A question about minimal polynomials

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Homework Help Overview

The discussion revolves around the concept of minimal polynomials in the context of linear transformations and matrix representations. Participants are examining the annihilator of a vector with respect to a matrix and exploring the relationship between the minimal polynomial and the transformation induced by the matrix.

Discussion Character

  • Conceptual clarification, Mathematical reasoning, Problem interpretation

Approaches and Questions Raised

  • Participants discuss the construction of a matrix from a vector and its images under a linear transformation, followed by row reduction to determine its form. There are questions about the implications of the resulting matrix on the minimal polynomial and its relationship to the transformation defined by the matrix.

Discussion Status

Some participants have provided insights into the conditions for a polynomial to annihilate a vector and have derived relationships between coefficients in the polynomial. There is acknowledgment of a potential misunderstanding regarding the application of the minimal polynomial to the transformation.

Contextual Notes

Participants are working under the constraints of a homework assignment, which may impose specific requirements on the form of the polynomial and its relation to the transformation. There is an ongoing exploration of how the minimal polynomial relates to different vectors and subspaces.

Artusartos
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Let [itex]A \in M_n(F)[/itex] and [itex]v \in F^n[/itex].

Also...[itex][g \in F[x] : g(A)(v)=0] = Ann_A (v)[/itex] is an ideal in F[x], called the annihilator of v with respect to A. We know that [itex]g \in Ann_A(v)[/itex] if and only if f|g in F[x]. Let [itex]V = Span(v, Av, A^2v, ... , A^{k-1}v).[/itex]. V is the smallest A-invariant subspace containing v. We denote the fact by writing V=F[x]v. This corresponds to the F[x]-module structure on [itex]F^n[/itex] induced by multiplication by A. We also know that [itex]v, Av, A^2v, ... , A^{k-1}v[/itex] is a basis, B, of v.

Now...

A = [itex]\begin{bmatrix} 2 & 0 & 0 \\0 & 3 & 0 \\0 & 0 & 4 \end{bmatrix}[/itex]

v = [itex]\begin{bmatrix} 1 \\1 \\0 \end{bmatrix}[/itex]

This is what the professor told us:

You need to find the matrix [itex][v | Av | ... | A^{k-1}v | A^kv][/itex] and then row reduce it to echelon form...He said that we would get a matrix of the form:

[itex]\begin{bmatrix} I_k & X \\0 & 0\end{bmatrix}[/itex]...I couldn't really write this matrix the way I wanted to...but this is basically what he said. The first few columns and rows will give the identity matrix [itex]I_k[/itex]. Then you will have zeros below [itex]I_k[/itex]. On the right hand side of [itex]I_k[/itex], you will have a few columns (call it "X"), and zeros below it.

He said that the minimal polynomial of T depends on the first column of X.

So this is what I did:


Let N = [itex][v | Av | ... | A^{k-1}v | A^kv][/itex] = [itex]\begin{bmatrix} 1 & 2 & 4 & 8 \\1 & 3 & 9 & 27 \\0 & 0 & 0 & 0 \end{bmatrix}[/itex]

After row reducing, I got:

[itex]\begin{bmatrix} 1 & 0 & -6 & -30 \\0 & 1 & 5 & 19 \\0 & 0 & 0 & 0 \end{bmatrix}[/itex]

So the first 2 rows and 2 columns of this matrix is [itex]I_2[/itex], and there are zeros below it. Then we have X=[itex]\begin{bmatrix} -6 & -30 \\5 & 19 \end{bmatrix}[/itex]. According to what the professor said, the first column of X determins the minimal polynomial of T. So the minimal polynomial is 6 + 5x + x^2, right?

So, what is T?

The definition that he gave for T is "[itex]T: V \rightarrow V[/itex] be induced by multiplication by A: T(w) = Aw for [itex]w \in V[/itex].

In this case the basis is the first two columns of N. So, basically, they are v and Av. Since T is induced by multiplication by A...T has the columns A(v) and A(Av)=A^2v

so...

...we have T = [itex][Av | A^2v][/itex] = [itex]\begin{bmatrix} 2 & 4 \\3 & 19 \end{bmatrix}[/itex]

But this matrix does not satisfy the minimal polynomial. Can anybody please help me with this? Did I do something wrong?

Thanks in advance
 
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Artusartos said:
Let [itex]A \in M_n(F)[/itex] and [itex]v \in F^n[/itex].

Also...[itex][g \in F[x] : g(A)(v)=0] = Ann_A (v)[/itex] is an ideal in F[x], called the annihilator of v with respect to A. We know that [itex]g \in Ann_A(v)[/itex] if and only if f|g in F[x]. Let [itex]V = Span(v, Av, A^2v, ... , A^{k-1}v).[/itex]. V is the smallest A-invariant subspace containing v. We denote the fact by writing V=F[x]v. This corresponds to the F[x]-module structure on [itex]F^n[/itex] induced by multiplication by A. We also know that [itex]v, Av, A^2v, ... , A^{k-1}v[/itex] is a basis, B, of v.

Now...

A = [itex]\begin{bmatrix} 2 & 0 & 0 \\0 & 3 & 0 \\0 & 0 & 4 \end{bmatrix}[/itex]

v = [itex]\begin{bmatrix} 1 \\1 \\0 \end{bmatrix}[/itex]

This is what the professor told us:

You need to find the matrix [itex][v | Av | ... | A^{k-1}v | A^kv][/itex] and then row reduce it to echelon form...He said that we would get a matrix of the form:

[itex]\begin{bmatrix} I_k & X \\0 & 0\end{bmatrix}[/itex]...I couldn't really write this matrix the way I wanted to...but this is basically what he said. The first few columns and rows will give the identity matrix [itex]I_k[/itex]. Then you will have zeros below [itex]I_k[/itex]. On the right hand side of [itex]I_k[/itex], you will have a few columns (call it "X"), and zeros below it.

He said that the minimal polynomial of T depends on the first column of X.

So this is what I did:


Let N = [itex][v | Av | ... | A^{k-1}v | A^kv][/itex] = [itex]\begin{bmatrix} 1 & 2 & 4 & 8 \\1 & 3 & 9 & 27 \\0 & 0 & 0 & 0 \end{bmatrix}[/itex]

After row reducing, I got:

[itex]\begin{bmatrix} 1 & 0 & -6 & -30 \\0 & 1 & 5 & 19 \\0 & 0 & 0 & 0 \end{bmatrix}[/itex]

So the first 2 rows and 2 columns of this matrix is [itex]I_2[/itex], and there are zeros below it. Then we have X=[itex]\begin{bmatrix} -6 & -30 \\5 & 19 \end{bmatrix}[/itex]. According to what the professor said, the first column of X determins the minimal polynomial of T. So the minimal polynomial is 6 + 5x + x^2, right?

So, what is T?

The definition that he gave for T is "[itex]T: V \rightarrow V[/itex] be induced by multiplication by A: T(w) = Aw for [itex]w \in V[/itex].

In this case the basis is the first two columns of N. So, basically, they are v and Av. Since T is induced by multiplication by A...T has the columns A(v) and A(Av)=A^2v

so...

...we have T = [itex][Av | A^2v][/itex] = [itex]\begin{bmatrix} 2 & 4 \\3 & 19 \end{bmatrix}[/itex]

But this matrix does not satisfy the minimal polynomial. Can anybody please help me with this? Did I do something wrong?

Thanks in advance

I don't know what you are doing, but I understand you want to find the monic polynomial p of least degree such that p(A) annihilates v, so you want to find the ci that give you
[tex]c_0v + c_1 Av + c_2 A^2v + c_3 A^3 v = 0[/tex]
or
[tex] c_0 + 2c_1 + 4c_2 + 8c_3 = 0\\<br /> c_0 + 3c_1 + 9c_2 + 27c_3 = 0.[/tex]
Row reduction gives us a solution of some c in terms of the others:
[tex]c_0 = 6c_2 + 30c_3, \; c_1 = -5c_2 -19c_3.[/tex]
So, if we put c_3 = 0 and c_2 = 1 we get c_0 = 6 and c_1 = -5, hence the minimial polynomial of v is p(x) = x^2 - 5x + 6.

RGV
 
Ray Vickson said:
I don't know what you are doing, but I understand you want to find the monic polynomial p of least degree such that p(A) annihilates v, so you want to find the ci that give you
[tex]c_0v + c_1 Av + c_2 A^2v + c_3 A^3 v = 0[/tex]
or
[tex] c_0 + 2c_1 + 4c_2 + 8c_3 = 0\\<br /> c_0 + 3c_1 + 9c_2 + 27c_3 = 0.[/tex]
Row reduction gives us a solution of some c in terms of the others:
[tex]c_0 = 6c_2 + 30c_3, \; c_1 = -5c_2 -19c_3.[/tex]
So, if we put c_3 = 0 and c_2 = 1 we get c_0 = 6 and c_1 = -5, hence the minimial polynomial of v is p(x) = x^2 - 5x + 6.

RGV

Thanks a lot for answering
Actually, that's the same thing that I got...I accidentally wrote x^2 + 5x +6 instead of x^2 - 5x + 6. But the problem that I'm having is that...when I substitute T for x, I do not get zero...why?
 
Artusartos said:
Thanks a lot for answering
Actually, that's the same thing that I got...I accidentally wrote x^2 + 5x +6 instead of x^2 - 5x + 6. But the problem that I'm having is that...when I substitute T for x, I do not get zero...why?

I suspect that T and A are two ways of talking about the same thing: T is a transformation and A is its matrix representation with respect to a particular basis.

So, you are saying that you do not get A^2 - 5A + 6I = 0. Well, that just means that p(A) does not annihilate the whole vector space. That's OK: it DOES annihilate the two-dimensional subspace span{v, Av, A^2v} = span{v,Av} for the particular v you started with. To annihilate the whole space, you would need to find the minimal polynomial q for another starting vector w (so that q(A)w = 0) and then (maybe) take the least common multiple of the polynomials p(x) and q(x), or something similar.

RGV
 
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