What is the nullspace of (A-2E)^2?

In summary, the authors discuss how to put a matrix in Jordan canonical form. They start with a 4x4 matrix that is less full and transform it to a quasi-diagonal form. They go on to say that vectors in the null space of ([A]' - 2[E])^3 are also in the null space of ([A]' - 2[E])^2. This, they say, shows that A has no generalized eigenvectors of rank 3. They seem to be assuming that if ([A]'-2[E])^2 [v]' = 0 then (A-2E)^2 |v> = 0 (|v> is a vector without reference to a particular basis,
  • #1
Geofleur
Science Advisor
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Please note: Below, I keep trying to put [ capital B ] but it gets turned into !

In Dennery and Krzywicki, they give an example of how to put a matrix in Jordan canonical form (pp. 167-170). They start with a 4x4 matrix [A] that looks kind of messy and transform it to a quasi-diagonal form [A]' = [B^(-1)] [A] that is less full (I'm distinguishing between operators A and their matrix representations [A]). So far so good.

They go on to say that vectors in the null space of (A-2E)^3 are also in the null space of ([A]' - 2[E])^2. This, they say, shows that A has no generalized eigenvectors of rank 3. They seem to be assuming that if ([A]'-2[E])^2 [v]' = 0 then (A-2E)^2 |v> = 0 (|v> is a vector without reference to a particular basis, and [v]' = [B^(-1)] [v]). Then they would have

(A-2E)^3 |v> = 0 implies that (A-2E)^2 |v> = 0

and this statement does indeed seem incompatible with the existence of a generalized eigenvector of rank 3 for A.

Now for my big confusion:

If ([A]'-2[E])^2 [v]' = 0 is just a particular representation of (A-2E)^2 |v> = 0, then it would seem that so is ([A]-2[E])^2 [v] = 0. But

([A]'-2[E])^2 [v]' = ([B^(-1)] [A] - 2[E])^2 [B^(-1)] [v] =

[B^(-1)]^2 ([A] - 2[E])^2 ^2 [B^(-1)] [v] =

[B^(-1)]^2 ([A] - 2[E])^2 [v] = 0.

The operators ([A]'-2[E])^2 and ([A] - 2[E])^2 do not seem to have to same vectors in their nullspaces. There is a factor of that would have to be the identity matrix there in the last equation. So what, then, does it mean to talk about *the* nullspace of (A-2E)^2? What would particular representations of the operator look like?
 
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  • #2
That should be
[ A ]' = [ B-1 ] [ A ] [ B ]

[B] comes out looking like due to forum tags

it is obvious that ([ A ]'-2[ E ])2 and ([ A ] - 2[ E ])2 do have to same vectors in their nullspaces as

[ B ]([ A ]'-2[ E ])2=([ A ] - 2[ E ])2[ B ]
 
Last edited:
  • #3
I don't see how that last statement is true. If I replace [A]' with the similarity transformation and plug it into the equation on the left hand side, I don't see how the right hand side results. There would be a factor of the inverse of B squared, for instance, no?

Also, I don't see how equality on multiplying by the inverse of B implies equality of the nullspace vectors.
 
  • #4
Wait. Actually I do see it now. If you write the squared factors out explicitly and replace [A]' with the similarity transformation in each factor, the two operators I mentioned can be seen to have the same nullspace vectors. Thanks!

I should mention that before, I was pushing operators through several terms without realizing it. Writing out the factors explicitly kept me from doing that.
 
  • #5
Oops your right that should have been

[ B ]([ A ]'-2[ E ])2=([ A ] - 2[ E ])2[ B ]
 

1. What are generalized eigenvectors?

Generalized eigenvectors are a generalization of standard eigenvectors in linear algebra. They are defined as vectors that satisfy the equation (A - λI)^k v = 0, where A is a square matrix, λ is an eigenvalue of A, I is the identity matrix, and k is a positive integer.

2. How are generalized eigenvectors different from standard eigenvectors?

While standard eigenvectors are associated with a specific eigenvalue, generalized eigenvectors can be associated with multiple eigenvalues. Additionally, generalized eigenvectors can be used to find a basis for the nullspace of (A - λI)^k, which can be useful in solving systems of equations.

3. How are generalized eigenvectors computed?

Generalized eigenvectors can be computed by finding the Jordan canonical form of a matrix, which involves finding its eigenvalues and their corresponding eigenvectors. Then, the generalized eigenvectors can be found using the nullspace of (A - λI)^k for each eigenvalue.

4. What are the applications of generalized eigenvectors?

Generalized eigenvectors have many applications in mathematics and science, particularly in solving systems of linear differential equations, studying dynamic systems, and finding invariant subspaces. They can also be used in computer graphics and engineering to solve problems involving matrices and transformations.

5. Can generalized eigenvectors be complex?

Yes, generalized eigenvectors can be complex. Just like standard eigenvectors, they can be associated with complex eigenvalues. In fact, complex eigenvalues and eigenvectors often arise in systems that involve oscillations or rotations.

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