Product of singular values = determinant proof

Click For Summary
SUMMARY

The proof that the determinant of an n x n matrix A is equal to the product of its singular values is established through the singular value decomposition A = U*E*V. Here, E is a diagonal matrix containing the singular values, and its determinant is the product of these values. Since U and V are unitary matrices, their determinants are either +1 or -1, leading to the conclusion that the absolute value of the determinant of A is equal to the product of the singular values, expressed as |det(A)| = product of singular values.

PREREQUISITES
  • Understanding of singular value decomposition (SVD)
  • Knowledge of unitary matrices and their properties
  • Familiarity with determinants of matrices
  • Basic concepts of eigenvalues and eigenvectors
NEXT STEPS
  • Study the properties of unitary matrices and their determinants
  • Explore the relationship between eigenvalues and singular values
  • Learn about the implications of singular value decomposition in data analysis
  • Investigate the geometric interpretation of determinants in linear transformations
USEFUL FOR

Mathematicians, students studying linear algebra, data scientists utilizing singular value decomposition, and anyone interested in matrix theory and its applications.

Vai
Messages
5
Reaction score
0

Homework Statement



So I'm working on this proof. Given an n x n (square) matrix, prove that it's determinant is equal to the product of it's singular values.

Homework Equations



We are given A = U*E*V as a singular value decomposition of A.

The Attempt at a Solution



I was thinking that det(A) = det(U) * det(E) * det(V)

and since E is the diagonal matrix with singular values on it's diagonal, it's determinant is the product of those singular values.

But then what to do about det(U) and det(V)? I guess it's logical that the product of their determinants is 1, but how do I show that?
 
Physics news on Phys.org
Hi Vai! :smile:

Do your singular values always need to be positive?? Does det(E) always need to be positive and det(A)??

U and V are unitary, what do you know about the determinant of unitary matrices?
 
micromass said:
Hi Vai! :smile:

Do your singular values always need to be positive?? Does det(E) always need to be positive and det(A)??

U and V are unitary, what do you know about the determinant of unitary matrices?

Thanks for the quick response.

I'm not sure about the sign on the singular values. Since they are the square roots of the eigenvalues of A' * A, then I assume that they are all positive. So then that means det(E) is also positive.

I wasn't aware that U and V are unitary matrices. But your comment made me think, and according to the definition of the singular value decomposition, they are orthogonal matrices. So then I can say their determinants are +/- 1.

I think that is enough then to show the det(A) is the product of the singular values since:

det(A) = det(U) * det(E) * det(V)
= (+/- 1) * (product of singular values) * (+/- 1)
 
Last edited:
How can det(A) equal det(E) if det(E) is always positive, but if det(A) is not always positive??
 
Whoops, I'm really sorry. I had to prove that the absolute value of the determinant of A is equal to the product of the singular values.

then:

|det(A)| = |det(U) * det(E) * det(V)|
= | (+/- 1) * (product of singular values) * (+/- 1) |
= product of singular values
 
Vai said:
Whoops, I'm really sorry. I had to prove that the absolute value of the determinant of A is equal to the product of the singular values.

then:

|det(A)| = |det(U) * det(E) * det(V)|
= | (+/- 1) * (product of singular values) * (+/- 1) |
= product of singular values

That is correct! :smile:
 
Ok, thank you very much for your help; saved me a lot of time there.
 

Similar threads

  • · Replies 4 ·
Replies
4
Views
1K
  • · Replies 5 ·
Replies
5
Views
5K
  • · Replies 11 ·
Replies
11
Views
1K
  • · Replies 5 ·
Replies
5
Views
2K
  • · Replies 6 ·
Replies
6
Views
3K
  • · Replies 15 ·
Replies
15
Views
2K
  • · Replies 9 ·
Replies
9
Views
2K
  • · Replies 11 ·
Replies
11
Views
2K
  • · Replies 2 ·
Replies
2
Views
7K
Replies
13
Views
33K