Topology: Complete Metric Spaces

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Topology: Complete Metric Spaces

2023-04-02 03:55| 来源: 网络整理| 查看: 265

[ This article was updated on 8 Mar 13; the universal property is now in terms of Cauchy-continuous maps. ] updated

On an intuitive level, a complete metric space is one where there are “no gaps”. Formally, we have:

Definition. A metric space (X, d) is said to be complete if every Cauchy sequence in X converges.

warning Completeness is not a topological property, i.e. one can’t infer whether a metric space is complete just by looking at the underlying topological space. For example, (0, 1) and R are homeomorphic as topological spaces, but the former is not complete (since the sequence (1/n) is Cauchy but doesn’t converge) and the latter is. Clearly, not every subspace of a complete metric space is complete. E.g. R – {0} is not complete since the sequence (1/n) doesn’t converge. However, we have:

Proposition 1. A subset of a complete metric space X is complete if and only if it’s closed in X.

Proof.

Both directions use theorem 1 here. If Y is closed in X, then any Cauchy sequence in Y is also Cauchy in X and hence must converge to some a in X; then a must lie in Y by the theorem.

Conversely, if Y is a non-closed subset of X, then there is a sequence in Y converging to a in X, outside Y. This sequence is Cauchy since it’s convergent in X, but it doesn’t converge in Y; thus Y is not complete. ♦

Proposition 2. If (X, d_X) and (Y, d_Y) are complete metric spaces, then so is (X\times Y, d) where d can be any one of the following metrics:

((x,y), (x',y')) \mapsto \sqrt{d_X(x,x')^2 + d_Y(y,y')^2}; ((x,y), (x',y')) \mapsto d_X(x,x') + d_Y(y,y'); ((x,y), (x',y')) \mapsto \max(d_X(x,x'), d_Y(y,y')).

Proof.

We know (from proposition 3 here) that if a sequence (x_n, y_n) in X × Y is Cauchy, then (x_n), (y_n) are Cauchy in X and Y respectively. Hence, they’re both convergent, say, to a\in X, b\in Y. Thus, (x_n, y_n) \to (a, b) is convergent. ♦

Exercise

Suppose X_1, X_2, \ldots is a countably infinite collection of complete metric spaces. Construct a metric on X:=\prod_{n=1}^\infty X_n as before. Is the resulting metric space complete?

Answer (highlight to read) :

Yes, each projection map πn : X → Xn is uniformly continuous. So a Cauchy sequence (xn)1, (xn)2, (xn)3, … gives rise to a Cauchy sequence in each Xn. Each of these converges, to say, an in Xn. Then by proposition 4 here, we see that (xn)1, (xn)2, (xn)3, … converges to (an). ♦

blue-lin

Completion of Metric Space

It turns out there’s a unique way of embedding any metric space into a “smallest” complete metric space.

Definition. A metric space Y is a completion of metric space X if:

X is a metric subspace of Y; Y is complete; and X is dense in Y.

Suppose X\subseteq Y satisfies the first two conditions. Then we take X\subseteq Z:=\text{cl}_Y(X)\subseteq Y. Now Z is closed in Y so it is complete by proposition 1 above. Furthermore, X is dense in Z by definition. So X\subseteq Z is now a completion. In other words, the third condition enforces a minimality condition on Y. One can visualise Y as filling up the gaps of X.

Classical example: the completion of Q, under the Euclidean metric, is R.

The key property of the completion is the following.

Universal Property of Completion. Suppose X\subseteq Y is a completion. Then:

for any Cauchy-continuous map f:X \to Z to a complete metric space Z, there is a unique continuous g:Y\to Z such that g|_X = f.

Minor Note.

Since g is continuous, it’s automatically Cauchy-continuous here since Y is complete: indeed, if (y_n) is a Cauchy sequence in Y, then it converges to some y, so (f(y_n))\to f(y) is convergent and must also be Cauchy.

Proof.

Uniqueness: if g, g’ satisfy g|_X = g'|_X then since X is dense in Y and Z is Hausdorff, we have g = g’.

Only existence remains: we denote the metric of X and Y by d and that of Z by d’.

Suppose y\in Y; since X is dense in Y, y is a limit of a sequence (xn) in X. Then (xn) is Cauchy and since f is Cauchy-continuous, (f(xn)) is Cauchy in Z. So (f(xn)) converges to some z and we let g(y) = z.

completion_map

To show g is well-defined: suppose (x_n), (x_n') \to y. We need to show (f(x_n)), (f(x_n')) have the same limit. It suffices to show d'(f(x_n), f(x_n')) \to 0 as n → ∞.

For each ε>0, pick δ>0 such that whenever d(x, y) N, d(x_n, x_n') \le d(x_n, y)+d(y, x_n') \delta \implies d(f(x_n), f(x_n')) \epsilon.

Clearly g|_X = f since if y\in X we can pick the constant sequence (y, y, …) in X.

Finally, we need to show g is continuous. By theorem 6 here, it suffices to show that if (y_n)\to y, then (g(y_n))\to g(y). Now since X is dense in Y, we can pick a sequence (x_n) such that d(x_n, y_n)\frac 1 n. This gives (x_n)\to y also. From our definition of g, we must have (g(x_n)) = (f(x_n)) \to g(y) so we’re done. ♦

Exercise

Prove that if f had been uniformly continuous, so is the induced g.

Answer (highlight to read).

The following replaces the last paragraph in the proof of universal property.

Let ε>0. There exists δ>0 such that whenever x, x’ in X satisfies d(x, x’)  N, we have d'(x_m, x_n) \epsilon and (x_n) is a Cauchy sequence in X, which must correspond to some y\in Y.

It remains to show (y_n)\to y. Indeed, we have:

d'(y_n, y) \le d'(y_n, x_n) + d'(x_n, y) \frac 1 n + d'(x_n, y).

Step 6 then tells us that d'(x_n, y)\to 0 since (x_n) \to y. And we’re done. ♦

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