Is Every Diagonalizable Endomorphism Defined by a Simple Polynomial?

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Discussion Overview

The discussion revolves around the diagonalizability of endomorphisms in finite-dimensional vector spaces, specifically examining the conditions under which an endomorphism can be represented by a polynomial that factors into linear terms with distinct roots. Participants explore the implications of a polynomial annihilating an endomorphism and the relationship between eigenvalues and eigenspaces.

Discussion Character

  • Technical explanation
  • Conceptual clarification
  • Debate/contested
  • Mathematical reasoning

Main Points Raised

  • One participant presents a theorem regarding diagonalizability and the existence of a polynomial that can be factored into linear terms with distinct roots.
  • Another participant questions the assumption that every vector in the space is an eigenvector based on the polynomial condition.
  • A participant provides a specific example with a matrix representation of an endomorphism, illustrating confusion about eigenvectors and polynomial evaluations.
  • Concerns are raised about the implications of linear dependence in the context of the dimension of the vector space and the number of distinct eigenvalues.
  • One participant proposes a method to show that the endomorphism is diagonalizable by constructing polynomials that map vectors to eigenspaces.
  • Another participant expresses uncertainty about the notation and the correctness of their reasoning regarding the polynomial conditions.
  • Final contributions suggest that the proposed approach to diagonalizability may be correct, although some details remain unclear to participants.

Areas of Agreement / Disagreement

Participants express various levels of understanding and confusion regarding the conditions for diagonalizability. There is no consensus on the correctness of certain steps or the implications of the polynomial conditions, indicating ongoing debate and exploration of the topic.

Contextual Notes

Some participants note limitations in their understanding of the notation and the implications of linear dependence among vectors in relation to the dimension of the vector space. The discussion reflects a mix of correct reasoning and uncertainty about specific mathematical claims.

geoffrey159
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Hello, I am studying reduction of endomorphisms and I came across a theorem that I can't understand completely. It states that:

Theorem: Let ##E## be a finite dimensional ##K## vector space, ##K## sub-field of ##\mathbb{C}##, and ##f## be an endomorphism of ##E##. Then, ##f## is diagonalizable if and only if there exists a polynomial ##P## of ##K[X]##, such that ##P(f) = 0##, and ##P## can be written as a product of polynomials of degree 1, and its roots have order of multiplicity 1.

I understand the proof I have for the sufficient condition, but the proof for the necessary condition is hard to follow for me so I tried an alternate way. I would like you to tell me if this is correct please:

##\Leftarrow ## ) Assume that there exists distinct ##\lambda_i##'s for ##i = 1...p##, and a polynomial ##P## in the form ##P = a \prod_{i=1}^p (X - \lambda_i) ## such that ##P(f) = 0##.
I want to show that ##E = \bigoplus_{\lambda \in \text{Sp}(f) } E_{f,\lambda}##, which is a necessary and sufficient condition of diagonalizability.
We have that for any ##x\in E-\{0\}##, ## P(f)(x) = 0##. So there exists ##i \in \{ 1...p \}## such that ##f(x) = \lambda_i x##, and ##x## belongs to the eigenspace ##E_{f,\lambda_i}##. Therefore ##x\in \bigoplus_{\lambda \in \text{Sp}(f) } E_{f,\lambda}##, and ##E \subset \bigoplus_{\lambda \in \text{Sp}(f) } E_{f,\lambda}##. The other inclusion is trivial. So ##f## diagonalizable.
 
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geoffrey159 said:
We have that for any ##x\in E-\{0\}##, ## P(f)(x) = 0##. So there exists ##i \in \{ 1...p \}## such that ##f(x) = \lambda_i x##, and ##x## belongs to the eigenspace ##E_{f,\lambda_i}##.
I may be missing the obvious, but I don't understand this step. How can it be that each element of E is an eigenvector?
 
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If ##P(f) = 0##, then ##P(f)(x) = 0 ## for all ##x\in E##.
  1. If ##x = 0## then ##x \in E \cap \bigoplus_{\lambda \in \text{Sp}(f) } E_{f,\lambda}##
  2. If ##x\neq 0##, then ## 0 = P(f)(x) = a\prod_{i = 1}^p (f(x) - \lambda_i x)##. So at least one term in the product is equal to 0. Therefore, there exists ##i## such that ##f(x) - \lambda_i x = 0##, which means that ##x## belongs to the eigenspace associated to ##f## and eigenvalue ##\lambda_i##.
 
I'm very confused, and probably wasting your time, but let us take a trivial example.
##E={\mathbb C}²##, and ##f## the endomorphism represented (with the canonical basis) by the matrix ##\begin{pmatrix}1 & 0 \\
0 & 2 \end{pmatrix}##.
So ##f(a,b)=(a,2b)##, and ##P(X)=(X-1)(X-2)##.
Take ##x=(1,1)##. ##f(x)=(1,2)##, so ##x## is not an eigenvector of f.
But ##P(f(x))=f(f(x))-3f(x)+2x=f(1,2)-3(1,2)+2(1,1)=(1,4)-(3,6)+(2,2)=(0,0)##.
 
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Oooops, sorry it's me who's wasting your time, I realize I am completely confused with the notations. I need to re-do this. Sorry
 
proofreading
 
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geoffrey159 said:
Developping the polynomial ##Q(f)## as a sum, and setting ##n = \text{Card(Sp}(f))##, we see that for any vector ##x\in E##, the family ## (x,f(x),f^2(x),...,f^n(x))## is linearly dependent in ##E##. Therefore ## \text{dim}(E) \le n ##.
I'm somewhat troubled by this step, but maybe I'm wrong about the notation.
If I understood it correctly, ##{Sp}(f)## is the set of all eigenvalues of ##f##.

If that is indeed the case, ##n = \text{Card(Sp}(f))## is the number of eigenvalues of ##f##. You claim that ## \text{dim}(E) \le n ##. But that can't be true in general, because an endomorphism can have less distinct eigenvalues than the dimension of the vector space, and still be diagonalizable.

I also don't immediately see why the linearly dependence of the family ## (x,f(x),f^2(x),...,f^n(x))## for all x implies that ## \text{dim}(E) \le n ##.
 
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Lol, this is exactly the reason why I deleted my post :-) I need to work more on this. Thank you for your help
 
geoffrey159 said:
Lol, this is exactly the reason why I deleted my post :-) I need to work more on this. Thank you for your help
Ok, no problem. :)
 
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  • #10
But I'm not giving up on this, I want to find the solution :-)
 
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  • #11
Think I have it now.

In a previous post, we said that ##P(f) = 0## implies that the eigenvalues of ##f## are among the zeros of ##P##.
Then it had to be true that ## P(f) = 0 \iff Q(f) = 0 ##, where ##Q = \prod_{\lambda \in \text{Sp}(f)} (X - \lambda) ##.

Now I want to show that ## E = \bigoplus_{\lambda\in\text{Sp}(f)} \text{Ker}(f-\lambda e) ##. The inclusion ##\supset## is trivial, and we now want to show ##\subset##. We need to prove that any ##x\in E## has a decomposition over the eigenspaces of ##f## in the form ##x = x_1 + ... + x_n ##, where ##x_i \in \text{Ker}(f-\lambda_i e) ##.

That would be done if we could find ##n## polynomials ##Q_k## such that the endomorphism ##Q_k(f)## sends any ##x\in E## in the ##k##-th eigenspace and :
## 0 = Q(f) = e - \sum_{k=1}^n Q_k(f) ##.

So the following constraints must be satisfied:
  1. ##Q_k(f) \in \text{Ker}(f-\lambda_k e) \iff f(Q_k(f)) = \lambda_k Q_k(f) \iff X(f) \circ Q_k(f) = (\lambda_k e)(f)\circ Q_k(f) \iff ((X-\lambda_k ) Q_k)(f) =0 ##
  2. Existence of a non-zero constant ##\beta## such that ## Q = \beta \ (1 - \sum_{k=1}^n Q_k)##, and the ##Q_k##'s have the same degree as ##Q##.
So if ##Q_k## has the form ##Q_k = \alpha (X-\mu) \prod_{i\neq k} (X-\lambda_i)##, where ##\alpha,\mu## are constants to be determined, then the first constraint is satisfied, and ##Q_k## has the same degree as ##Q##. For the second constraint, we must satisfy that ## 1 - \sum_{k=1}^n Q_k ## has the same roots as ##Q##. So it seems logic to determine ##\alpha,\mu## such that ##Q_k(\lambda_i) = \delta_{ik} \iff \alpha = \frac{1}{(\lambda_k-\mu) \prod_{i\neq k} (\lambda_k - \lambda_i)}## and ##\mu## is not an eigenvalue of ##f##.

Finally, there exists a constant ##\beta \neq 0## such that ## Q = \beta (1 - \sum_{k=1}^n \frac{X-\mu}{\lambda_k -\mu} \prod_{i\neq k} \frac{ (X-\lambda_i)}{ (\lambda_k - \lambda_i)})##, and for any ##x\in E##, ##P(f)(x) = 0 \iff Q(f)(x) = 0 \Rightarrow x \in \bigoplus_{\lambda\in \text{Sp}(f)} \text{Ker}(f-\lambda e) ##, which proves that ##f## is diagonolizable.

Is it correct now ?
 
  • #12
Looks correct to me. I'm a little lost in your point 1) concerning the polynomials ##Q_k##, but the formula for these polynomials fits the bill.
 
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  • #13
Finally! That made me sweat ;-) Thank you very much Samy for your patience
 

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