Compact subspace in metric space

In summary, according to the Heine-Borel theorem, there is no closed and bounded set in a metric space which is not compact.
  • #1
facenian
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Is there an easy example of a closed and bounded set in a metric space which is not compact. Accoding to the Heine-Borel theorem such an example cannot be found in ##R^n(n\geq 1)## with the usual topology.
 
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  • #2
facenian said:
Is there an easy example of a closed and bounded set in a metric space which is not compact. Accoding to the Heine-Borel theorem such an example cannot be found in ##R^n(n\geq 1)## with the usual topology.
From Wikipedia:

A simple counterexample yields the discrete metric on an infinite set of ##X##. The discrete metric is defined by
##d (x, x) = 0##,
##d (x, y) = 1## for ## x \neq y\; , \; x, y \in X ##
In this metric, each subset of ##X## is closed and bounded, but only the finite subsets are compact.

Further counterexamples are all infinite-dimensional normalized vector spaces.
 
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  • #3
facenian said:
Is there an easy example of a closed and bounded set in a metric space which is not compact. Accoding to the Heine-Borel theorem such an example cannot be found in ##R^n(n\geq 1)## with the usual topology.

Take the closed unit disk in the plane with the following metric. If two points lie on the same radius line through the origin, their distance is the Euclidean distance. If they lie on different radii, it is the sum of their Euclidean distances to the origin. This space is bounded since the maximum distance is 2.

Show that it is closed, i.e. every Cauchy sequence converges to a point in the space.

Is it compact?
 
  • #4
fresh_42 said:
From Wikipedia:

A simple counterexample yields the discrete metric on an infinite set of ##X##. The discrete metric is defined by
##d (x, x) = 0##,
##d (x, y) = 1## for ## x \neq y\; , \; x, y \in X ##
In this metric, each subset of ##X## is closed and bounded, but only the finite subsets are compact.

Further counterexamples are all infinite-dimensional normalized vector spaces.
I think it will be hard to beat this example on simplicity basis.
In the case of @lavinia 's example I believe the disk should be an open unit disk.
Thank you guys, it's been very helpful
 
  • #5
facenian said:
I think it will be hard to beat this example on simplicity basis.
In the case of @lavinia 's example I believe the disk should be an open unit disk.
Thank you guys, it's been very helpful
No. It is the closed unit disk. If it were open then a Cauchy sequence of points that converges to a point of distance 1 to the origin will not converge.
 
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  • #6
lavinia said:
No. It is the closed unit disk. If it were open then a Cauchy sequence of points that converges to a point of distance 1 to the origin with not converge.
Of course!, I'm sorry I was thinking what must happen for it not to be compact and responded on the contrary. Thanks again.
 
  • #7
facenian said:
Of course!, I'm sorry I was thinking what must happen for it not to be compact and responded on the contrary. Thanks again.

This space is also path connected unlike the example of the infinite discrete space.

Have you found an open cover with no finite subcover?
 
  • #8
Another simple example Hilbert space. The unit ball is closed and bounded but not compact. A particular Hilbert space would be all infinite series, where the sum of the squares is finite.
 
  • #9
mathman said:
Another simple example Hilbert space. The unit ball is closed and bounded but not compact. A particular Hilbert space would be all infinite series, where the sum of the squares is finite.
Can you describe the topology a little more?
 
  • #10
@mathman, I know you meant this, but technically you need to say infinite dimensional Hilbert space. Indeed a normed space is locally compact iff it is finite dimensional, Riesz's theorem. Dieudonne', Foundations of modern analysis, page 109.
 
  • #11
lavinia said:
Can you describe the topology a little more?

Probably @mathman refers to the space ##\mathcal{l}^2 = \{(a_n)_n \in \mathbb{K}^\mathbb{N}\mid \sum |a_n|^2 < \infty\}##, with the norm induced by the innerproduct ##\langle (a_n)_n, (b_n)_n\rangle:= \sum a_n b_n##.

I.e., ##\Vert (a_n)_n \Vert = \sum |a_n|^2 < \infty##

You take the topology that is derived from the norm.
 
  • #12
Yes
Math_QED said:
Probably @mathman refers to the space ##\mathcal{l}^2 = \{(a_n)_n \in \mathbb{K}^\mathbb{N}\mid \sum |a_n|^2 < \infty\}##, with the norm induced by the innerproduct ##\langle (a_n)_n, (b_n)_n\rangle:= \sum a_n b_n##.

I.e., ##\Vert (a_n)_n \Vert = \sum |a_n|^2 < \infty##

You take the topology that is derived from the norm.
Yes, there are infinite nets without finite subnets, which is an equivalent to compactness: every e-net has a finite subnet. I think also the sequence ##e_i:= \delta^i_j## has no convergent subsequence, since ##||e_i-e_j||= \sqrt 2 ##
 
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  • #13
WWGD said:
Yes

Yes, there are infinite nets without finite subnets, which is an equivalent to compactness: every e-net has a finite subnet. I think also the sequence ##e_i:= \delta^i_j## has no convergent subsequence, since ##||e_i-e_j||= \sqrt 2 ##

In the context of this question, one can also use the well known theorem from functional analysis that in a normed space the unit ball compact is if and only if the space is finite dimensional. Since the space provided by @mathman is infinitedimensional, the unit ball isn't compact, but clearly it is closed (every closed ball is closed as set) and bounded.
 
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  • #14
mathwonk said:
@mathman, I know you meant this, but technically you need to say infinite dimensional Hilbert space. Indeed a normed space is locally compact iff it is finite dimensional, Riesz's theorem. Dieudonne', Foundations of modern analysis, page 109.
When I first was exposed to Hilbert space, it was only infinite dimensional, i.e. the infinite dimensional extension of Euclidean space.
 
  • #15
well technically a hilbert space is usually defined as any complete inner product space, so finite dimensional spaces qualify.

https://en.wikipedia.org/wiki/Hilbert_space

But it is true some people use the term in a restricted sense, sometimes even to mean only those infinite dimensional ones with a countable dense subset, basically "little l-2". Then Euclidean spaces are essentially just (isomorphic to) spaces of finite sequences of scalars of fixed length n, and "Hilbert space" is (isomorphic to) the space of infinite square - summable sequences. These are also called "separable" (infinite dimensional) hilbert spaces.

So there are three classes of Hilbert spaces, finite dimensional, separable infinite dimensional, and inseparable (necessarily infinite dimensional), and some people only use the term "Hilbert space" for the second class. My favorite book on the topic, which explains it this way, is the one I started out on in college: Spectral Theory, by Edgar Lorch, Oxford Univ Press 1962. In fact he says there on p. 60, as you learned, that "Historically, the term Hilbert space has been reserved for" the case of countably infinite dimensional ones. (dimension here is in the sense of hilbert space dimension, i.e. the cardinality not of a maximal linearly independent set, but of a maximal orthonormal set, since every hilbert space has uncountable linear dimension.)
 
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  • #16
mathman said:
When I first was exposed to Hilbert space, it was only infinite dimensional, i.e. the infinite dimensional extension of Euclidean space.
Does that mean in your world there is no zero operator or at least no restriction of the codomain to the image? I think from a categorial point of view to include finite dimensional Hilbert spaces make absolute sense.
 
  • #17
by the way for the OP, in any metric space, the equivalent of compactness is the combined conditions "complete and totally bounded", replacing the weaker Euclidean conditions of "closed and bounded".
 
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1. What is a compact subspace in a metric space?

A compact subspace in a metric space is a subset of a metric space that is both closed and bounded. This means that the subspace contains all of its limit points and can be contained within a finite distance.

2. How is compactness different from connectedness?

Compactness and connectedness are two different properties of a subset in a metric space. A compact subset is closed and bounded, while a connected subset is not separated into two or more disjoint sets. In other words, a compact subspace can be contained within a finite distance, while a connected subspace cannot be split into two or more separate parts.

3. Can a compact subspace be unbounded?

No, a compact subspace must be both closed and bounded. If a subspace is unbounded, it cannot be contained within a finite distance and therefore cannot be considered compact.

4. How is compactness related to the Heine-Borel theorem?

The Heine-Borel theorem states that a subset in a metric space is compact if and only if it is closed and bounded. In other words, a subset is compact if and only if it satisfies the definition of a compact subspace.

5. What are some examples of compact subspaces in a metric space?

Some examples of compact subspaces in a metric space include a closed interval [a,b] in the real numbers with the standard metric, a closed disk in the plane with the Euclidean metric, and a closed and bounded set of points in a Euclidean space with the standard Euclidean metric.

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