Why is the product of eigenvalues equal to the det(A)?

In summary, the product of eigenvalues of any diagonalisable N × N matrix A must equal the determinant of A because, when A is diagonalized, the diagonal elements of the resulting matrix are the eigenvalues of A. Since the determinant of a diagonal matrix is the product of its diagonal elements, the product of the eigenvalues of A must equal the determinant of A. This can also be shown by taking the determinant of both sides of ##D = P^{-1}AP##, where D is the diagonalized matrix, P is the corresponding change of basis matrix, and A is the original matrix.
  • #1
j3dwards
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0

Homework Statement


Explain in your own words why the product of eigenvalues of any diagonalisable N × N matrix A must equal the determinant of A.

Homework Equations


MT=M-1

The Attempt at a Solution


So what I do know: the determinant measures the change in area of the unit square under the transformation (as the point (x,y) transforms to the point (X,Y)). And the eigenvectors describe the direction of the deformation of the matrix A - which are unchanged by the deformation.

So my question is why does the product of the eigenvectors equal the determinant of the matrix A?
 
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  • #2
If you diagonalize a diagonalizable matrix, what do you get as the diagonal elements in the diagonalized matrix? Another hint, determinant of a matrix is invariant under change of basis.
 
  • #3
In the title and in your last sentence it should be "eigenvalues" instead of eigenvectors.
j3dwards said:
##M^T=M^{-1}##
Why are you assuming ##M## is unitary? This is not necessary.

Hint: Jordan normal form.
Edit: Start with @blue_leaf77's suggestion, then use the Jordan form for the general case. (From the title I got you had to solve it in general, from your description I get you may assume that ##M## is diagonalizable.)
 
  • #4
blue_leaf77 said:
If you diagonalize a diagonalizable matrix, what do you get as the diagonal elements in the diagonalized matrix? Another hint, determinant of a matrix is invariant under change of basis.

You get the eigenvalues in the diagonal elements in the diagonalised matrix.

Please explain, I really don't understand and my exam is soon!
 
  • #5
j3dwards said:
You get the eigenvalues in the diagonal elements in the diagonalised matrix.
Yes, and if you calculate the determinant of this diagonal matrix, how does it look like in terms of the eigenvalues?
 
  • #6
j3dwards said:
You get the eigenvalues in the diagonal elements in the diagonalised matrix.

Please explain, I really don't understand and my exam is soon!
What happens if you take the determinant of both sides of ##D = P^{-1}AP## ?
 

Related to Why is the product of eigenvalues equal to the det(A)?

1. What is the significance of eigenvalues in matrix operations?

Eigenvalues are important because they represent the scaling factor of the eigenvectors in a matrix. This allows us to better understand the behavior of a matrix and its transformations.

2. How are eigenvalues and determinants related?

The product of eigenvalues is equal to the determinant of a matrix. This means that the eigenvalues and determinant share a common relationship and can provide similar information about a matrix.

3. Why is it important to know the product of eigenvalues and the determinant?

Knowing the product of eigenvalues and the determinant can help us understand several properties of a matrix, such as its invertibility, trace, and characteristic polynomial. It also allows us to solve systems of linear equations and perform other matrix operations.

4. Can the product of eigenvalues ever be equal to the determinant of a matrix?

Yes, the product of eigenvalues is always equal to the determinant of a matrix. This is a fundamental property of matrices and can be proven mathematically.

5. How does the product of eigenvalues affect the overall behavior of a matrix?

The product of eigenvalues can provide information about the scale and orientation of a matrix. It can also give insight into its stability and convergence properties, making it a valuable tool in various fields such as physics, engineering, and economics.

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