Minimal Polynomial A nxn Matrix

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Homework Help Overview

The discussion revolves around the minimal polynomial of an n x n matrix A, focusing on its relationship with the matrix's eigenvalues and their indices. Participants are exploring the expression for the minimal polynomial in terms of the distinct eigenvalues and their indices.

Discussion Character

  • Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants are questioning the definition of "index" and its implications for proving the expression for the minimal polynomial. There is a discussion about the relationship between the minimal polynomial and the characteristic polynomial, as well as the conditions under which the minimal polynomial can be determined.

Discussion Status

The discussion is ongoing, with participants providing definitions and clarifications regarding the index of eigenvalues. Some guidance has been offered regarding the properties of the minimal polynomial and its relationship to the characteristic polynomial, but no consensus has been reached on the proof itself.

Contextual Notes

There are references to specific definitions from literature, and participants are considering examples such as the zero and identity matrices to illustrate points about the minimal polynomial. The discussion also highlights the need for clarity on terms like "multiplicity" and "index" in this context.

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Let A be an n x n matrix; denote its distinct eigenvalues by a_1,...,a_k and denote the index of a_i by d_i. How do I prove that the minimal polynomial is then:

m_A(s) = (s-a_1)^d_1*...*(s-a_k)^d_k

?

The characterstic polynomial is defined as:

p_A(s) = (s-a_1)*...*(s-a_n);
 
Last edited:
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the index of a_i by d_i
What do you mean by index? If you mean "multiplicity", then you can't prove it. For example, consider the minimum polynomials of the zero and identity matrices. (1 and x-1, respectively)
 
The book defines the index as:

"N_m = N_m(a) the nullspace of (A-a*I)^m. The subspaces N_m consist of generalized eigenvectors; they are indexed increasingly, that is N_1 is included in N_2 is included in...

Since these are subspaces of a finite-dimensional space, they must be equal from a certain index on. We denote by d = d(a) the smallest such index, that is, N_d = N_(d+1) = ... but N_(d-1) /= N_d_j

d(a) is called the index of the eigenvalue a."

This is from Peter D. Lax's book on linear algebra.
 
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If f is the minimal polynomial of A, then f(A) is the zero matrix. So f(A)v = 0 for any vector. Does that help?
 
That is also true for the characteristic polynomial. I know that the characteristic polynomial can be divided by a minimal polynomial and I want to show that the minimal polynomial is equal to (s-a_1)^(d_1)*...*(s-a_k)^(d_k)
 
That is also true for the characteristic polynomial.
Right. But you want the smallest polynomial that satisfies what I wrote. So you first want to prove:

(s-a_1)^(d_1)*...*(s-a_k)^(d_k)

satisfies what I wrote, and then you want to prove that any proper factor of it does not. I think good choices of f(A)v will do that.
 

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