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Endomorphism/Eigenspaces/Relations/Section

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We have seen in fact that the eigenspace to is the kernel of the endomorphism. More general, the following characterization holds.


Let be a field, a -vector space and

a linear mapping. Let . Then

Let . Then if and only if , and this is the case if and only if holds, which means .


In particular, is an eigenvalue of if and only if is not injective. For a given , this property can be checked with the help of a linear system (or the determinant), and the eigenspace can be determined. However, it is not a linear problem to decide whether has eigenvalues at all and how those can be determined. We will continue to study a linear mapping by considering the differences to homotheties for various .

For an -matrix , we have to determine the kernel of the matrix . If, for example, we want t know whether the matrix has the eigenvalue , then

shows that this is not the case.


Let be a field, a -vector space and

a linear mapping. Let be elements in . Then

Let . Then

Therefore,

and this implies, because of , .



Let be a field, a -vector space and

a linear mapping. Let be eigenvectors for (pairwise) different eigenvalues . Then are

linearly independent.

We prove the statement by induction on . For , the statement is true. Suppose now that the statement is true for less than vectors. We consider a representation of , say

We apply to this and get, on one hand,

On the other hand, we multiply the equation with and get

We look at the difference of the two equations, and get

By the induction hypothesis, we get for the coefficients , . Because of , we get  for , and because of , we also get .



Let be a field, a finite-dimensional -vector space and

a linear mapping. Then there exist at most many eigenvalues

for .

Proof

In particular, an endomorphism on a finite-dimensional vector space has only finitely many eigenvalues.