Generalized vectors. Eigenvalues/Eigenvectors.

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Homework Help Overview

The discussion revolves around proving the linear independence of a single eigenvector and its associated generalized vector for a matrix with a single eigenvalue. The context is linear algebra, specifically focusing on eigenvalues and eigenvectors.

Discussion Character

  • Exploratory, Assumption checking, Conceptual clarification

Approaches and Questions Raised

  • Participants explore the implications of the definitions of eigenvectors and generalized vectors, questioning the linear independence of the vectors involved. There are attempts to apply the operator associated with the matrix to the vectors to derive relationships.

Discussion Status

Some participants have provided insights into the definitions of linear independence and have begun to apply these definitions to the problem. There is an ongoing exploration of the implications of the eigenvalue and eigenvector relationships, with various interpretations being discussed.

Contextual Notes

There are discussions about the nature of eigenvectors, particularly the assertion that a linear operator cannot have "one single eigenvector," which raises questions about the assumptions being made in the problem setup.

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Homework Statement



Let A \in M_{22} (\mathbb{R}) with one single eigenvalue λ and one single eigenvector v. We denote w the generalized vector such that (A - λI)w = v. Prove that v and w are linearly independent.

Homework Equations



I know that if A has only one eigenvalue λ and one eigenvector v that the equation Av = λv is satisfied. That is, (A - λI)v = 0.

The Attempt at a Solution



I thought about this a bit, but I'm having trouble getting this one going. I thought about letting B = (A - λI) so that we get two equations :

Bv = 0 and Bw = v

Then I thought that it could be broken down into two cases, one where λ = 0 and one where λ ≠ 0, but I'm not sure this is the right path to take.

Any pointers?
 
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Zondrina said:

Homework Statement



Let A \in M_{22} (\mathbb{R}) with one single eigenvalue λ and one single eigenvector v. We denote w the generalized vector such that (A - λI)w = v. Prove that v and w are linearly independent.

Homework Equations



I know that if A has only one eigenvalue λ and one eigenvector v that the equation Av = λv is satisfied. That is, (A - λI)v = 0.

The Attempt at a Solution



I thought about this a bit, but I'm having trouble getting this one going. I thought about letting B = (A - λI) so that we get two equations :

Bv = 0 and Bw = v

Then I thought that it could be broken down into two cases, one where λ = 0 and one where λ ≠ 0, but I'm not sure this is the right path to take.

Any pointers?

What's the definition of linearly independent?
 
There are several equivalent things, but if v_1, ..., v_n is a set of vectors, then v_1, ..., v_n are L.I if the equation :

c_1v_1, ..., c_nv_n = 0

has only a trivial solution. That is all the scalars are zero.
 
Zondrina said:
There are several equivalent things, but if v_1, ..., v_n is a set of vectors, then v_1, ..., v_n are L.I if the equation :

c_1v_1, ..., c_nv_n = 0

has only a trivial solution. That is all the scalars are zero.

That's the one. So if c1*v+c2*w=0 you want to show c1 and c2 are 0. Start by applying B to that equation. What do you conclude from that?
 
Last edited:
Okay so we want to show : c_1v + c_2w = 0 has only the trivial solution.

We know that if we multiply both sides by B = (A-λI) we get :

B(c_1v + c_2w) = 0
c_1Bv + c_2Bw = 0

We know that Bv = 0 because v is an eigenvector for the matrix A.

c_2Bw = 0

We also know that Bw = v since w is our generalized vector.

c_2v = 0

Now, since eigenvectors are non-zero, it must be the case that c2 = 0.
 
Zondrina said:
Okay so we want to show : c_1v + c_2w = 0 has only the trivial solution.

We know that if we multiply both sides by B = (A-λI) we get :

B(c_1v + c_2w) = 0
c_1Bv + c_2Bw = 0

We know that Bv = 0 because v is an eigenvector for the matrix A.

c_2Bw = 0

We also know that Bw = v since w is our generalized vector.

c_2v = 0

Now, since eigenvectors are non-zero, it must be the case that c2 = 0.

Sure. Now put c2=0 into your original equation. What do you conclude about c1?
 
Now subbing c2 back into our original equation yields :

c_1v = 0

Once again, since v is an eigenvector, it is non-zero. Which tells us that c1 must be zero.

Thus, c1 = c2 = 0 which implies that v and w are linearly independent.

EDIT : Q.E.D

Thanks.
 
Last edited:
Zondrina said:

Homework Statement



Let A \in M_{22} (\mathbb{R}) with one single eigenvalue λ and one single eigenvector v. We denote w the generalized vector such that (A - λI)w = v. Prove that v and w are linearly independent.

Homework Equations



I know that if A has only one eigenvalue λ and one eigenvector v that the equation Av = λv is satisfied. That is, (A - λI)v = 0.
That's true for any A such that \lambda is an eigenvalue with eigenvector v. The fact that A has only that eigenvalue and one independent eigenvector, tells you that there exist a vector u such that A- \lambda I)u\ne 0 but that (A- \lambda I)^2u= 0.

(It is never true that a linear operator has "one single eigenvector" because any multiple of an eigenvector is an eigenvector.)

The Attempt at a Solution



I thought about this a bit, but I'm having trouble getting this one going. I thought about letting B = (A - λI) so that we get two equations :

Bv = 0 and Bw = v

Then I thought that it could be broken down into two cases, one where λ = 0 and one where λ ≠ 0, but I'm not sure this is the right path to take.

Any pointers?
 

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