Minimal vs Characteristic Polynomials

In summary, the characteristic polynomial and the minimal polynomial are the same up to a factor of +/- 1.
  • #1
cadillacclaire
2
0
Let T:V to V be a linear operator on an n-dimensional vector space V. Let T have n distinct eigenvalues. Prove that the minimal polynomial and the characteristic polynomial are identical up to a factor of +/- 1

I'm probably over thinking this, but it seems that if you have n distinct eigenvalues then the minimal polynomial would have to be EXACTLY the same as the characteristic. How could it be different?

Thanks in advance!
 
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  • #2
The characteristic polynomial for a matrix is the polynomial [itex]det(A- \lambda I)[/itex]. The minimal polynomial is the polynomial of least degree, p, such that p(A)= 0.

Yes, if an n by n matrix has n distinct eigevalues, [itex]\{\lambda_i\}[/itex], then, since eigenvectors corresponding to distinct eigenvalues are independent, there exist a basis for the space, [itex]\{\vec{v}_i\}[/itex], consisting of eigenvectors. In order that p(A)= 0 we must have [itex]p(A)(\vec{v}_i)= 0[/itex] for every such eigenvector and that means p(A) must have a factor of the form [itex](x- \lambda_i)[/itex] which, in turn, means that the minimal polynomial is the characteristic polynomial.

In fact, it is not necessary that all eigenvalues be distinct. If an n by n matrix has n independent eigenvectors (if it is diagonalizable) then the characteristic polynomial is the same as the minimal polynomial. If an eigenvalue, [itex]\lambda[/itex], has "algebraic multiplicity" (the number of factors of the form [itex](x- \lambda)[/itex] in the characteristic polynomial) n, then, by definition, the charactaristice polynomial has a factor of [itex](x- \lambda)^n[/itex]. If an eigenvalue, [itex]\lambda[/itex] has "geometric multiplicity" (the dimension of the subspace of eigenvectors corresponding to the eigenvalue) m, then the minimal polynomial contains the factor [itex](x-\lambda)^m[/itex].

So the characteristic polynomial is the same as the minimal polynomial if and only if the geometric multiplicity of every eigenvalue is the same as it algebraic multiplicity.
 
  • #3
Thanks for the quick reply. I think the problem itself was not worded very well and that's what threw me off. Good to know that I'm on the right track!
 

Related to Minimal vs Characteristic Polynomials

1. What is the difference between minimal and characteristic polynomials?

The minimal polynomial of a square matrix is the smallest degree monic polynomial that the matrix satisfies. The characteristic polynomial, on the other hand, is the polynomial whose roots are the eigenvalues of the matrix.

2. How are minimal and characteristic polynomials related?

The minimal polynomial divides the characteristic polynomial, meaning that the roots of the minimal polynomial are also roots of the characteristic polynomial. Additionally, the degree of the minimal polynomial is always less than or equal to the degree of the characteristic polynomial.

3. Can a matrix have multiple minimal and characteristic polynomials?

No, a matrix can only have one minimal polynomial and one characteristic polynomial. However, different matrices can have the same minimal and characteristic polynomials.

4. How are minimal and characteristic polynomials used in linear algebra?

Minimal and characteristic polynomials are important tools in finding the eigenvalues and eigenvectors of a matrix. They also play a role in determining the properties and behavior of a matrix, such as its diagonalizability and similarity to other matrices.

5. Is there a relationship between the minimal polynomial and the Jordan canonical form of a matrix?

Yes, the minimal polynomial of a matrix is the same as the minimal polynomial of its Jordan canonical form. Additionally, the characteristic polynomial of a matrix is the same as the characteristic polynomial of its Jordan canonical form, up to a constant factor.

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