How to determine an infinitely dimensional matrix is positive definite

In summary, the conversation discusses how to show the positive definiteness of an infinitely dimensional matrix. One suggestion is to use an inner product and check if it satisfies the definition of positive definite. Another approach is to verify that the matrix is self-adjoint and then show that all eigenvalues are positive. This can be challenging in infinite dimensions, but can be simplified by using an orthonormal basis of eigenvectors.
  • #1
kevchang
3
0
I ran into an infinitely dimensional matrix and wanted to show it is positive definite. I think I cannot do so by checking the principal minors as for finitely dimensional matrices... Can someone let me know how to show its positive definiteness? Thanks a ton!
 
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  • #2
If you've got an inner product in that vector space, maybe you can check whether <Mx, x> > 0 for all x in the space. This implies that a matrix is positive definite in a finite dimensional space (if by positive definite you mean hermitian with non-negative eigenvalues). Not sure if it works in an infinite dimensional space.
 
  • #3
Positive definite is defined using an inner product, so the post above should be taken as a definition, with the proviso that <Mx,x> > 0 for all non-zero x. The usual way to prove such things is to characterize the eigenvalues. In infinite dimensions, things get quite complicated, so one usually starts by verifying that the operator (matrix) is self-adjoint. Then a theorem states that there's an orthonormal basis of eigenvectors, so positive-definite reduces to showing that all eigenvalues are positive.
 

1. How do I determine if a matrix is positive definite?

To determine if a matrix is positive definite, you must check if all of its eigenvalues are positive. If they are, then the matrix is positive definite.

2. Can a matrix have infinitely many dimensions and still be positive definite?

Yes, a matrix can have infinitely many dimensions and still be positive definite. The number of dimensions does not affect whether a matrix is positive definite or not.

3. Is there a specific method or algorithm to determine if a matrix is positive definite?

Yes, there are several methods and algorithms that can be used to determine if a matrix is positive definite. Some common ones include the Cholesky decomposition method and the Sylvester's criterion method.

4. What are the practical applications of positive definite matrices?

Positive definite matrices have many applications in fields such as statistics, engineering, and physics. They are commonly used in optimization problems and to model physical systems.

5. Can a non-square matrix be positive definite?

No, a non-square matrix cannot be positive definite. Positive definiteness is a property that only applies to square matrices, where the number of rows is equal to the number of columns.

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