Prove a map of a space onto itself is bijective

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Discussion Overview

The discussion revolves around the properties of functions between metric spaces, particularly focusing on the implications of a function being onto and the conditions required for it to also be one-to-one. Participants explore related concepts in linear mappings and the relationship between linear operators and matrices.

Discussion Character

  • Exploratory
  • Technical explanation
  • Conceptual clarification
  • Debate/contested

Main Points Raised

  • One participant suggests that if a function F from a metric space A onto itself is onto, it should also be one-to-one, seeking a formal proof.
  • Another participant counters this by providing a counterexample using the set of natural numbers, indicating that additional conditions on F are necessary.
  • A later reply shifts the focus to the existence of two onto functions F and G between two metric spaces A and B, questioning whether this implies a bijection between A and B.
  • One participant discusses the relationship between linear maps and matrices, asserting that a linear map is determined by its action on basis elements of R^n.
  • There is a query about the role of finite dimensionality in determining linear mappings, specifically whether linearity alone suffices for this determination.
  • Another participant confirms that knowing how a linear mapping L acts on basis elements allows for the calculation of L on any vector in the space.
  • A question is raised regarding the existence of a basis for every vector space, leading to a clarification about finite and infinite dimensional vector spaces and the use of Zorn's Lemma.

Areas of Agreement / Disagreement

Participants express differing views on the implications of a function being onto and whether additional conditions are required for it to be one-to-one. There is also a lack of consensus on the necessity of finite dimensionality in determining linear mappings, as well as the existence of bases in vector spaces.

Contextual Notes

Participants reference specific theorems and concepts from functional analysis and linear algebra, indicating that the discussion may hinge on definitions and assumptions related to these areas.

Who May Find This Useful

This discussion may be of interest to students and professionals in mathematics, particularly those studying functional analysis, linear algebra, and the properties of metric spaces.

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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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
 
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.
 
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
 
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.
 
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.

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

Note that X and Y being topological has nothing to do with it
 
Does every vector space have a basis?
 
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.
 

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