Proving Matrix Similarity: Trace vs. Determinant Comparison

  • Thread starter talolard
  • Start date
  • Tags
    Matrices
In summary, when showing that two matrices are similar, it is not enough to only show that their traces are equal or that their determinants are equal. This is because there are examples of matrices with equal traces or determinants that are not similar. In order for two matrices to be similar, they must have the same eigenvalues and the same number of independent eigenvectors corresponding to each eigenvalue.
  • #1
talolard
125
0
If I have two matrices A and B and I want to show they are similar, is it enough to show that Trace(A)=Trace(B) or instead show that Det(A)=Det(B)?
Thanks
Tal
 
Physics news on Phys.org
  • #2
No, it isn't. For example, both
[tex]\begin{bmatrix}1 & 0 \\ 0 & 1\end{bmatrix}[/tex]
and
[tex]\begin{bmatrix}\frac{1}{2} & 0 \\ 0 & 2\end{bmatrix}[/tex]
have the same determinant but are not similar.

Also both
[tex]\begin{bmatrix}1 & 0 \\ 0 & 1\end{bmatrix}[/tex]
and
[tex]\begin{bmatrix}2 & 0 \\ 0 & 0\end{bmatrix}[/tex]
have the same trace but are not similar.

And, just in case you were wondering,
[tex]\begin{bmatrix}1 & 0 \\ 0 & 1\end{bmatrix}[/tex]
and
[tex]\begin{bmatrix}1 & 1 \\ 0 & 1\end{bmatrix}[/tex]
have the same determinant and the same trace but are not similar.

In order to be similar, two matrices must have the same eigenvalues and the same number of independent eigenvectors corresponding to each eigenvalue.
 
  • #3
Great, Thanks.
 

FAQ: Proving Matrix Similarity: Trace vs. Determinant Comparison

What is the definition of similarity of matrices?

The similarity of matrices refers to the relationship between two matrices that have the same size and shape. It means that they are composed of the same number of rows and columns, and the corresponding elements of the matrices have similar mathematical properties.

How is the similarity of matrices determined?

The similarity of matrices is determined by calculating the eigenvalues and eigenvectors of the matrices. If the eigenvalues and eigenvectors of two matrices are the same, then the matrices are considered similar. Another way to determine similarity is by using row or column operations to transform one matrix into the other.

What are the applications of similarity of matrices?

Similarity of matrices is used in various fields such as linear algebra, statistics, and computer science. In linear algebra, similarity is used to simplify matrix computations and to solve systems of equations. In statistics, similarity is used in multivariate analysis and data reduction techniques. In computer science, similarity is used in data compression and pattern recognition algorithms.

Can two matrices be similar but not equal?

Yes, two matrices can be similar but not equal. Similarity only requires that the matrices have the same size and shape, and the corresponding elements have similar properties. This means that the matrices can have different numerical values, but their underlying structure is the same.

What is the significance of diagonalizable matrices in similarity?

Diagonalizable matrices are important in similarity because they can be easily transformed into diagonal matrices, which have all zero elements except for the main diagonal. This simplifies calculations and makes it easier to determine if two matrices are similar. Additionally, diagonalizable matrices have a unique set of eigenvalues and eigenvectors, making them useful in solving systems of equations and other mathematical problems.

Similar threads

Replies
6
Views
3K
Replies
25
Views
3K
Replies
5
Views
4K
Replies
4
Views
1K
Replies
5
Views
2K
Replies
18
Views
3K
Replies
15
Views
4K
Back
Top