Invariant spaces and eigenvector problem

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SUMMARY

The discussion centers on the properties of a 1-dimensional A-invariant subspace W in the context of linear algebra. It is established that every non-zero vector in W is indeed an eigenvector of the matrix A, provided that A is an n x n matrix. The participants clarify that while A.w = λ.w holds for any vector w in W, the eigenvalues λ must be consistent across all vectors in W due to its dimensionality. This leads to the conclusion that all non-zero vectors in W share the same eigenvalue.

PREREQUISITES
  • Understanding of linear algebra concepts, specifically eigenvectors and eigenvalues.
  • Familiarity with the definition of A-invariant subspaces.
  • Knowledge of matrix representations, particularly n x n matrices.
  • Basic proficiency in manipulating linear equations and vector spaces.
NEXT STEPS
  • Study the properties of eigenvalues and eigenvectors in linear transformations.
  • Learn about invariant subspaces and their implications in linear algebra.
  • Explore the relationship between matrix dimensions and eigenvalue multiplicity.
  • Investigate the implications of dimensionality on the uniqueness of eigenvalues.
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Students and educators in linear algebra, mathematicians exploring eigenvalue problems, and anyone seeking to deepen their understanding of invariant subspaces and their properties.

gottfried
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Homework Statement


Let W be a 1-dimensional subspace of V that is A-invariant. Show that every non zero vector in W is a eigenvector of A. [A element of Mn(F)]

The Attempt at a Solution



We know W is A-invariant therefore for all w in W A.w is in W. W is one dimensional which implies to me that A must therefore be a one by one matrix with an entry from F. Is this a correct assumption?

If so then A.w=λ.w where λ is an element of F which implies that all w in W are eigenvectors of A.

I'm new to this sort of linear algebra and therefore can't tell if I've made a blatant mistake?
 
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gottfried said:

Homework Statement


Let W be a 1-dimensional subspace of V that is A-invariant. Show that every non zero vector in W is a eigenvector of A. [A element of Mn(F)]

The Attempt at a Solution



We know W is A-invariant therefore for all w in W A.w is in W. W is one dimensional which implies to me that A must therefore be a one by one matrix with an entry from F. Is this a correct assumption?
No, in fact it makes no sense at all. Any n by n matrix can have "1-dimensional invarient subspace".

If so then A.w=λ.w where λ is an element of F which implies that all w in W are eigenvectors of A.
How did you arrive at that? If w is in the invariant subspace, W, then Aw is also in W and, since W is "1-dimensional", it must be a multiple of A. But it does not immediately follow that that multiple is the same for all vectors in W.

Suppose that u and v are different vectors in W. Then we can say that [itex]Au= \lambda_1 u[/itex] and that [itex]Av= \lambda v[/itex] but we cannot yet say that [itex]\lambda_1= \lambda_2[/itex]. To do that, we need to use the fact that W is "1-dimensional" again. Because of that, any vector in the subspace is a mutiple of any other (except 0). We can write u= xv so that Au= x(Av). What does that give you?

I'm new to this sort of linear algebra and therefore can't tell if I've made a blatant mistake?
 
Thanks for the help. I'm still a little confused though.

HallsofIvy said:
Suppose that u and v are different vectors in W. Then we can say that [itex]Au= \lambda_1 u[/itex] and that [itex]Av= \lambda v[/itex] but we cannot yet say that [itex]\lambda_1= \lambda_2[/itex].

Why do we need to show that the two λ's are the same. Isn't that [itex]Au= \lambda_1 u[/itex] sufficient because that is the definition of an eigenvector? Unless eigenvalues have to unique for each matrix?
 

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