Metric Spaces - Distance Between sets and it's closures

In summary, the problem is that although it is easy to see that d(x,B) \leq d(x,B) almost trivially, proving that it actually does is more difficult.
  • #1
SqueeSpleen
141
5
I was trying to prove:
[itex]d(A,B) = d( \overline{A}, \overline{B} )[/itex]
I "proved" it using the following lemmas:
Lemma 1:
[itex]d(A,B) = \inf \{ d(x,B) \}_{x \in A} = \inf \{ d(A,y) \}_{y \in B}[/itex]
(By definition we have: [itex]d(A,B) = \inf \{ d(x,y) \}_{x \in A, y \in B}[/itex] )
Lemma 2:
[itex]d(x_{0},A) = d(x_{0}, \overline{A})[/itex]

Proof body:
[itex]d(A,B) \underbrace{=}_{L1} \inf \{ d(x,B) \}_{x \in A} \underbrace{=}_{L2} \inf \{ d(x, \overline{B}) \}_{x \in A} \underbrace{=}_{L1} \inf \{ d(A,y) \}_{y \in \overline{B}} \underbrace{=}_{L2} \inf \{ d(\overline{A},y) \}_{y \in \overline{B}} \underbrace{=}_{L1} d(\overline{A}, \overline{B})[/itex]

The problem is that... I have the first lemma proved in the textbook, but the second lemma isn't in it and I couldn't prove it (That's why I said "proved" instead of proved).
I know that [itex] d( x , \overline{B} ) \leq d(x,B) [/itex] almost trivially because by definition is the infimum of a set and the infimum of a subset must be equal or higher.
But all the things I though are useful to prove [itex] d( x , \overline{B} ) \leq d(x,B) [/itex] not [itex] d( x , \overline{B} ) \geq d(x,B) [/itex].
If [itex] d(x,B) = 0[/itex] I know it's true because of a theorem that implies it.
But if [itex] d(x,B) > 0[/itex] I can't prove [itex] d( x , \overline{B} ) \geq d(x,B) [/itex]
 
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  • #2
Assume by contradiction that ##d(x,\overline{B})<d(x,B)##.

Take a sequence ##(x_n)_n## such that each ##x_n\in \overline{B}## and such that ##d(x,x_n)\rightarrow d(x,\overline{B})##. Then there is some ##n## such that

[tex]d(x,x_n)<d(x,B)[/tex]

Now try to find a contradiction. What is ##d(x_n,B)##?
 
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  • #3
If [itex]x_{n} \in \overline{B}[/itex] then for every [itex]\varepsilon > 0[/itex], in particular for every [itex]\varepsilon \in (0,d(x,B)-d(x,x_{n}))[/itex] there exists a [itex]y \in B[/itex] such that [itex]d(x_{n},y) < \varepsilon[/itex]
Then [itex]d(x,y) \leq d(x,x_{n})+d(x_{n},y) < d(x,B)[/itex]
But [itex]y \in B[/itex], so [itex]d(x,B) \leq d(x,y)[/itex] and we have [itex]d(x,B) < d(x,B)[/itex] which is a contradiction.

Thank you very much micromass.
 
  • #4
Well done!
 

Related to Metric Spaces - Distance Between sets and it's closures

1. What is a metric space?

A metric space is a mathematical set that is equipped with a function called a metric, which measures the distance between any two elements in the set. It is a way to define and study the properties of geometric objects, such as points, lines, and shapes, using the concept of distance.

2. How is distance between sets defined in a metric space?

In a metric space, the distance between two sets A and B is defined as the infimum of all the distances between points in A and points in B. In other words, it is the minimum distance between any two points in the two sets.

3. What is the closure of a set in a metric space?

The closure of a set in a metric space is the smallest closed set that contains all the points in the original set. It can also be defined as the set of all limit points of the original set. The closure of a set is important because it helps to define completeness and compactness in a metric space.

4. How is the closure of a set related to the distance between sets in a metric space?

The closure of a set A is the set of all points that are either in A or are limit points of A. This means that any point in the closure of A can be approximated by points in A. In a metric space, the distance between two sets A and B is zero if and only if the closure of A and B are the same set.

5. Can the distance between sets and their closures be infinite in a metric space?

Yes, the distance between sets and their closures can be infinite in certain cases in a metric space. For example, if one set is unbounded and the other set is a bounded set, the distance between them can be infinite. It is also possible for the distance to be undefined if the sets have no points in common.

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