Prove a map of a space onto itself is bijective

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In summary, the conversation discusses the implications of a function being onto in a metric space, the existence of a bijection between two metric spaces, and the relationship between linear maps and matrices. It also touches on the concept of basis elements and its role in determining a linear mapping. The conversation ends with a question about whether every vector space has a basis, with the response that every finite dimensional vector space does and proving it for infinite dimensional vector spaces requires a theorem like Zorn's Lemma.
  • #1
pacificguy
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Hi,
Say F:A->A where A is a metric space and F is onto. I think it should be true that this implies that F is also one to one. Is there a way to formally prove this? Thanks.
 
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  • #2
Of course not. Let A be the set of natural numbers. Then F:A -> A by F(1)=1, F(2)=1, F(3)=2, F(4)=3,..F(k)=k-1

And of course A is a metric space with the standard absolute value

You need some other condition on F
 
  • #3
Oh I guess you're right. Ok if A and B are two metric spaces and there exists two onto functions F and G such that F:A->B and G:B->A, is there a way to prove that there exists a bijection mapping A to B? The reason I'm asking is because I'm trying to prove a comment from Rudin that says there is a bijection from the set of all Linear operators from R^n to R^m and the set of all real mxn matrices.
 
  • #4
The comment in Rudin doesn't really have anything to do with what you're talking about as far as I can tell.

Given a linear map, it is determined entirely by how it maps the basis elements of Rn. And you can find a matrix that maps each basis element to any point of your choosing in Rm. So given a linear map, you can find a matrix which is the same function (and obviously every matrix is a linear map) and hence the two sets are essentially equivalent
 
  • #5
So linearity is the key to the proof? Or does a topological vector space being finite dimensional also play a role when it comes to being able to uniquely determine a linear mapping by how it maps basis elements?

In other words, is the following statement true:

Given a linear mapping L from a topological vector space X onto a topological vector space Y, L is "determined entirely by how it maps the basis elements of X?"

I am looking at Functional Analysis "Big Rudin" page 16 Theorems 1.21 and 1.22 which relate local compactness of a topological vector space to that space necessarily having finite dimension.
 
  • #6
Edwin said:
So linearity is the key to the proof? Or does a topological vector space being finite dimensional also play a role when it comes to being able to uniquely determine a linear mapping by how it maps basis elements?

The finite dimensionality is important only for allowing you to actually write a matrix

In other words, is the following statement true:
Given a linear mapping L from a topological vector space X onto a topological vector space Y, L is "determined entirely by how it maps the basis elements of X?"

Of course. If you know how it maps the basis elements, then let v be in X.

[tex]v= \sum_{i=1}^{n} \alpha_i v_i[/tex] for some basis vectors vi and field elements [itex] \alpha_i[/itex]. But we know precisely how to calculate
[tex] L(\sum_{i=1}^{n} \alpha_i v_i)[/tex]

Note that X and Y being topological has nothing to do with it
 
  • #7
Does every vector space have a basis?
 
  • #8
Yes. The fact that every finite dimensional vector space has a basis is one of the basic theorems of Linear Algebra. The fact that every infinite dimensional vector space has a basis requires something like Zorn's Lemma.
 

1. What does it mean for a map of a space to be bijective?

A bijective map of a space is one that is both injective and surjective. This means that every point in the space has a unique image under the map, and every point in the image has a pre-image in the original space. In simpler terms, a bijective map is a one-to-one and onto mapping.

2. Why is it important to prove that a map of a space is bijective?

Proving that a map is bijective is important because it guarantees that the mapping is well-defined and reversible. This means that every point in the original space has a unique image, and every point in the image has a pre-image in the original space. It also ensures that the map preserves the structure of the space, which is important in many mathematical and scientific applications.

3. How do you prove that a map of a space is bijective?

To prove that a map of a space is bijective, you must show that it is both injective and surjective. This can be done using various methods, such as using the definition of injectivity and surjectivity, or using mathematical techniques such as the pigeonhole principle or proof by contradiction. It is also important to carefully define the map and its domain and codomain before attempting to prove its bijectivity.

4. Can a map of a space be bijective if it is not continuous?

Yes, a map of a space can still be bijective even if it is not continuous. Bijectivity is a property of the mapping itself, while continuity is a property of the map's behavior. While many bijective maps are also continuous, it is possible for a bijective map to be discontinuous. However, in many cases, continuity is desired or assumed in order to preserve the structure and properties of the space.

5. Are there any specific examples of maps of a space that are always bijective?

Yes, there are some specific examples of maps of a space that are always bijective. One example is the identity map, where every point in the space is mapped to itself. Another example is the inverse function, where the map is bijective if and only if its inverse exists. In general, bijectivity depends on the specific mapping and its domain and codomain, so it is not always possible to determine if a map is bijective without further information.

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