Proving R^2 is metrizable in the dictionary order topology

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In summary: In this case, I think it's safe to say that the dot is finer than the topology induced by your proposed metric.
  • #1
radou
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Homework Statement



As the title suggests, I need to show that RxR is metrizable in the dictionary order topology.

As a reminder, for two elements (a, b) and (c, d) of R^2, the dictionary order is defined as (a, b) < (c, d) if a < c, or if a = c and b < d.


The Attempt at a Solution



The typical basis elements for the dictionary order topology (dot from now on) are represented by either "infinite vertical regions" or "vertical intervals".

If we define a metric on R^2 with:

d(x, y) = |x2 - y2| , for x1 = y1 ; max{|xi - yi|, for x1 =/= y1}

where x = (xi) and y = (yi) are points in R^2,

we can prove that the dot equals the topology induced by this metric, for, if B is some basis element in the dot, we can find open balls which are either regions or open intervals contained in this basis element, whatever it looks like. The same vice versa.

I hope this works.
 
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  • #2
radou said:
If we define a metric on R^2 with:

d(x, y) = |x2 - y2| , for x1 = y1 ; max{|xi - yi|, for x1 =/= y1}

where x = (xi) and y = (yi) are points in R^2,

This is the same as simply
[tex] d(x,y)=max\{ |x_1-y_1|,|x_2-y_2| \}[/tex]

since if [tex] x_1=y_1[/tex] then in the max you'll definitely be taking the difference between [tex] x_2[/tex] and [tex] y_2[/tex].

we can prove that the dot equals the topology induced by this metric, for, if B is some basis element in the dot, we can find open balls which are either regions or open intervals contained in this basis element, whatever it looks like. The same vice versa.

What do you mean by "the dot"?
 
  • #3
Office_Shredder said:
What do you mean by "the dot"?

The dictionary order topology, as I stated in the first post.

Office_Shredder said:
This is the same as simply
[tex] d(x,y)=max\{ |x_1-y_1|,|x_2-y_2| \}[/tex]

since if [tex] x_1=y_1[/tex] then in the max you'll definitely be taking the difference between [tex] x_2[/tex] and [tex] y_2[/tex].

Yes, I'm aware of that. But in that case, if given a basis element of the dot of type "vertical intercal", for example, the interval <(a, c), (a, d)>, for any x in this interval, how can I find a basis element of the metric topology defined as you proposed above, if the basis elements in this case (open balls) are square regions?

Btw, the concept of proving two topologies are equal is to show each one is finer than the other.
 

FAQ: Proving R^2 is metrizable in the dictionary order topology

What is the dictionary order topology?

The dictionary order topology is a type of topology that is defined on a set of words or symbols, typically ordered alphabetically. In this topology, a basis for the open sets is given by the intervals [a, b) where a and b are elements of the set, with a

What does it mean for a space to be metrizable?

A space is said to be metrizable if there exists a metric on the space that induces the given topology. This means that the open sets in the topology can be defined in terms of distance, and the properties of the metric can be used to prove topological properties of the space.

How is R^2 defined in the dictionary order topology?

R^2, or the Cartesian product of the real numbers with itself, is defined in the dictionary order topology as the set of all ordered pairs (x,y) where x and y are real numbers, with the basis for the open sets given by the intervals [a,b) x [c,d).

Why is it important to prove that R^2 is metrizable in the dictionary order topology?

Proving that R^2 is metrizable in the dictionary order topology has practical applications in mathematics and physics. It allows for the use of distance-based techniques and properties in the study of this space, making it easier to analyze and understand.

How is the proof for R^2 being metrizable in the dictionary order topology typically approached?

The proof typically involves constructing a metric on the space that satisfies the properties of the dictionary order topology. This can be done by defining a function that measures the distance between two points in R^2 and showing that it satisfies the metric axioms. Additionally, it may involve showing that this metric induces the given topology on R^2.

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