Explaining Minimal Polynomial of Matrix A

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Discussion Overview

The discussion revolves around the minimal polynomial of a given matrix A, exploring its relationship with the characteristic polynomial. Participants engage with theoretical aspects, mathematical reasoning, and specific examples, including a second matrix B with the same characteristic polynomial but differing minimal polynomial behavior.

Discussion Character

  • Technical explanation
  • Mathematical reasoning
  • Debate/contested

Main Points Raised

  • One participant presents matrix A and its characteristic polynomial, seeking clarification on the calculation of the minimal polynomial.
  • Another participant suggests that checking for distinct roots in the characteristic polynomial can indicate the form of the minimal polynomial.
  • A participant points out an eigenvector associated with the eigenvalue 2, proposing that this could simplify the factorization of the characteristic polynomial.
  • Concerns are raised about the clarity of notation used in the discussion, specifically regarding the meaning of the "v" in the expression for the minimal polynomial.
  • One participant asserts that the minimal polynomial is derived from the characteristic polynomial by removing duplicate factors, but another counters that this is misleading and emphasizes the need for careful consideration of multiplicities.
  • A participant illustrates the concept of minimal polynomials with an example involving the derivative operator, highlighting the role of nilpotent matrices in determining the form of the minimal polynomial.
  • Another participant presents matrix B, which has the same characteristic polynomial as A but does not satisfy the same minimal polynomial, raising questions about the validity of the method used to determine the minimal polynomial.
  • Further clarification is sought regarding the relationship between the minimal polynomial and the characteristic polynomial, particularly concerning the treatment of repeated factors.

Areas of Agreement / Disagreement

Participants express differing views on the relationship between the minimal polynomial and the characteristic polynomial, particularly regarding the removal of duplicate factors and the conditions under which the minimal polynomial can be determined. The discussion remains unresolved with multiple competing perspectives on the topic.

Contextual Notes

Participants note limitations in the approach to determining the minimal polynomial, particularly regarding assumptions about the relationship between the characteristic polynomial and the minimal polynomial when dealing with matrices that share the same characteristic polynomial but have different minimal polynomial behaviors.

vabamyyr
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I have matrix A
[tex]\left(\begin{array}{ccc}6&2&-2\\-2&2&2\\2&2&2\end{array} \right)[/tex]

Its characteristic polynomial is
[tex] p(\lambda)=\lambda^3 - 10\lambda^2 + 32\lambda -32[/tex]

Finding minimal polynomial i get:
[tex](I\lambda-A)^\vee=\left(\begin{array}{ccc}\lambda-6&-2&2\\2&\lambda-2&-2\\-2&-2&\lambda-2\end{array}\right)^\vee[/tex]

I can't understand why this last result equals with
[tex]\left(\begin{array}{ccc}\lambda^2-4\lambda&-2\lambda+8&2\lambda-8\\2\lambda-8&\lambda^2-8\lambda+16&2\lambda-8\\-2\lambda+8&2\lambda-8&\lambda^2-8\lambda+16\end{array} \right)[/tex]
can someone explain?
 
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would you mind retypsetting that so it is more legible?
 
Oh, and if you check that the char poly has 3 distinct roots it will be its minimal poly. other than that, it is of the form (x-a)^2(x-b) a different from b or (x-a)^3, check if those happen and if they do the minimal polys are divisors of these and you can check which, A satisfies.
 
Also, you can observe right away that (0 1 0)T is an eigenvector with eigenvalue 2 (look at the middle column of A). So 2 is a root of your characteristic polynomial, which will make it easier for you to factor.
 
I guess I am on my own again.
 
Perhaps it would help if you explain what the "v" in
[tex](I\lambda-A)^\vee[/tex]
means!

In any case, it was explained to you that the minimal polynomial- the polynomial of smallest degree that A satisfies- is just the characteristic polynomial with duplicate factors removed. And it was pointed out that [itex]\lambda- 2[/itex] is a factor so it should be simple to determine all the factors. What more do you want?
 
vabamyyr said:
I guess I am on my own again.
No, we essentially answered your question for you. After having those questions answered, you went and edited your post and added some more stuff in (the stuff with the (A - xI)V[/sub]). If you edit a post, no one will notice any changes have been made unless they come and look at the thread i.e. when you edit it, the thread doesn't appear at the top of the "Linear & Abstract Algebra" forum like it would if you made a new post, and it doesn't appear when people search for "New Posts".

If you have a new question, make a new post or a new thread, don't edit an old post which every one thinks has already been answered. Moreover, it appears you only gave it less than 5 hours before complaining that "you're on your own again." Be more patient.
 
HallsofIvy said:
just the characteristic polynomial with duplicate factors removed.


That in my mind is a little misleading. It is the characteristic poly with 'unnecessary' duplicate factors removed in some sense.
 
I have matrix A
[tex]\left(\begin{array}{ccc}6&2&-2\\-2&2&2\\2&2&2\end{array} \right)[/tex]

Its characteristic polynomial is
[tex] p(\lambda)=\lambda^3 - 10\lambda^2 + 32\lambda -32[/tex]

when i factor it i get [tex]p(\lambda)=(2-\lambda)(\lambda-4)^2[/tex]
So removing the duplicate factor
[tex](\lambda-4)[/tex]
i get that minimal polynomial is
[tex](\psi)=(2-\lambda)(\lambda -4)[/tex]
and A really satisfies it.

But let's assume I have matrix B [tex]\left(\begin{array}{ccc}6&2&2\\-2&2&0\\0&0&2\end{array} \right)[/tex]

Its characteristic polynomial is the same as for A and following
the same method as HallsOfIvy pointed out i get the same
[tex]p(\psi)[/tex] for B as for A but when u put B into the equation
you don't get 0 so this method doesn't work.
 
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  • #10
Erm, no, as was pointed out you cannot *just* remove factors and assume that the minimal poly is the product of the distinct linear factors. All this tells you if indeed your manipulations are correct is that the minimal poly and the characterstic poly are the same. The method is correct, and has given you the minimal poly, it is just that you don't recognize this.

This was what I wished to clarify from HallsofIvy's post. The minimal poly is not the product of the distinct linear factors but the product of the distinct linear factors with the smallest multiplicity of each possible so that the matrix satisfies the polynomial.
 
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  • #11
to illustrate matt's point about repeated factors in mminimal polynomials, consider the derivative operator D, acting on functions. on the space spanned by the functions e^x and xe^x, the minimal polynomial is (D-1)^2. while on the span of e^x, it is just D-1.


expressed in matrices, i.e. stripped of all meaning, for the ordered basis e^x, xe^x, we get a matrix of D with columns [ 1 0]^t and [1 1]^t,

where ^t means transpose.:wink:

the point is that the matrix is not disgonalizable, but is a sum of a diagonal matrix (namely the identity matrix), and a "nilpotent matrix", here the matrix which is all zeroes except for a 1 in the upper right corner.

It is the rpoesence of this nilpotent summand which prevents the minimal polynomial from having distinct irreducible factors.


or think about the map D, on the space of polynomials of degree at most n-1. The eigenvalues are all zero, and the characteristic polynomial is D^n, which is also the minimal polynomial.:shy:
 
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