Sequence of metric spaces is compact iff each metric space is compact

In summary, Homework Statement is a proof of the compactness of a product space by showing that if each component space is compact, then the product space is also compact. The proof is divided into two parts: the forward implication and the backward implication. The forward implication is proven by showing that if the product space is compact, then each component space is also compact. The backward implication is proven by showing that if each component space is compact, then the product space is also compact. The key idea is to use the fact that a sequence in the product space can be projected onto each component space, and by using compactness of each component space, a subsequence can be chosen that converges in each component space. This in turn implies convergence in the
  • #1
mahler1
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Homework Statement .

Let ##(X_n,d_n)_{n \in \mathbb N}## be a sequence of metric spaces. Consider the product space ##X=\prod_{n \in \mathbb N} X_n## with the distance ##d((x_n)_{n \in \mathbb N},(y_n)_{n \in \mathbb N})=\sum_{n \in \mathbb N} \dfrac{d_n(x_n,y_n)}{n^2[1+d_n(x_n,y_n)]}##.

Prove that ##(X,d)## is compact if and only if each ##(X_n,d_n)## is compact.

The attempt at a solution.

I didn't have problems to prove the forward implication. Let ##n \in \mathbb N## fixed, call it ##n=n_0## and let
Now let ##x_i## an arbitrary element in the space ##(X_i,d_i)## for ##i \neq n_0## and define the sequence ##\{\vec{x}^n\}_{n \in \mathbb N}## in ##(X,d)## as follows:

##\vec{x}^j=(x_1,x_2,...,x_{n_0-1},y^k,x_{n_0+1},...)##. By hypothesis, there is ##\{\vec{x}^{n_k}\}_{k \in \mathbb N}## convergent subsequence of ##\{\vec{x}^n\}_{n \in \mathbb N}##. Let ##\{a^{\infty}\}=(a_1,a_2,...,a_{n_0-1},a_{n_0},a_{n_0+1},...,)## be the limit of ##\{\vec{x}^{n_k}\}_{k \in \mathbb N}##. Let's prove that ##\lim_{k \to \infty} y^{n_k}=a_{n_0}##

Let ##0<\epsilon<1##, then, there is ##N: \space \forall k\geq N##, ##d(\vec{x}^{n_k},\vec{a}^{\infty})<\dfrac{\epsilon}{{n_0}^2}##.

But then, ##\dfrac{d_{n_0}(y^{n_k},a_{n_0})}{{n_0}^2[1+d_{n_0}(y^{n_k},a_{n_0})]}=\dfrac{d_{n_0}({x_{n_0}}^{n_k},a_{n_0})}{{n_0}^2[1+d_{n_0}({x_{n_0}}^{n_k},a_{n_0})]}\leq \sum_{j \in \mathbb N} \dfrac{d_j({x_j}^{n_k},a_j)}{j^2[1+d_j({x_j}^{n_k},a_j)]}=d(\vec{x}^{n_k},\vec{a}^{\infty})<\dfrac{\epsilon}{{n_0}^2}## for all ##k\geq N##.

So, ##d_{n_0}(y^{n_k},a_{n_0})<\dfrac{\epsilon}{1-\epsilon}<\epsilon## for all ##k\geq N##. This shows ##y^{n_k} \to a_{n_0}##, so the sequence ##\{y^j\}_{j \in \mathbb N}## has a convergent subsequence in ##(X_{n_0},d_{n_0})##. As ##\{y^j\}_{j \in \mathbb N}## was an arbitrary sequence, the metric space ##(X_{n_0},d_{n_0})## is compact. Since ##n_0## was an arbitrary natural number, then for each ##n \in \mathbb N##, the space ##(X_n,d_n)## is compact.

I have problems to prove the other implication. I want to show that if each ##(X_n,d_n)## is compact, then the space ##(X,d)## has to be compact. So, let ##\{\vec{x}^n\}_{n \in \mathbb N}## be a sequence in ##(X,d)## with ##\vec{x}^n=(x_{1}^n,x_{2}^n,...,x_{k}^n,...)##. Then ##\{x_{k}^n\}_{n \in \mathbb N}## is a sequence in the space ##(X_k,d_k)##. For each ##k##, I know there is a convergent subsequence Then ##\{x_{k}^{n_j}\}_{j \in \mathbb N}##. The problem is I have an infinite number of indexes ##j## dancing around, for each space ##(X_k,d_k)## I have a convergent subsequence, how can I combine the indexes of each space to choose the appropiate convergent subsequence of ##\{\vec{x}^n\}_{n \in \mathbb N}## in the space ##(X,d)##?

I hope my question and notation are clear. For me, one of the difficulties of this exercise is that one can easily be confused by all the sequences and indexes playing here.
 
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  • #2
mahler1 said:
I have problems to prove the other implication. I want to show that if each ##(X_n,d_n)## is compact, then the space ##(X,d)## has to be compact. So, let ##\{\vec{x}^n\}_{n \in \mathbb N}## be a sequence in ##(X,d)## with ##\vec{x}^n=(x_{1}^n,x_{2}^n,...,x_{k}^n,...)##. Then ##\{x_{k}^n\}_{n \in \mathbb N}## is a sequence in the space ##(X_k,d_k)##. For each ##k##, I know there is a convergent subsequence Then ##\{x_{k}^{n_j}\}_{j \in \mathbb N}##. The problem is I have an infinite number of indexes ##j## dancing around, for each space ##(X_k,d_k)## I have a convergent subsequence, how can I combine the indexes of each space to choose the appropiate convergent subsequence of ##\{\vec{x}^n\}_{n \in \mathbb N}## in the space ##(X,d)##?

I hope my question and notation are clear. For me, one of the difficulties of this exercise is that one can easily be confused by all the sequences and indexes playing here.

For any sequence on [itex]X[/itex], there is a subsequence such that its projection onto [itex]X_1[/itex] converges. Take this subsequence. It has a subsequence whose projection onto [itex]X_2[/itex] converges. Take this subsequence. It has a subsequence whose projection onto [itex]X_3[/itex] converges. ...

EDIT: One point which is worth noting is that the metrics [itex]d_k[/itex] and [itex]d_k' = \displaystyle\frac{d_k}{k^2(1 + d_k)}[/itex] give rise to exactly the same topology on [itex]X_k[/itex], so a sequence converges with respect to [itex]d_k[/itex] if and only if it converges with respect to [itex]d_k'[/itex].
 
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  • #3
pasmith said:
EDIT: One point which is worth noting is that the metrics [itex]d_k[/itex] and [itex]d_k' = \displaystyle\frac{d_k}{k^2(1 + d_k)}[/itex] give rise to exactly the same topology on [itex]X_k[/itex], so a sequence converges with respect to [itex]d_k[/itex] if and only if it converges with respect to [itex]d_k'[/itex].

This last remark was particularly helpful, it was much more difficult trying to prove [itex]d_k<\epsilon[/itex] without using that fact.
 

1. What is the definition of compactness for a sequence of metric spaces?

The compactness of a sequence of metric spaces refers to the property of the sequence where every open cover of the sequence has a finite subcover. In other words, every open subset of the sequence can be covered by a finite number of its elements.

2. How is compactness defined for each individual metric space in the sequence?

For each individual metric space in the sequence, compactness is defined as the property where every open cover of the space has a finite subcover. This means that every open subset of the space can be covered by a finite number of its elements.

3. What is the relationship between compactness of the sequence and compactness of each individual metric space?

The compactness of the sequence is equivalent to the compactness of each individual metric space in the sequence. This means that if the sequence is compact, then each metric space in the sequence is also compact, and vice versa.

4. Can a sequence be compact if each individual metric space is not compact?

No, a sequence cannot be compact if each individual metric space in the sequence is not compact. This is because the compactness of the sequence relies on the compactness of each individual metric space.

5. Why is the concept of compactness important in mathematics?

The concept of compactness is important in mathematics because it provides a useful tool for proving the existence of solutions to equations and theorems. It also helps in simplifying proofs and providing a better understanding of the structure of mathematical objects.

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