Prove Rank & Similarity of Matrices A & B

  • Thread starter Bachelier
  • Start date
  • Tags
    rank
In summary: So if you have two matrices that have the same eigenvalues but are not similar, then their rank is different.
  • #1
Bachelier
376
0
let A and B be n x n matrices over a field F. Suppose that A^2 = A and B^2 = B. Prove that A and B are similar if and only if they have the same rank.
 
Physics news on Phys.org
  • #2
Can I use the same eigenvalues argument?
They have +1,-1 as eigenvalue, but how do I make the connection to the rank?

Thank you
 
  • #3
Perhaps this will help: Every vector x can be written as x=(I-A)x+Ax. If [tex]A^2=A[/tex] then the range of (I-A) and the range of A are disjoint complementary subspaces (needs a proof). A vanishes on the first subspace while the second one consists of vectors of eigenvalues 1. Similarly for B.
 
  • #4
arkajad said:
Perhaps this will help: Every vector x can be written as x=(I-A)x+Ax. If [tex]A^2=A[/tex] then the range of (I-A) and the range of A are disjoint complementary subspaces (needs a proof). A vanishes on the first subspace while the second one consists of vectors of eigenvalues 1. Similarly for B.

So basically to prove similarity of A and B, I am proving they have the same eigenvalues. Am I wrong?
we have
[tex]A^2 -A =0[/tex]
[tex]A( A - I) =0[/tex]
A( A - I) is not invertible.
To say A is not invertible is to say A has eigenvalue of 0.
and A - I is not invertible , means A has eigenvalue of 1. Similarly for B.
What do you think?
 
  • #5
Bachelier said:
Can I use the same eigenvalues argument?
They have +1,-1 as eigenvalue, but how do I make the connection to the rank?

Thank you
If you know the eigenvalues, what can you tell about the null space and therefore the nullity? Using the nullity, what can you tell about rank given that they have the same dimensions?
 
  • #6
Anonymous217 said:
If you know the eigenvalues, what can you tell about the null space and therefore the nullity? Using the nullity, what can you tell about rank given that they have the same dimensions?

Using the Nullity, I can find the rank of A by the dimension theorem. n-r.
If I know the eigenvalues, then rank A = [tex]n - rank (A- \lambda*I)[/tex]I) For all eigenvalues.

Note that Null space of A alone equals the eigenspace of its eigenvalue 0.
 
  • #7
Equality of the ranks should tell you that the two complementary subspaces have the same dimension for A i B. Therefore you can find ... what?
 
  • #8
Be careful, you have [tex] \begin{pmatrix}1&0\\0&1\end{pmatrix}, \begin{pmatrix}1&1\\0&1\end{pmatrix}[/tex] which are not similar but have the same eigenvalues. Better check for a similarity matrix between two idempotent matrix and use trace(P) = rank(P) for an idempotent matrix P. I did not check it myself but that was the first thing came to my mind.

EDIT : Actually this proves the [itex](\Longrightarrow)[/itex] direction since if they are similar, their trace equals to the number of "1" eigenvalues which is their corresponding matrix rank.

Note: Idempotent matrix eigenvalues are either 1 or zero.
 
Last edited:

1. How do I prove the rank of matrices A and B?

The rank of a matrix is the maximum number of linearly independent rows or columns. To prove the rank of matrices A and B, you can use the Gaussian elimination method to reduce the matrices into their row-echelon form. The number of non-zero rows in the row-echelon form will be the rank of the matrix.

2. Can I use the determinant to prove the similarity of matrices A and B?

No, the determinant of a matrix is not enough to prove its similarity to another matrix. While similar matrices have the same determinant, matrices with the same determinant are not necessarily similar.

3. What is the importance of proving the similarity of matrices A and B?

Proving the similarity of matrices A and B is important because it allows us to understand the relationship between the two matrices. Similar matrices have the same eigenvectors and eigenvalues, which are important properties in many applications such as computing powers of matrices and solving differential equations.

4. Is it possible for two matrices to have the same rank but not be similar?

Yes, it is possible for two matrices to have the same rank but not be similar. This can happen when the matrices have different eigenvalues, even though they have the same number of linearly independent rows or columns.

5. Can I use elementary row or column operations to prove the similarity of matrices A and B?

Yes, you can use elementary row or column operations to prove the similarity of matrices A and B. If you can transform matrix A into matrix B through elementary row or column operations, then the two matrices are similar. This is because these operations do not change the rank or the eigenvalues of a matrix.

Similar threads

  • Linear and Abstract Algebra
Replies
7
Views
1K
  • Linear and Abstract Algebra
Replies
2
Views
1K
  • Linear and Abstract Algebra
Replies
4
Views
871
  • Linear and Abstract Algebra
Replies
5
Views
1K
  • Linear and Abstract Algebra
Replies
6
Views
772
  • Linear and Abstract Algebra
Replies
9
Views
4K
  • Linear and Abstract Algebra
Replies
1
Views
622
  • Linear and Abstract Algebra
Replies
5
Views
1K
  • Math POTW for University Students
Replies
2
Views
875
  • Linear and Abstract Algebra
Replies
1
Views
975
Back
Top