A question about the rank of the sum of linear transformations

In summary, L(V,W) stands for a linear transformation vector space from vector space V to W. The conversation discusses the relationship between the rank of linear transformations and the combination of their matrices. It is shown that the rank of the combined transformation is less than or equal to the sum of the ranks of the individual transformations. It is also mentioned that the image of the combined transformation is a subspace of the sum of the images of the individual transformations.
  • #1
sanctifier
58
0
Notations:
L(V,W) stands for a linear transformation vector space form vector space V to W.
rk(?) stands for the rank of "?".

Question:
Let τ,σ ∈L(V,W) , show that rk(τ + σ) ≤ rk(τ) + rk(σ).
I want to know wether the way I'm thinking is right or not, or there's a better explanation.
My thought is:
Since every linear tansformation is reprensted by a matrix, also is τ + σ. rk(τ) and rk(σ) roughly means the numbers of basis vectors of their own matrix column spaces, so the combination τ + σ only preserves the distinct basis vectors from the column spaces of the matirces of τ and σ, namely, rk(τ + σ) ≤ rk(τ) + rk(σ) holds.

Thanks for any help.
 
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  • #2
Show that the im(τ + σ) is a subspace of im(τ) + im(σ). Remember that in general, rk(τ) = dim(im(τ)).

(By im, I mean image.)
 
  • #3
adriank said:
Show that the im(τ + σ) is a subspace of im(τ) + im(σ). Remember that in general, rk(τ) = dim(im(τ)).

(By im, I mean image.)

Indeed, it's a simpler way to solve the question.

Thanks!
 

1. What is the rank of the sum of linear transformations?

The rank of the sum of linear transformations is equal to the minimum of the ranks of each individual linear transformation.

2. How do you calculate the rank of the sum of linear transformations?

To calculate the rank of the sum of linear transformations, you would need to calculate the ranks of each individual linear transformation and then take the minimum of those ranks.

3. Can the rank of the sum of linear transformations be greater than the rank of the individual linear transformations?

No, the rank of the sum of linear transformations can never be greater than the rank of the individual linear transformations. It can only be equal to or less than the minimum rank of the individual transformations.

4. Why is the rank of the sum of linear transformations important?

The rank of the sum of linear transformations is important because it helps us understand the dimension of the vector space that is spanned by the linear transformations. It also has important applications in fields such as linear algebra and functional analysis.

5. Are there any special cases where the rank of the sum of linear transformations may be different?

Yes, there are special cases where the rank of the sum of linear transformations may be different. For example, if one of the linear transformations is the identity transformation, then the rank of the sum will be equal to the rank of the other transformation. Additionally, if the linear transformations are not defined on the same vector space, the rank of the sum may also be different.

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