Invariant subspaces of representations

In summary, the conversation discusses a linear representation of a finite group and its invariant subspaces. The representation is given by a matrix A and it is asked whether there are any one-dimensional invariant subspaces. The conversation then delves into the definition of a linear representation and the properties of invariant subspaces. Finally, it is concluded that the only possible one-dimensional invariant subspace is spanned by the eigenvector (1,1,1) of A, but it may not contain all the elements of the representation.
  • #1
Carla1985
94
0
Let $\varrho :\mathbb{Z}\rightarrow GL_3(\mathbb{R})$ be the representation given by $\varrho (n)=A^n$ where

A=$\begin{pmatrix}
2 & 5 & -1 \\
2 & \frac{5}{2} & \frac{11}{2} \\
6 & \frac{-2}{2} & \frac{3}{2} \\
\end{pmatrix}$

Does ρ have any 1-dimensional invariant subspaces? Do I have to divide up the elements in the representation with their corresponding eigenvectors. I know From $A^4$ the matrix is just a scaler of the previous 4, i.e. $A^4=I$, $A^5=A$ etc and their eigenvectors are the same then?

Im struggling to understand this chapter we are doing a little so any help is much appreciated.

Carla x
 
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  • #2
Carla1985 said:
Let $\varrho :\mathbb{Z}\rightarrow GL_3(\mathbb{R})$ be the representation given by $\varrho (n)=A^n$ where

A=$\begin{pmatrix}
2 & 5 & -1 \\
2 & \frac{5}{2} & \frac{11}{2} \\
6 & \frac{-2}{2} & \frac{3}{2} \\
\end{pmatrix}$

Does ρ have any 1-dimensional invariant subspaces? Do I have to divide up the elements in the representation with their corresponding eigenvectors. I know From $A^4$ the matrix is just a scaler of the previous 4, i.e. $A^4=I$, $A^5=A$ etc and their eigenvectors are the same then?

Im struggling to understand this chapter we are doing a little so any help is much appreciated.

Carla x

Hey Carla! :)Here's a definition from http://www.win.tue.nl/~aeb/2WF02/fgreps.pdf:

Let G be a finite group.
A linear representation of G is a homomorphism ρ : G → GL(V ) where GL(V ) is the group of invertable linear transformations of the vector space V.
A subspace W of V is called ρ(G)-invariant if ρ(g)W ⊆ W for all g ∈ G.
A 1-dimensional subspace of $\mathbb R^3$ would be the span of some vector $v$.
So $W = \{\mu v : \mu \in \mathbb R \}$.

What we need is that $\varrho(n)W ⊆ W$ for all $n \in \mathbb Z$.
What does this expand to for, say, $n=1$?

ILS x
 
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  • #3
Carla1985 said:
Let $\varrho :\mathbb{Z}\rightarrow GL_3(\mathbb{R})$ be the representation given by $\varrho (n)=A^n$ where

A=$\begin{pmatrix}
2 & 5 & -1 \\
2 & \frac{5}{2} & \frac{11}{2} \\
6 & \frac{-2}{2} & \frac{3}{2} \\
\end{pmatrix}$

Does ρ have any 1-dimensional invariant subspaces? Do I have to divide up the elements in the representation with their corresponding eigenvectors. I know From $A^4$ the matrix is just a scaler of the previous 4, i.e. $A^4=I$, $A^5=A$ etc and their eigenvectors are the same then?

Im struggling to understand this chapter we are doing a little so any help is much appreciated.

Carla x

Let $G = \mathbb{Z}$ be additive group.
Let $V = \mathbb{R}^3$ be real vector space.
With linear action of $G$ on $V$ given by,
$$ n\cdot x = A^n x \text{ for }n \in G, x\in V$$

Say $W$ is a one-dimensional subspace of $V$, so $W = \left< w \right>$ is spanned by a non-zero vector in $\mathbb{R}^3$. Since $W$ is invariant under $G$ it means in particular that $1\cdot w \in W$, in other words, $Aw = kw$ for some $k\in \mathbb{R}$.

This shows that an invariant one-dimensional subspace of $V$ must be spanned by an eigenvector of $A$. Now look for the eigenvectors.
 
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  • #4
I like Serena said:
Hey Carla! :)Here's a definition from http://www.win.tue.nl/~aeb/2WF02/fgreps.pdf:
Let G be a finite group.
A linear representation of G is a homomorphism ρ : G → GL(V ) where GL(V ) is the group of invertable linear transformations of the vector space V.
A subspace W of V is called ρ(G)-invariant if ρ(g)W ⊆ W for all g ∈ G.
A 1-dimensional subspace of $\mathbb R^3$ would be the span of some vector $v$.
So $W = \{\mu v : \mu \in \mathbb R \}$.

What we need is that $\varrho(n)W ⊆ W$ for all $n \in \mathbb Z$.
What does this expand to for, say, $n=1$?

ILS x

With n=1 I have $AW⊆W$

The only eigenvector for A is (1,1,1). Does this mean my span and the invariant subspace would be W ={(x,x,x)∈R3 |x∈R}?

There are elements of the representation that don't fall into this though (every 4th element), is that ok?

Thanks, I think I'm slowly starting to understand it, I know my brain is on a go slow not helped by the fact I was up at 5am with the kids this morning :p
 
  • #5
Carla1985 said:
With n=1 I have $AW⊆W$

More specifically $\varrho(1)W = \{\varrho(1)\mu v : \mu \in \mathbb R \}
= \{\mu A v : \mu \in \mathbb R \}$.
This is only contained in $W$ iff $v$ is an eigenvector of $A$.
The only eigenvector for A is (1,1,1). Does this mean my span and the invariant subspace would be W ={(x,x,x)∈R3 |x∈R}?

That would be the only candidate then.
There are elements of the representation that don't fall into this though (every 4th element), is that ok?

I assume you are referring to $\varrho(4) = A^4$, which is apparently equal to $I$?
If so, is $I(1,1,1) \in W = \{\mu (1,1,1) : \mu \in \mathbb R \}$?
 
  • #6
Carla1985 said:
The only eigenvector for A is (1,1,1). Does this mean my span and the invariant subspace would be W ={(x,x,x)∈R3 |x∈R}?


I did not compute the eigenvectors of A but assuming it is (1,1,1) then you are correct that W = <(1,1,1)> which is exactly how you described it.

There are elements of the representation that don't fall into this though (every 4th element), is that ok?


What do you mean by that?
 
  • #7
I think there is a typo in your original matrix.

I believe the matrix actually under consideration must be:

\(\displaystyle A = \begin{bmatrix}2&5&-1\\-2&\frac{5}{2}&\frac{11}{2}\\6&-\frac{3}{2}&\frac{3}{2} \end{bmatrix}\)

which satisfies:

$A^4 - 1296I = 0$

(1,1,1) is indeed an eigenvalue of this matrix, and since $A$ satisfies the polynomial:

$x^4 - 1296 = (x^2 + 36)(x + 6)(x - 6)$

any eigenvalue must be a root of this polynomial (so we have just two possible eigenvalues, 6 and -6).

It turns out the characteristic polynomial is $(x - 6)(x^2 + 36)$, which rules out -6 as an eigenvalue. Solving for $E_6$ we find the space is indeed spanned by (1,1,1).

It is trivial that if:

$Av = \lambda v$ that:

$A^kv = \lambda^kv$

so any power of $A$ has the same eigenvectors as $A$.

Thus $\langle(1,1,1)\rangle = E_6$ is indeed a one-dimensional invariant subspace of $\rho$.
 
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  • #8
Hi, thanks all, I woke up this morning and it all started to make sense (eventually!). Here's how I have wrote it all out, hopefully its right lol:

We need to find a 1 dimensional subspace of $\mathbb{R}^3$, call this U. As its 1 dimensional subspace then any element of U is an eigenvector of $\varrho (n)$ with corresponding eigenvalue $\lambda_n$.

Since A has eigenvector (1,1,1) with eigenvalue 6 then (1,1,1) is our 1 dimensional basis element, call this u.

So $Au=6u$

And then:
$A^2u=A\lambda u=\lambda(Au)=\lambda(\lambda u)=\lambda^2u$

So then for any value of n:
$A^n u=\lambda^n u$

ie:
$\varrho (n)(u)=\lambda^n (u)\ \ \forall n \in \mathbb{N}$

Hence every element of U is a scaler multiple of u and U is a 1 dimensional invariant subspace of U.

Carla x
 
  • #9
Looks fine to me! :)

ILS x
 
  • #10
Looks good.
 

FAQ: Invariant subspaces of representations

What are invariant subspaces of representations?

Invariant subspaces of representations are subspaces of a vector space that are preserved under the action of a group or algebraic structure. This means that any element in the subspace remains in the subspace after applying a transformation from the group or algebra.

Why are invariant subspaces important in representation theory?

Invariant subspaces help to simplify the study of representations by breaking them down into smaller, more manageable pieces. They also provide insight into the structure of the representation and can help to identify important substructures within it.

How are invariant subspaces related to symmetry?

Invariant subspaces are closely related to symmetry because they are preserved under transformations from a group or algebra, which is a fundamental aspect of symmetry. Invariant subspaces can also help to identify symmetries within a representation.

Can invariant subspaces be used to classify representations?

Yes, invariant subspaces can be used as a tool for classifying representations. By identifying the invariant subspaces within a representation, we can break it down into simpler components and classify them based on their properties.

Are there any real-world applications of invariant subspaces of representations?

Yes, invariant subspaces have many applications in physics, chemistry, and engineering. For example, they are used in the study of molecular vibrations and the analysis of quantum systems. They are also used in signal processing and control systems design.

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