About the invariance of similar linear operators and their minimal polynomial

In summary, the conversation discusses the invariance of minimal polynomials under similarity of linear operators on a vector space. It is stated that if two linear operators, τ and σ, are similar, then their minimal polynomials, mτ(x) and mσ(x), are equal. The concept of similarity is defined using dummy variables and the equation alpha = alpha*phi*phi^(-1) is given as an example. The conversation then delves into a specific example to demonstrate how the invariance of minimal polynomials is derived. The conversation concludes with the speaker seeking help with other questions related to linear and abstract algebra.
  • #1
sanctifier
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About the invariance of similar linear operators and their minimal polynomial

Notations:
F denotes a field
V denotes a vector space over F
L(V) denotes a vector space whose members are linear operators from V to V itself and its field is F, then L(V) is an algebra where multiplication is composition of functions.
τ, σ, φ denote distinct linear operators contained in L(V)
m?(x) denotes the minimal polynomial of the linear operator "?"
~ denotes the similarity of the left and right operand, e.g., if τ ~ σ, then τ = φσφ-1

Question:
If τ ~ σ are similar linear operators on V, then mτ(x) = mσ(x), i.e., the minimal polynomial is an invariant under similarity of operators.

I wonder how it's proved.

Thanks for any help!
 
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  • #2
Use dummy variables and factor them wisely, here is a taste

[itex] \alpha = \alpha\varphi\varphi^{-1}, \alpha\in\mathbb{F},\varphi\in\mathbb{V}[/itex]
 
  • #4
Because I am too cool!

just kidding, it says alpha = alpha*phi*phi^(-1) and alpha in F and phi in V.
 
  • #5
I still don't understand.
For example, suppose mτ(x) = s1+s2τ+s3τ2 = 0 and τ = φσφ-1,

then mτ(x) = s1+s2φσφ-1+s3φ2σ2-1)2 =0,

multiply (φ2)-1 on the left and φ2 on the right of the both sides of mτ(x)

we will get s1+s2φ-1σφ+s3σ2 = 0,
this doesn't equal to s1+s2σ+s3σ2 = 0, does it?

Ah, yes, now I know where I made a mistake, τ2 ≠φ2σ2-1)2

since τ2 = (φσφ-1)2 = φσφ-1φσφ-1
= φσ2φ-1,

then multiply φ-1 on the left and φ on the right of of the both sides of the equation mτ(x) = s1+s2φσφ-1+s3φσ2φ-1=0

we will get s1+s2σ+s3σ2 = 0

The property that τ2 = φσ2φ-1 I've explored before reaching this theorem, it seems I need more practice.

Thanks for reply, trambolin.

There are some other questions I posted in "Linear & Abstract Algebra" with no replies yet, maybe you can help me again, thanks a lot!

(This is not my mother language, please forgive the grammar mistakes I've made)
 

Related to About the invariance of similar linear operators and their minimal polynomial

1. What is the concept of invariance in similar linear operators?

The concept of invariance in similar linear operators refers to the property that two linear operators that have the same minimal polynomial are said to be similar. This means that they can be transformed into each other through a change of basis.

2. How is the minimal polynomial related to similar linear operators?

The minimal polynomial is the polynomial of least degree that when evaluated at a linear operator, gives the zero operator. Similar linear operators have the same minimal polynomial, which means they have the same characteristic polynomial and eigenvalues.

3. What is the significance of invariance in similar linear operators?

Invariance in similar linear operators is significant because it allows us to study and analyze linear operators by considering their minimal polynomial, which is often easier to compute. It also helps us understand the relationship between different operators and their corresponding matrices.

4. How can we determine if two linear operators are similar?

Two linear operators are similar if they have the same minimal polynomial. This can be verified by comparing their characteristic polynomials or by computing the Jordan canonical form of their corresponding matrices.

5. Can similar linear operators have different eigenvectors?

Yes, similar linear operators can have different eigenvectors. The eigenvectors of a linear operator depend on the choice of basis, and similar operators can have different bases. However, their eigenvalues will remain the same since they have the same minimal polynomial.

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