Questions about the concept of subspace of linear transformation

In summary, if T is a finite dimensional subspace of L(V) and U is a finite dimensional subspace of V, then T(U) = {F(u) | F is in T, u is in U} is a subspace of V. Dim(T(U))<=(dim(T))(dim(U)) .
  • #1
bigheadsam
4
0
Hi all,
I have some questions about the concept of subspace of linear transformation and its dimension, when I try to prove following problems:
Prove T is a finite dimensional subspace of L(V) and U is a finite dimensional subspace of V, then
T(U) = {F(u) | F is in T, u is in U} is a subspace of V,
Dim(T(U))<=(dim(T))(dim(U))

What does “T is a finite dimensional subspace of L(V)” mean?
L1(v)+L2(v) = (L1+L2)(v)
aL1(v) = (aL1)(v) ?

and what is dim(T) and dim(T(U))?

Every Linear transformation has its Matrix format, dim(T) is dim(M(T))?
I am a fish in Linear algebra. Hope I explain my questions clearly.
 
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  • #2
bigheadsam said:
I am a fish in Linear algebra.

You are a fish in definitions, obviously. First of all, I assume that by L(V) you mean the vector space of all linear operators from some finite dimensional space V to V?
 
  • #3
radou said:
You are a fish in definitions, obviously. First of all, I assume that by L(V) you mean the vector space of all linear operators from some finite dimensional space V to V?

Yeah, L(V) means the vector space of all linear operators from finite dimensional space V to V.
 
  • #4
OK, so, first of all, I assume this is the problem statement:

Prove that, if T is a finite dimensional subspace of L(V) and U is a finite dimensional subspace of V, then
(i) T(U) = {F(u) | F is in T, u is in U} is a subspace of V,
(ii) Dim(T(U))<=(dim(T))(dim(U)) .

In general, if A : V --> W is a linear operator, and L is a subspace of V, then A(L) is a subspace of W. Do you know how to prove that?
 
  • #5
T(U) = {F(u) | F is in T, u is in U} is a subspace of V
If T is a subspace of V, then what do you mean by T(U)? If F is in T, then F is a vector in V. What do you mean by F(u)?
 
  • #6
HallsofIvy said:
If T is a subspace of V, then what do you mean by T(U)? If F is in T, then F is a vector in V. What do you mean by F(u)?

He said T was a subspace of L(V), not V.
 
  • #7
radou said:
In general, if A : V --> W is a linear operator, and L is a subspace of V, then A(L) is a subspace of W. Do you know how to prove that?

yeah, I know how to prove it.
I just has an idea of what does "T is a finite dimensional subspace of L(V)" mean.
Does It mean that T is a subset of one kind of operator and this subset must be closed under addition and scalar multiplication.
for example, the non-invertible operator is not a subspace of L(V), cause it is not closed under addition. [tex]\left(\begin{array}{cc}1&0\\0&0\end{array}\right)[/tex] and [tex]\left(\begin{array}{cc}0&0\\0&1\end{array}\right)[/tex] they are both non-invertible operator but their addition [tex]\left(\begin{array}{cc}1&0\\0&1\end{array}\right)[/tex] is invertible.
 
  • #8
bigheadsam said:
yeah, I know how to prove it.
I just has an idea of what does "T is a finite dimensional subspace of L(V)" mean.
Does It mean that T is a subset of one kind of operator and this subset must be closed under addition and scalar multiplication.

Yes, exactly.

For example, take some subspace M of V. We say that M is invariant under the operator A, if A(M) is in M. Now, for some fixed subspace M, take the set of all operators such that M is invariant for these operators. Then this set is a subspace of L(V).

Edit: perhaps a more instructive example of a subspace of L(V) would be the space of all continuous linear operators from V to V.
 
Last edited:
  • #9
Thank you radou.
I think I've already figured out how to prove the problem.
 

1. What is the definition of subspace in the context of linear transformations?

A subspace of a linear transformation is a subset of the vector space on which the transformation is defined, that also satisfies the properties of a vector space. This means that it must contain the zero vector, be closed under addition and scalar multiplication, and be closed under composition with the linear transformation.

2. How is the concept of subspace related to linear independence?

A subspace is considered linearly independent if none of its vectors can be expressed as a linear combination of the others. This means that a linear transformation can be uniquely determined by its action on a linearly independent set of vectors in its subspace.

3. Can a subspace of a linear transformation be infinite-dimensional?

Yes, a subspace can be infinite-dimensional as long as it satisfies the properties of a vector space. In fact, many important examples of subspaces, such as the solution space of a homogeneous system of linear equations, are infinite-dimensional.

4. How do you determine if a subset of a vector space is a subspace of a linear transformation?

To determine if a subset is a subspace, you can check if it contains the zero vector, is closed under addition and scalar multiplication, and is closed under composition with the linear transformation. You can also use the subspace criterion, which states that a subset is a subspace if and only if it is non-empty and closed under addition and scalar multiplication.

5. What is the importance of subspaces in linear algebra?

Subspaces are important in linear algebra because they provide a way to study the behavior of linear transformations on a smaller, more manageable set of vectors. They also allow us to better understand the structure of vector spaces and to solve systems of linear equations.

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