Injective and Surjective linear transformations

In summary, the conversation discusses the concepts of injectivity and surjectivity in relation to linear maps and matrices. The participants also touch upon the alternative theorem, which states that for vector spaces of the same dimension, an isomorphism is equivalent to being injective or surjective. They also provide examples to illustrate the differences between these concepts and how they relate to the invertibility of a matrix.
  • #1
AntsyPants
9
0
I was struck with the following question: Is there a linear map that's injective, but not surjective? I know full well the difference between the concepts, but I'll explain why I have this question.

Given two finite spaces [itex]V[/itex] and [itex]W[/itex] and a transformation [itex]T: V→W[/itex] represented by a matrix [itex]\textbf{A}[/itex], we know that [itex]T[/itex] is invertible if and only if there is a one-to-one mapping between spaces, which means, [itex]\textbf{A}[/itex] is invertible.

On the other hand, we know that [itex]T[/itex] is surjective if its image space can generate [itex]W[/itex]. The image space is related with the column space of [itex]\textbf{A}[/itex], so let's consider the system

[itex]\textbf{A v} = \textbf{w}[/itex]

where [itex]\textbf{v}[/itex] and [itex]\textbf{w}[/itex] are the coordinates of an element of [itex]V[/itex] and [itex]W[/itex], respectively. If [itex]\textbf{A}[/itex] is invertible than this system is always possible, meaning we can obtain any element of [itex]W[/itex] from an element of [itex]V[/itex], so [itex]T[/itex] must also be surjective.

Perhaps I didn't formulate this right and I may be doing some mistake somewhere, but it's just a simple curiosity.
 
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  • #2
I'm guessing you are using the following Alternative theorem:

Let V and W be vector spaces of the same dimension and let [itex]T:V\rightarrow W[/itex] be linear, then the following are equivalent
1) T is an isomorphism
2) T is injective
3) T is surjective

This only holds for spaces of the same dimension! For spaces not of the same dimension, this is clearly false! (indeed, because the matrix A in that case is not even rectangular)
 
  • #3
Yes I assumed they were of the same dimension, otherwise it wouldn't be invertible, but I have a problem with your statement. Consider for instance the projection

[itex]T(x,y) = (x,0)[/itex]

[itex]T[/itex] receives a bidimensional vector and also returns one, so[itex]T:R^{2}→R^{2}[/itex]. The spaces are of the same dimension, but don't satisfy any of 1)-3).
 
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  • #4
"T is invertible if and only if there is a one-to-one mapping between spaces, which means, A is invertible."

Not so, actually. There exist one-to-one mappings from ℝ2→ℝ3, just not continuous ones. The point of interest isn't whether one exists, but whether T is that one-to-one mapping. You may have known that and just put the wrong word though.

"The spaces are of the same dimension, but don't satisfy any of 1)-3)."

He said the three are equivalent, not that they are true. What he means is that if anyone of the three hold, then so do the other too. In your example, none of them hold, which is okay.

No back to the original question. Try the map T:V→W, where V is dimension 2 and W is dimension 3, defined by

T(x,y) = (x,y,0).

It's essentially the identity map into the bigger space, so it's injective. However, since W is higher dimension, there's no way for it to be a surjection.
 
  • #5
AntsyPants said:
Consider for instance the projection

[itex]T(x,y) = (x,0)[/itex]

[itex]T[/itex] receives a bidimensional vector and also returns one, so[itex]T:R^{2}→R^{2}[/itex]. The spaces are of the same dimension, but don't satisfy any of 1)-3).
Right. But to say that the statements 1-3 are equivalent is to say that either they're all true or they're all false. So your example doesn't contradict what micromass said.
 

1. What is the difference between an injective and a surjective linear transformation?

An injective linear transformation is one-to-one, meaning that each element in the domain maps to a unique element in the range. A surjective linear transformation is onto, meaning that every element in the range has at least one corresponding element in the domain.

2. How can I determine if a linear transformation is injective or surjective?

To determine if a linear transformation is injective, you can check if the kernel (null space) of the transformation is equal to 0. If it is, then the transformation is injective. To determine if a linear transformation is surjective, you can check if the range of the transformation is equal to the entire codomain. If it is, then the transformation is surjective.

3. Can a linear transformation be both injective and surjective?

Yes, a linear transformation can be both injective and surjective. This type of transformation is called a bijective linear transformation.

4. How do injective and surjective linear transformations relate to the concept of dimension?

Injective linear transformations preserve dimension, meaning that the dimension of the domain and the dimension of the range are equal. Surjective linear transformations can decrease the dimension of the domain, but cannot increase it. This means that the dimension of the range is less than or equal to the dimension of the domain.

5. What is the significance of injective and surjective linear transformations in mathematics and other fields?

Injective and surjective linear transformations are important concepts in mathematics because they help us understand the relationship between the domain and range of a function. In other fields, such as computer science and engineering, these concepts are used in data compression, image processing, and signal analysis, among others.

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