Proving the Direct Sum Decomposition of V using Linear Maps

In summary, null(T) is a subspace of V and for all u in V, u is not in null(T). For all n in V, n is in null(T). T(n) = 0, T(u) not= 0. The result of a = a' is enough to prove uniqueness for a direct sum.
  • #1
*melinda*
86
0

Homework Statement


Suppose that T is a linear map from V to F, where F is either R or C. Prove that if u is an element of V and u is not an element of null(T), then

V = null(T) (direct sum) {au : a is in F}.

2. Relevant information
null(T) is a subspace of V
For all u in V, u is not in null(T)
For all n in V, n is in null(T)
T(n) = 0, T(u) not= 0

The Attempt at a Solution


I think I should let U = {au : a is in F} and show that it's a subspace of V. Then I can show that each element of V can be written uniquely as a sum of u + n. Should I do this by showing that (u, n) is a basis for V?
 
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  • #2
What's the dimension of null(T) in terms of the dimension of V?
 
  • #3
if V were finite dimensional then I could say, dim{null(T)} = dim(V) - dim{range(T)}.

But nothing given in the problem statement will let me assume V is finite.
 
  • #4
Ok, I think I was thinking about this wrong. Suppose x=a*u+n and x=a'*u+n' where n and n' are in the null space. Then T(x)=a*T(u)=a'*T(u). Since T(u) is nonzero, a=a'. Right? So x=a*u+n and x=a*u+n'. Can n and n' be different?
 
  • #5
n and n' could definitely be different, but I don't think it matters much since they both get mapped to zero.

Is the result of a = a' is enough to prove uniqueness for a direct sum?
 
  • #6
It does matter in V. But if x=a*u+n and x=a*u+n' (after you've shown a=a') then n=x-a*u and n'=x-a*u. Conclusion?
 
  • #7
Gosh, I must be getting sleepy to overlook the importance of n being unique.

So, I can show that each element of V can be written uniquely as a sum of u + n.

Should I also prove U = {au : a is in F} is a subspace of V
 
  • #8
*melinda* said:
Gosh, I must be getting sleepy to overlook the importance of n being unique.

So, I can show that each element of V can be written uniquely as a sum of u + n.

Should I also prove U = {au : a is in F} is a subspace of V

Even being sleepy, I think you could, right? I think it could actually be considered as 'obvious' and not deserving of proof.
 
  • #9
:zzz:

I should be able to stay awake long enough to write down my solution.

Thanks for the help!
 
  • #10
Very, very welcome.
 

1. What is linear algebra?

Linear algebra is a branch of mathematics that deals with linear equations and their representations in vector spaces. It encompasses the study of linear equations, matrices, vector spaces, and linear transformations.

2. What are linear maps?

Linear maps, also known as linear transformations, are functions that preserve vector addition and scalar multiplication. In other words, they map one vector space to another while preserving the structure of the space.

3. How are linear maps represented?

Linear maps can be represented in various ways, such as through matrices, system of linear equations, or function notation. Matrices are the most common and convenient representation of linear maps, where each column represents the image of a basis vector.

4. What are the applications of linear algebra and linear maps?

Linear algebra and linear maps have numerous applications in various fields such as engineering, physics, computer graphics, economics, and statistics. They are used to solve systems of equations, analyze data, and model real-world situations.

5. What are eigenvectors and eigenvalues in linear algebra?

Eigenvectors and eigenvalues are concepts used in linear algebra to study linear maps. An eigenvector is a non-zero vector that remains in the same direction after being transformed by a linear map. The corresponding eigenvalue is a scalar that represents the stretching or shrinking factor of the eigenvector under the linear map.

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