Eigenvector existence in complex space

jostpuur
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I'm reading a proof where there's a conclusion: "Since zW\subset W, there is an eigenvector v\neq 0 of z in W, zv=\lambda v." There W is a subspace of some vector space V, and z is a matrix, in fact a member of some solvable Lie algebra \mathfrak{g}\subset\mathfrak{gl}(V). (Could be irrelevant information, though.)

This seemed a strange claim, because just because z maps W into W doesn't in general mean that the eigenvector exists like that. However, I noticed that I was unable to come up with a counter example if I allowed the W to be over the complex field. Is there a theorem that says something like this:

Let W\subset\mathbb{C}^n be a vector space, and A a matrix such that AW\subset W. Then there exists an eigenvector v\in W of the matrix A, so that Av=\lambda v for some \lambda \in\mathbb{C}^n.
 
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hmhm... the equation

<br /> \textrm{det}(A-\lambda\cdot 1)=0<br />

of course has complex solutions. But is this enough for the existence of the eigenvectors? The conclusion works in the other direction at least. If that determinant is non-zero, then eigenvectors don't exist.
 
Of course there is an eigenvector. That W is a subspace is irrelevant. W is a complex vector space and z restricts to an endomorphism of it, hence it has an e-vector. This is true if we replace C with any algebraically closed field. What is an e-vector? A root of the char poly. In particular t is an e-value of Z implies ker(Z-t) is not zere. Let v be any element of the kernel, hence (Z-t)v=0.
 
The matrix

<br /> A = <br /> \left[\begin{array}{cc}<br /> 0 &amp; -1 \\<br /> 1 &amp; 0 \\<br /> \end{array}\right]<br />

gives linear mappings A:\mathbb{C}^2\to\mathbb{C}^2 and A:\mathbb{R}^2\to\mathbb{R}^2 so that A\mathbb{C}^2\subset\mathbb{C}^2 and A\mathbb{R}^2\subset\mathbb{R}^2. I can see that in the complex case vectors (1,-i) and (1,i) are eigenvectors with eigenvalues \pm i, but it doesn't look like that the eigenvectors exist in the real case.
 
To me, at least, the question is not whether eigenvectors exist but whether eigenvalues exist. If \lambda is an eigenvalue of A, then there exist non-0 v such that Av= \lambdav by definition of "eigenvalue".

Yes, some matrices, over the real numbers, do not have real eigenvalues- and so, since we are talking "over the real numbers" do not have eigenvalues. Since the complex numbers are algebraically closed, the "eigenvalue equation" always has a solution and so a matrix, over the complex numbers, always has at least one (complex) eigenvalue and so eigenvectors.
 
Okey, I missed the meaning of "algebraically closed" previously.
 
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