Eigenvector existence in complex space

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Discussion Overview

The discussion revolves around the existence of eigenvectors in complex vector spaces, particularly in the context of matrices that map subspaces into themselves. Participants explore the implications of a matrix being a member of a solvable Lie algebra and the conditions under which eigenvectors can be guaranteed to exist.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested

Main Points Raised

  • One participant questions the claim that the existence of an eigenvector follows from a matrix mapping a subspace into itself, suggesting that this may not generally hold.
  • Another participant notes that the determinant equation has complex solutions, but questions whether this is sufficient for the existence of eigenvectors.
  • A different participant asserts that eigenvectors do exist in the complex case, arguing that the subspace being complex allows for the restriction of the matrix to be an endomorphism, thus guaranteeing an eigenvector.
  • One participant provides a specific matrix example, demonstrating that while eigenvectors exist in the complex case, they do not in the real case.
  • A participant emphasizes that the core question is about the existence of eigenvalues, stating that matrices over the complex numbers always have at least one eigenvalue due to the algebraically closed nature of the complex field.
  • Another participant acknowledges a misunderstanding regarding the term "algebraically closed" in relation to the discussion.

Areas of Agreement / Disagreement

Participants express differing views on the implications of a matrix mapping a subspace into itself regarding eigenvector existence. While some argue that eigenvectors exist in the complex case, others focus on the necessity of eigenvalues and the implications of working over the real numbers versus the complex numbers. The discussion remains unresolved regarding the generality of the initial claim.

Contextual Notes

Participants highlight the distinction between complex and real vector spaces, noting that the algebraically closed property of the complex numbers plays a crucial role in the existence of eigenvalues and eigenvectors. There is also an acknowledgment of the limitations of the discussion regarding the relevance of the subspace being complex or real.

jostpuur
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I'm reading a proof where there's a conclusion: "Since [itex]zW\subset W[/itex], there is an eigenvector [itex]v\neq 0[/itex] of z in W, [itex]zv=\lambda v[/itex]." There W is a subspace of some vector space V, and z is a matrix, in fact a member of some solvable Lie algebra [itex]\mathfrak{g}\subset\mathfrak{gl}(V)[/itex]. (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 [itex]W\subset\mathbb{C}^n[/itex] be a vector space, and A a matrix such that [itex]AW\subset W[/itex]. Then there exists an eigenvector [itex]v\in W[/itex] of the matrix A, so that [itex]Av=\lambda v[/itex] for some [itex]\lambda \in\mathbb{C}^n[/itex].
 
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hmhm... the equation

[tex] \textrm{det}(A-\lambda\cdot 1)=0[/tex]

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

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

gives linear mappings [itex]A:\mathbb{C}^2\to\mathbb{C}^2[/itex] and [itex]A:\mathbb{R}^2\to\mathbb{R}^2[/itex] so that [itex]A\mathbb{C}^2\subset\mathbb{C}^2[/itex] and [itex]A\mathbb{R}^2\subset\mathbb{R}^2[/itex]. I can see that in the complex case vectors (1,-i) and (1,i) are eigenvectors with eigenvalues [itex]\pm i[/itex], 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 [itex]\lambda[/itex] is an eigenvalue of A, then there exist non-0 v such that Av= [itex]\lambda[/itex]v 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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