Eigenspaces-symmetric matrix (2x2)

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In summary, to prove that a 2x2 symmetric matrix with real entries has two distinct eigenvalues, the discriminant of the characteristic polynomial must be greater than zero. This means that the matrix cannot have the same value for both a and d, as well as b being equal to zero. Additionally, since there are two eigenvectors and eigenvalues, the only way to determine if they are perpendicular is by using the method for deciding when two vectors are orthogonal, which is based on the fact that a symmetric matrix is equal to its transpose.
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*best&sweetest*
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I have a tough time proving that if a 2x2 symmetric matrix with real entries has two distinct eigenvalues than the eigenspaces corresponding to those eigenvalues are perpendicular lines through the origin in R^2.



All I have is symmetric matrix

a b
b d

and I know that since it has distinct eigenvalues it must be that the discriminant of the characteristic polynomial must be greater than zero, i.e

(a-d)^2 + 4b^2 > 0

so it cannot be that a=d and b=0 at the same time.

Now, I have no clue what to do next, and I have a feeling that this might be on my final exam, so any help would be greatly appreciated. Thanks!
 
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You know a lot more than this. You know there are two eigenvectors and two eigenvalues. Now, what is the only way we have of deciding when two vectors are orthogonal? Remember, symmetrice means A=A^t, and what have you been taught about matrices and the only method you know for deciding when two vectors are orthogonal.
 
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FAQ: Eigenspaces-symmetric matrix (2x2)

What is an eigenspace of a symmetric matrix?

An eigenspace of a symmetric matrix is a subspace of the matrix's vector space that contains all of the eigenvectors associated with a particular eigenvalue of the matrix.

How do you find the eigenspace of a 2x2 symmetric matrix?

To find the eigenspace of a 2x2 symmetric matrix, you first need to find the eigenvalues of the matrix by solving the characteristic equation. Then, for each eigenvalue, you can find the corresponding eigenvector by solving the system of equations given by the matrix equation (A - λI)x = 0, where A is the matrix, λ is the eigenvalue, and x is the eigenvector. The set of all eigenvectors corresponding to a particular eigenvalue will form the eigenspace for that eigenvalue.

What is the dimension of the eigenspace of a symmetric matrix?

The dimension of the eigenspace of a symmetric matrix is equal to the multiplicity of the corresponding eigenvalue. This means that if an eigenvalue has a multiplicity of 2, then the eigenspace for that eigenvalue will have a dimension of 2.

Can a symmetric matrix have multiple eigenspaces?

Yes, a symmetric matrix can have multiple eigenspaces, as it can have multiple distinct eigenvalues. Each eigenvalue will have its own corresponding eigenspace. However, if an eigenvalue has a multiplicity greater than 1, then the eigenspace for that eigenvalue will have a dimension greater than 1.

How are eigenspaces of a symmetric matrix related to each other?

The eigenspaces of a symmetric matrix are orthogonal to each other. This means that the eigenvectors corresponding to different eigenvalues are mutually perpendicular. Additionally, the eigenspaces of a symmetric matrix are complementary, meaning that together they span the entire vector space of the matrix.

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