Positive-definite symmetric matrix satisfying a certain property

In summary, the author is trying to solve a homework equation that states that there exists an invertible matrix that satisfies the equation for all vectors with nonzero entries in a group, but is not sure where to go from there. He is also uncertain if knowing the definition of a group and the fact that G is finite helps.
  • #1
Convergence
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Homework Statement


We have a finite group ##G## and a homomorphism ##\rho: G \rightarrow \mathbb{GL}_n(\mathbb{R})## where ##n## is a positve integer. I need to show that there's an ##n\times n## positive definite symmetric matrix that satisfies ##\rho(g)^tA\rho(g)=A## for all ##g \in G##, where ##t## means transpose

Homework Equations





The Attempt at a Solution


Well I've basically just written down definitions and tried to go from there. So for all non-zero vectors ##v## with ##n## real entries, ##v^tAv>0##, and I know ##A=A^t## Also, I know ##A## is positive-definite if and only if there exists an invertible ##n\times n## matrix ##P## such that ##A=P^tP##. But I'm not really sure where to go with that. I was wondering maybe I can start with ##\rho(g)^tA\rho(g)=A## and then show that ##A## is positive-definite, but I don't really see that going anywhere. If ##\rho(g)## was orthogonal, then maybe that would help, but again I'm not to sure. I'd appreciate any hints. Also, this is from a group theory course that only requires one quarter of linear algebra
 
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  • #2
What would help me is knowing the definition of ##GL_n(R)##.
 
  • #3
brmath, it's the group of nxn invertible matrices over the real numbers.

Convergence, if the determinant of [itex] \rho(g) [/itex] is not 1, then
[tex] \det \left( \rho(g^n) \right) = \det \left( \rho(g)^n \right) = \det\left( \rho(g) \right)^n [/tex]
takes on infinitely many values as n goes to infinity which is a contradiction as G is finite. So [itex] \rho(g) [/itex] has determinant 1 for all g.

I mention this only because you said it might help if [itex] \rho(g) [/itex] was orthogonal; knowing that G is finite does give you information about what the image looks like. I don't know if that helps though.

EDIT: Actually that's a red herring I think... I would suggest focusing on A = PtP, and also remember that the sum of two positive definite matrices is still positive definite!
 
  • #4
Office-Shredder -- if G is finite ##g^n = g## for some n, so I'm not clear where you got inf many values for the determinants.
 
  • #5
Yes, which is why if [tex] \det(\rho(g))^n [/tex] takes on more than finitely many values you get a contradiction (since eventually it should become [itex] \det(\rho(g)) [/itex] again). For example if the determinant was 2 then you would get that the determinant of [itex] \rho(g^n) [/itex] is 2n which is impossible because eventually it has to be 2 again.

Although I realize in my above post I missed the obvious possibility that the determinant could be -1 as well.
 

FAQ: Positive-definite symmetric matrix satisfying a certain property

What is a positive-definite symmetric matrix?

A positive-definite symmetric matrix is a square matrix where all the eigenvalues (or characteristic roots) are positive and the matrix is symmetric, meaning that it is equal to its transpose.

What does it mean for a matrix to satisfy a certain property?

When a matrix satisfies a certain property, it means that the matrix has a specific characteristic or behavior that is described by that property. In the case of a positive-definite symmetric matrix, it means that the matrix has positive eigenvalues and is symmetric.

How can I determine if a matrix is positive-definite and symmetric?

To determine if a matrix is positive-definite and symmetric, you can use various mathematical techniques such as computing the eigenvalues, checking if the matrix is equal to its transpose, or using the Cholesky decomposition method.

Why are positive-definite symmetric matrices important?

Positive-definite symmetric matrices are important because they have several useful properties, such as being invertible, having real eigenvalues, and being diagonalizable. They also have applications in various fields, including statistics, physics, and engineering.

Can a non-square matrix be positive-definite and symmetric?

No, a non-square matrix cannot be positive-definite and symmetric. The definition of a positive-definite symmetric matrix requires it to be a square matrix, meaning that it has the same number of rows and columns.

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