Distinct Eigenvalues
Today I’d like to point out a little fact that applies over any field (not just the algebraically-closed ones). Let be a linear endomorphism on a vector space
, and for
, let
be eigenvectors with corresponding eigenvalues
. Further, assume that
for
. I claim that the
are linearly independent.
Suppose the collection is linearly dependent. Then for some we have a linear relation
We can assume that is the smallest index so that we get such a relation involving only smaller indices.
Hit both sides of this equation by , and use the eigenvalue properties to find
On the other hand, we could just multiply the first equation by to get
Subtracting, we find the equation
But we this would contradict the minimality of we assumed before. Thus there can be no such linear relation, and eigenvectors corresponding to distinct eigenvalues are linearly independent.

[...] vectors here, they span a subspace of dimension , which must be all of . And we know, by an earlier lemma that a collection of eigenvectors corresponding to distinct eigenvalues must be linearly [...]
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[...] Eigenspaces are Disjoint We know that eigenspaces of distinct eigenvalues are disjoint. That is, no vector is an eigenvector of two different eigenvalues. This extends to generalized [...]
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[...] as a corollary we can find that not only are the eigenvectors corresponding to distinct eigenvalues linearly independent, they are actually orthogonal! Indeed, if and are eigenvectors of with [...]
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Is the dimension of V, n? ie dim(V)=n, ie their contains n elements in a basis for V. since you have n eigenvectors that are linearly independent and any set of n linearly independent vectors is a basis for an n dimensional vectorspace.
Yes, H, that’s true. But all this post was intended to prove was their linear independence.
Oh, and I think you mean “there”.