Metric spaces and the distance between sets

In summary, the problem asks us to show that the distance between two disjoint, compact subsets in a metric space is greater than 0. The attempt at a solution argues that this is trivial since the definition of a metric guarantees that distances are always greater than or equal to 0. However, this argument breaks down when considering non-compact subsets. To solve the problem, we should use the fact that X satisfies the Bolzano-Weierstrass Property.
  • #1
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Homework Statement


Okay, so we've moved on from talking about R^n to talking about general metric spaces and the differences between the two. We're given that X (a metric space) satisfies the Bolzano-Weierstrass Property and that A and B are disjoint, compact subsets of X. Dist(A,B) is defined as the inf{d(x,y): x in A, y in B}. We're asked to show that Dist(A,B)>0.


Homework Equations


General theory of metric spaces: definition of a metric space, metric, etc.


The Attempt at a Solution


Okay, I think I must be missing something because to me it seems kind of trivial. My proof basically says that, by definition of a metric, d(x,y) is always greater than or equal to 0, with equality holding only when x=y. Since A and B are disjoint in our problem, x does not equal y for all x in A and y in B hence d(x,y) is always greater than 0. Since the inf is the min of these distances, it follows that the inf is always greater than 0.

I didn't use the fact that X satisfies the Bolzano-Weierstrass Property however, which makes me think that I'm missing something. Any help would be greatly appreciated.
 
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  • #2
To see where your argument breaks down, consider the open intervals (0,1) and (1,2). Since they are not compact, they don't satisfy the hypothesis of your problem. However, you could use your reasoning to "show" that the distance between them is > 0, which it clearly isn't.

Hint: The sentence "Since the inf is the min of these distances, it follows that the inf is always greater than 0." is the problem with your argument. Try to apply it to the above example.

HTH

Petek
 

FAQ: Metric spaces and the distance between sets

1. What is a metric space?

A metric space is a mathematical concept that defines a set of objects and a distance function between them. The distance function measures the distance between any two objects in the set, and it must follow certain properties such as non-negativity, symmetry, and the triangle inequality.

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

In a metric space, the distance between sets is defined as the infimum (greatest lower bound) of the distances between all pairs of elements from the two sets. This means that the distance between sets is the smallest possible distance between any two points from the two sets.

3. What is the importance of metric spaces in mathematics?

Metric spaces are important in mathematics as they provide a general framework for studying and understanding properties of spaces and their distances. They are used in various fields such as analysis, topology, and geometry to define and study objects and their relationships.

4. Can two different metric spaces have the same distance function?

Yes, it is possible for two different metric spaces to have the same distance function. This is because the distance function is only one aspect of a metric space, and the other defining properties, such as the set of objects and the topology, can differ while still having the same distance function.

5. How are metrics and norms related in a metric space?

In a metric space, the distance function can be used to define a norm, which is a mathematical concept that measures the size or magnitude of a vector or a function. This is done by assigning a distance value to each element in the set and then taking the supremum (least upper bound) of these values. Therefore, metrics and norms are closely related in a metric space.

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