tex]\breve{}[/tex]BC - [tex]\lambda[/tex]I
A-[tex]\lambda[/tex]I = C[tex]\breve{}[/tex]BC - [tex]\lambda[/tex]C[tex]\breve{}[/tex]C since C[tex]\breve{}[/tex]C=I
A-[tex]\lambda[/tex]I = C[tex]\breve{}[/tex][B-[tex]\lambda[/tex]]C
det(A-[tex]\lambda[/tex]I) = det(C[tex]\breve{}[/tex][B-[tex]\lambda[/tex]I]C)
det(A-[tex]\lambda[/tex]I) = det(C[tex]\breve{}[/tex]det(B-[tex]\lambda[/tex]I)det(C)
det(A-[tex]\lambda[/tex]I) = det(C[tex]\breve{}[/tex])det(C)det(B-[tex]\lambda[/tex]I)
Therefore, det(A-[tex]\lambda[/tex]I) = det(B-[tex]\lambda[/tex]I)
So, A, B have the same characteristic polynomials. This implies that they have the same eigenvalues with the same algebraic multiplicity. However, I do not think that this implies that they have the same geometric multiplicity because it doesn't same anything about the dimension of the eigenspace. Does it? Any suggestions on how I should try to show that the geometric multiplicity is the same?

So does anyone have any advice? I spent a while to get the first part, I just could use a nudge in the right direction for the next part... Thanks in advance.
 
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  • #2
No, algebraic multiplicity doesn't tell you anything about geometric multiplicity. The geometric multiplicity is the number of linearly independent eigenvectors corresponding to a given eigenvalue lambda. Hint: can you show if A=C^(-1)BC and x is an eigenvector of A, then Cx is an eigenvector of B with the same eigenvalue?
 
  • #3
Dick said:
No, algebraic multiplicity doesn't tell you anything about geometric multiplicity. The geometric multiplicity is the number of linearly independent eigenvectors corresponding to a given eigenvalue lambda. Hint: can you show if A=C^(-1)BC and x is an eigenvector of A, then Cx is an eigenvector of B with the same eigenvalue?


So now that I've proven that A, B have same eigenvalues [tex]\lambda[/tex]1-[tex]\lambda[/tex]n and that they appear the same amount of times, consider the eigenvectors for those eigenvalues. As you said, let x be an eigenvector of A. Need to show that Cx is an eigenvector of B with the same eigenvalue...

If x is an eigenvector of A, then:
Ax = [tex]\lambda[/tex]x where [tex]\lambda[/tex] is the corresponding eigenvalue.

Since A=C^(-1)BC, Ax=C^(-1)BCx=[tex]\lambda[/tex]x
Then, CAx=BCx=C[tex]\lambda[/tex]x

So, BCx = Cx[tex]\lambda[/tex]

Shows that Cx is an eigenvector of B with the same eigenvalue [tex]\lambda[/tex].

So since if x is an eigenvector of A with eigenvalue [tex]\lambda[/tex] then Cx is an eigenvector of A with the same eigenvalue [tex]\lambda[/tex] then the geometric multiplicities are the same? The same eigenvalue will correspond to a similar eigenvector and eigenspace so the geometric multiplicity will be the same?
 
  • #4
Basically. The geometric multiplicity is the dimension of the eigenspace of lambda. You've shown C maps the eigenspace of A to the eigenspace of B. C^(-1) does the reverse. C is a nonsingular matrix. That shows the dimensions are the same, right?
 
  • #5
Yes, I understand now. Thank you for your help. I figured out the first part and just needed that little hint to help me with the rest!
 

Related to Similar Matrices & Geometric Multiplicity

1. What is a similar matrix?

A similar matrix is a type of matrix that has the same eigenvalues and eigenvectors as another matrix. This means that the two matrices can be transformed into each other through a change of basis.

2. How do you determine if two matrices are similar?

To determine if two matrices are similar, you can calculate their eigenvalues and eigenvectors. If the eigenvalues and eigenvectors are the same, then the matrices are similar. You can also check if the matrices have the same rank, determinant, and trace.

3. What is the geometric multiplicity of an eigenvalue?

The geometric multiplicity of an eigenvalue is the number of linearly independent eigenvectors associated with that eigenvalue. It represents the number of dimensions in the eigenspace for that eigenvalue.

4. How does the geometric multiplicity relate to the algebraic multiplicity?

The algebraic multiplicity of an eigenvalue is the number of times the eigenvalue appears as a root of the characteristic polynomial. The geometric multiplicity is always less than or equal to the algebraic multiplicity. When the two are equal, the matrix is said to be diagonalizable.

5. Why are similar matrices important in linear algebra?

Similar matrices have the same properties and characteristics, making them useful in solving systems of linear equations and performing operations such as matrix multiplication. They also allow for easier analysis and understanding of a matrix through its eigenvalues and eigenvectors.

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