Compactness in Metric Spaces: Is It Possible?

  • Thread starter Bleys
  • Start date
  • Tags
    Metric
In summary, in metric spaces, compactness is often proven after introducing the notions of closed and bounded or sequential compactness. However, there is a way to prove that a closed interval [a,b] is compact in the usual topology on the real numbers just from definition. This can be done by considering an arbitrary open cover and using the fact that this topology has a natural correspondence with the metric space. This is shown in the proof of the Heine-Borel Theorem, which explicitly proves the compactness of a closed interval using covers. The proof involves considering the supremum of all numbers c' such that [a,c'] can be covered by finitely many elements of the cover, and ultimately shows that the supremum is
  • #1
Bleys
74
0
I've never actually seen a proof that a space is compact just from the definition. In metric spaces it was usually after the notion of closed and bounded or sequential compactness was introduced.
For example is there a way to prove [a,b] is compact (with the usual topology on the real numbers) just from definition? It seems almost impossible... you have to consider an arbitrary open cover!
Is it possible to use the fact that this topology has a natural correspondence with the metric space? Because open sets in the metric space are the same as the open sets in the topology?
 
Physics news on Phys.org
  • #2
See http://planetmath.org/encyclopedia/ProofOfHeineBorelTheorem.html
There they explicitely prove that a closed interval is compact using covers. The proof is somewhat involved though...
 
Last edited by a moderator:
  • #3
It's not too involved--let c be the supremum of all numbers c' such that [a,c'] can be covered by finitely many elements of the cover you're given. Well, c is contained in some element of the cover, so add that element to your finite subcover to get another finite subcover that includes a neighborhood of c, so that it covers [a,c+epsilon] (you don't end up with two disconnected components because of the definition of supremum). So c was not the supremum after all, unless c=b.
 

1. What is compactness in metric spaces?

Compactness in metric spaces is a property of a set that measures how closely it resembles a finite set. In other words, it measures how "close together" the points in the set are. A compact set is one where every open cover (a collection of open sets that cover the set) has a finite subcover (a subset of the open sets that still covers the set).

2. How is compactness defined in metric spaces?

Compactness in metric spaces is defined using the concept of open sets. A set is compact if every open cover of the set has a finite subcover. In other words, if every open set that contains the set can be "broken down" into a finite number of open sets that also contain the set.

3. What are some examples of compact sets in metric spaces?

Some examples of compact sets in metric spaces include a closed interval [a, b] on the real number line, a closed ball in n-dimensional Euclidean space, and the Cantor set. These sets all have the property that any open cover has a finite subcover.

4. Why is compactness an important concept in metric spaces?

Compactness is an important concept in metric spaces because it allows us to make statements about the behavior of functions and sequences within a set. For example, if a function is continuous on a compact set, then it must also be uniformly continuous. Additionally, compact sets have many useful properties that can be used to prove theorems in analysis and topology.

5. Is compactness always possible in metric spaces?

No, compactness is not always possible in metric spaces. For a set to be compact, it must satisfy the mathematical definition of compactness, which requires that every open cover has a finite subcover. This is not always the case, as there are many sets that do not have this property. However, compact sets are quite common in many areas of mathematics and are an important concept to understand in order to solve problems and prove theorems.

Similar threads

  • Calculus and Beyond Homework Help
Replies
12
Views
1K
  • Topology and Analysis
Replies
32
Views
2K
  • Topology and Analysis
Replies
3
Views
1K
  • Topology and Analysis
Replies
16
Views
2K
  • Calculus and Beyond Homework Help
Replies
1
Views
1K
  • Topology and Analysis
Replies
2
Views
1K
Replies
3
Views
848
  • Quantum Physics
Replies
1
Views
695
  • Calculus and Beyond Homework Help
Replies
12
Views
1K
  • Special and General Relativity
Replies
25
Views
2K
Back
Top