Dimension of Hom(K)(U,V) and Basis of the Vector Space

In summary, the dimension of Hom_K(U,V) is mxn. The basis of Hom(subscriptK)(U,V) is {u1...un} and {v1...vm}. Any linear transformation from U->V can be written in terms of these basis vectors.
  • #1
mathmathmad
50
0

Homework Statement


Let U and V be vector spaces of dimensions of n and m over K and let Hom(subscriptK)(U,V) be the vector space over K of all linear maps from U to V. Find the dimension and describe a basis of Hom(subscriptK)(U,V). (You may find it helpful to use the correspondence with mxn matrices over K)


Homework Equations





The Attempt at a Solution


is Hom(subscriptK)(U,V) a matrix that maps U to V?
I don't get what Hom(subscriptK)(U,V) is...
 
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  • #2
Hom_K(U,V) isn't 'a' matrix mapping U to V. It's the set of ALL matrices mapping U to V. K indicates the field the entries in the matrices are from (i.e. real, complex, etc, etc).
 
  • #3
How does one describe the basis in this case?
 
  • #4
vintwc said:
How does one describe the basis in this case?

Pick a basis {u1...un} for U and a basis {v1...vm} for V and think about a how to make a simple set of independent linear transformations whose span is all linear transformations.
 
  • #5
is the dimension of Hom_K(U,V) = mxn?
 
  • #6
mathmathmad said:
is the dimension of Hom_K(U,V) = mxn?

Yes. Can you show that by producing a basis?
 
  • #7
^ no... can you please show me how?
 
Last edited:
  • #8
mathmathmad said:
^ no... can you please show me how?

Describe SOME linear transformation from U->V in terms of the basis. ANY one.
 
  • #9
I am trying to prove this without using matrix form. I am using the transformation:
[tex]
$ T_{ij} $ ( i= 1, \ldots, n and j= 1,\ldots,m) as the linear transformation that does the following: \\
$ u_i \mapsto v_j \quad \text{ and } \quad u_{k \neq i} \mapsto 0 $
[/tex]
However I do not know where to start in proving these transformations are linearly independent. I am used to dealing with vectors and doing this kind of thing with a vector space of linear transformations is throwing me off.
 
Last edited:
  • #10
Ok, so linear independence means that sum over all i and j of a_ij*T_ij=0 implies ALL a_ij=0, right? Suppose a_KL is not zero. Put u_K into the transformation sum(a_ij*T_ij). That turns it sum(a_ij*T_ij(u_K)). What does that look like if you simplify to a single sum over j?
 
  • #11
Excellent, I understand much better how to work with linear combinations of these transformations. I get it now. Thanks
 
  • #12
Oh one last question, if I wanted to use einstein summation notation here could I just leave off both sum symbols?
ie. is
[tex]
\alpha_{ij}T_{ij} = 0
[/tex]
the same as
[tex]
\sum_{i=1}^{n} \sum_{j=1}^{m} \alpha_{ij}T_{ij} = 0
[/tex]
using einstein summation notation?
 
  • #13
LogicalTime said:
Oh one last question, if I wanted to use einstein summation notation here could I just leave off both sum symbols?
ie. is
[tex]
\alpha_{ij}T_{ij} = 0
[/tex]
the same as
[tex]
\sum_{i=1}^{n} \sum_{j=1}^{m} \alpha_{ij}T_{ij} = 0
[/tex]
using einstein summation notation?

Right. That's actually what I was writing. I put the 'sum' into make the sums were understood. Be sure you say you are using the Einstein summation convention, though. That's not automatically understood.
 
  • #14
cool, thanks again!
 

Related to Dimension of Hom(K)(U,V) and Basis of the Vector Space

1. What is the dimension of Hom(K)(U,V)?

The dimension of Hom(K)(U,V) is the number of linear transformations from the vector space U to the vector space V that can be represented as a linear combination of a given basis.

2. How is the dimension of Hom(K)(U,V) related to the dimensions of U and V?

The dimension of Hom(K)(U,V) is equal to the product of the dimensions of U and V. This means that if U has a dimension of m and V has a dimension of n, then the dimension of Hom(K)(U,V) is m x n.

3. Can the dimension of Hom(K)(U,V) be greater than the dimensions of U and V?

Yes, it is possible for the dimension of Hom(K)(U,V) to be greater than the dimensions of U and V. This would occur if the vector space U has a smaller dimension than V, but there are still enough linear transformations from U to V to span the entire space.

4. What is a basis of a vector space?

A basis of a vector space is a set of linearly independent vectors that span the entire space. This means that any vector in the space can be written as a unique linear combination of the basis vectors.

5. How do you find a basis for the vector space Hom(K)(U,V)?

To find a basis for Hom(K)(U,V), you need to first determine the dimensions of U and V. Then, you can create a basis for Hom(K)(U,V) by using the standard basis vectors for U and V. For example, if U has a dimension of m and V has a dimension of n, the standard basis for Hom(K)(U,V) would consist of all possible combinations of the m x n matrices with one entry of 1 and all other entries equal to 0.

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