A question about minimal polynomials

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In summary, we are trying to find the monic polynomial of least degree that annihilates v with respect to A. This is equivalent to finding the coefficients c_0, c_1, c_2, c_3 such that c_0v + c_1 Av + c_2 A^2v + c_3 A^3 v = 0. By row reducing, we can solve for c_0 and c_1 in terms of c_2 and c_3.
  • #1
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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  • #2
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\\
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
 
  • #3
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\\
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?
 
  • #4
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
 
Last edited:

1. What is a minimal polynomial?

A minimal polynomial is the smallest degree polynomial with integer coefficients that has a given root. It is used to find the algebraic expression for a given root.

2. How is a minimal polynomial different from a characteristic polynomial?

A minimal polynomial has the smallest degree possible to express a root, while a characteristic polynomial is the polynomial whose roots are the eigenvalues of a given matrix.

3. Can a minimal polynomial have multiple roots?

Yes, a minimal polynomial can have multiple roots. This can happen when the given root has a higher multiplicity, meaning it appears as a root multiple times in the polynomial.

4. How is a minimal polynomial calculated?

The minimal polynomial for a given root can be calculated using the Cayley-Hamilton theorem, which states that a matrix satisfies its own characteristic polynomial. This theorem can be applied to find the minimal polynomial of a given matrix.

5. Why is the concept of minimal polynomials important?

Minimal polynomials are important in various areas of mathematics, including linear algebra and algebraic geometry. They are used to find algebraic expressions for roots and to understand the structure of certain mathematical objects. They also play a crucial role in solving polynomial equations and in studying the properties of matrices.

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