Proof of Quotient Map Q: A -> R for Exam Review

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In summary, the conversation discusses the properties of a quotient map, q, obtained by restricting the projection pi_1 on a subspace A of RxR. It is shown that q is neither open nor closed, and the conversation explores finding examples to demonstrate this. One example is given, and the conversation mentions the possibility of considering subsets that are not saturated under the map to find more examples.
  • #1
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Im reviewing material for the exam and came across this question:
Let pi_1:RxR->R be the projection on the first coordinate.
Let A be the subspace of RxR consisitng of all points (x,y) s.t either x>=0 or (inclusive or) y=0.

let q:A->R be obtained by resticting pi_1. show that q is quotient map that is neither open nor closed.
now to show that it's quotient map is the easy task, I want to see if I grasp it correctly, the set [0,infinity)x{0} is closed and open in A, but q([0,infinity)x{0})=[0,infinity) isn't closed nor open in R, correct?
 
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  • #2
loop quantum gravity said:
the set [0,infinity)x{0} is closed and open in A, but q([0,infinity)x{0})=[0,infinity) isn't closed nor open in R, correct?


[0,inf)x{0} is certianly not closed and open because A is simply connected and so A itself and the empty set are the only closed&open sets.

I guess you will have to find two sets, one closed, the other open, such that their image is not closed (open).
 
  • #3
I understand that [0,infinity) is closed in R, cause it's the complement of (-infinity,0) which is open in R.
So how to find such examples?
I mean for example a closed set in A would be an intersection of A with a closed set in RxR, now because q gives us only the first coordinate, then A obviously consists of all the points of the form: [0,infinity)xR and Rx{0}, which means that the map of such sets under q would be: subsets of [0,infinity) or R.
I don't see any example that shows what i need.
 
  • #4
RxR, now because q gives us only the first coordinate, then A obviously consists of all the points of the form: [0,infinity)xR and Rx{0}, which means that the map of such sets under q would be: subsets of [0,infinity) or R.
I don't see any example that shows what i need.[/QUOTE].


I think the standard example is that of the subset A={ (x,y) in IR^2 : yx=1 }.




I don't know of a general way of generating (counter) examples, but there is

a result that quotient maps take saturated open ( equiv. closed) sets to

open (equiv. closed) sets. So if you can consider subsets that are not saturated

under your map, this should help.
 

1. What is a quotient map?

A quotient map is a type of function in mathematics that maps elements from one set to another set by identifying certain elements as equivalent. This allows for a partitioning of the original set into smaller subsets.

2. What is the purpose of a proof of quotient map for exam review?

The purpose of a proof of quotient map for exam review is to demonstrate a clear understanding of the concept and its properties, and to provide evidence for its validity and applicability in various mathematical contexts.

3. How is a quotient map different from other types of maps?

A quotient map differs from other types of maps, such as injective, surjective, or bijective maps, in that it does not necessarily preserve individual elements or their uniqueness. Instead, it focuses on the relationship between elements and their equivalence.

4. Can a quotient map be bijective?

No, a quotient map cannot be bijective because it does not necessarily preserve the uniqueness of elements in the original set. This means that there can be multiple elements in the original set that are mapped to the same element in the quotient set.

5. What are some real-world applications of quotient maps?

Quotient maps have various applications in fields such as topology, group theory, and algebra. They can be used to study the structure of spaces, define equivalence relations, and classify objects with similar properties. In real-world scenarios, quotient maps can be used to analyze data sets and identify patterns or similarities among different data points.

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