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Completeness

Definition 1: a sequence \((x_n)_{n \in \mathbb{N}}\) in a metric space \((X,d)\) is a Cauchy sequence if

\[ \forall \varepsilon > 0 \exists N \in \mathbb{N} \forall n,m > N: \quad d(x_n, x_m) < \varepsilon. \]

A convergent sequence \((x_n)_{n \in \mathbb{N}}\) in a metric space \((X,d)\) is always a Cauchy sequence since

\[ \forall \varepsilon > 0 \exists N \in \mathbb{N}: \quad d(x_n, x) < \frac{\varepsilon}{2}, \]

for all \(n > N\). By axiom 4 of the definition of a metric space we have for \(m, n > N\)

\[ d(x_m, x_n) \leq d(x_m, x) + d(x, x_n) < \frac{\varepsilon}{2} + \frac{\varepsilon}{2} = \varepsilon, \]

showing that \((x_n)\) is Cauchy.

Definition 2: a metric space \((X,d)\) is complete if every Cauchy sequence in \(X\) is convergent.

Therefore, in a complete metric space every Cauchy sequence is a convergent sequence.

Proposition 1: let \(M \subset X\) be a nonempty subset of a metric space \((X,d)\) and let \(\overline M\) be the closure of \(M\), then

  1. \(x \in \overline M \iff \exists (x_n)_{n \in \mathbb{N}} \text{ in } M: x_n \to x\),
  2. \(M \text{ is closed } \iff M = \overline M\).
Proof:

To prove statement 1, let \(x \in \overline M\). If \(x \notin M\) then \(x\) is an accumulation point of \(M\). Hence, for each \(n \in \mathbb{N}\) the ball \(B(x,\frac{1}{n})\) contains an \(x_n \in M\) and \(x_n \to x\) since \(\frac{1}{n} \to 0\) as \(n \to \infty\). Conversely, if \((x_n)_{n \in \mathbb{N}}\) is in \(M\) and \(x_n \to x\), then \(x \in M\) or every neighbourhood of \(x\) contains points \(x_n \neq x\), so that \(x\) is an accumulation point of \(M\). Hence \(x \in \overline M\).

Statement 2 follows from statement 1.

We have that the following statement is equivalent to statement 2: \(x_n \in M: x_n \to x \implies x \in M\).

Proposition 2: let \(M \subset X\) be a subset of a complete metric space \((X,d)\), then

\[ M \text{ is complete} \iff M \text{ is a closed subset of } X \]
Proof:

Let \(M\) be complete, by proposition 1 statement 1 we have that

\[ \forall x \in \overline M \exists (x_n)_{n \in \mathbb{N}} \text{ in } M: x_n \to x. \]

Since \((x_n)\) is Cauchy and \(M\) is complete, \(x_n\) converges in \(M\) with the limit being unique by statement 1 in lemma 1. Hence, \(x \in M\) which proves that \(M\) is closed because \(x \in \overline M\) has been chosen arbitrary.

Conversely, let \(M\) be closed and \((x_n)\) Cauchy in \(M\). Then \(x_n \to x \in X\) which implies that \(x \in \overline M\) by statement 1 in proposition 1, and \(x \in M\) since \(M = \overline M\) by assumption. Hence, the arbitrary Cauchy sequence \((x_n)\) converges in \(M\).

Proposition 3: let \(T: X \to Y\) be a map from a metric space \((X,d)\) to a metric space \((Y,\tilde d)\), then

\[ T \text{ is continuous in } x_0 \in X \iff x_n \to x_0 \implies T(x_n) \to T(x_0), \]

for any sequence \((x_n)_{n \in \mathbb{N}}\) in \(X\) as \(n \to \infty\).

Proof:

Suppose \(T\) is continuous at \(x_0\), then for a given \(\varepsilon > 0\) there is a \(\delta > 0\) such that

\[ \forall \varepsilon > 0 \exists \delta > 0: \quad d(x, x_0) < \delta \implies \tilde d(Tx, Tx_0) < \varepsilon. \]

Let \(x_n \to x_0\) then

\[ \exists N \in \mathbb{N} \forall n > N: \quad d(x_n, x_0) < \delta. \]

Hence,

\[ \forall n > N: \tilde d(Tx_n, Tx_0) < \varepsilon. \]

Which means that \(T(x_n) \to T(x_0)\).

Conversely, suppose that \(x_n \to x_0 \implies T(x_n) \to T(x_0)\) and \(T\) is not continuous. Then

\[ \exists \varepsilon > 0: \forall \delta > 0 \exists x \neq x_0: \quad d(x, x_0) < \delta \quad \text{ however } \quad \tilde d(Tx, Tx_0) \geq \varepsilon, \]

in particular, for \(\delta = \frac{1}{n}\) there is a \(x_n\) satisfying

\[ d(x_n, x_0) < \frac{1}{n} \quad \text{ however } \quad \tilde d(Tx_n, Tx_0) \geq \varepsilon, \]

Clearly \(x_n \to x_0\) but \((Tx_n)\) does not converge to \(Tx_0\) which contradicts \(Tx_n \to Tx_0\).

Completeness proofs

To show that a metric space \((X,d)\) is complete, one has to show that every Cauchy sequence in \((X,d)\) has a limit in \(X\). This depends explicitly on the metric on \(X\).

The steps in a completeness proof are as follows

  1. take an arbitrary Cauchy sequence \((x_n)_{n \in \mathbb{N}}\) in \((X,d)\),
  2. construct for this sequence a candidate limit \(x\),
  3. prove that \(x \in X\),
  4. prove that \(x_n \to x\) with respect to metric \(d\).

Proposition 4: the Euclidean space \(\mathbb{R}^n\) with \(n \in \mathbb{N}\) and the metric \(d\) defined by

\[ d(x,y) = \sqrt{\sum_{j=1}^n \big(x(j) - y(j) \big)^2}, \]

for all \(x,y \in \mathbb{R}^n\) is complete.

Proof:

Let \((x_m)_{m \in \mathbb{N}}\) be a Cauchy sequence in \((\mathbb{R}^n, d)\), then we have

\[ \forall \varepsilon > 0 \exists N \in \mathbb{N}: \forall m, k > N: d(x_m, x_k) = \sqrt{\sum_{j=1}^n \big(x_m(j) - x_k(j) \big)^2} < \varepsilon, \]

obtains for all \(j \in \mathbb{N}\): \(|x_m(j) - x_k(j)| < \varepsilon\).

Which shows that \((x_m(j))_{m \in \mathbb{N}}\) is a Cauchy sequence in \(\mathbb{R}\). Suppose that it converged by \(x_m(j) \to x(j)\) as \((m \to \infty)\) then \(x \in \mathbb{R}^n\) since \(x = \big(x(1), \dots, x(n)\big)\).

Thus for \((k \to \infty)\) we have

\[ d(x_m, x) < \varepsilon \implies x_m \to x, \]

which implies that \(\mathbb{R}^n\) is complete.

A similar proof exists for the completeness of the Unitary space \(\mathbb{C}^n\).

Proposition 5: the space \(C([a,b])\) of all real-valued continuous functions on a closed interval \([a,b]\) with \(a<b \in \mathbb{R}\) with the metric \(d\) defined by

\[ d(x,y) = \max_{t \in [a,b]} |x(t) - y(t)|, \]

for all \(x, y \in C\) is complete.

Proof:

Let \((x_n)_{n \in \mathbb{N}}\) be a Cauchy sequence in \((C,d)\), then we have

\[ \forall \varepsilon > 0 \exists N \in \mathbb{N}: \forall n, m > N: d(x_n, x_m) = \max_{t \in [a,b]} |x_n(t) - x_m(t)| < \varepsilon, \]

obtains for all \(t \in [a,b]\): \(|x_n(t) - x_m(t)| < \varepsilon\).

Which shows that \((x_m(t))_{m \in \mathbb{N}}\) for fixed \(t \in [a,b]\) is a Cauchy sequence in \(\mathbb{R}\). Since \(\mathbb{R}\) is complete the sequence converges; \(x_m(t) \to x(t)\) as \(m \to \infty\).

Thus, for \(m \to \infty\) we have

\[ d(x_n, x) = \max_{t \in [a,b]} | x_n(t) - x(t) | < \varepsilon, \]

hence \(\forall t \in [a,b]: | x_n(t) - x(t) < \varepsilon\), obtaining convergence to \(x_n \to x\) as \(n \to \infty\) and \(x \in C\) which implies that \(C\) is complete.

While \(C\) with a metric \(d\) defined by

\[ d(x,y) = \int_a^b |x(t) - y(t)| dt, \]

for all \(x,y \in C\) is incomplete.

Proof:

Will be added later.

Proposition 6: the space \(l^p\) with \(p \geq 1\) and the metric \(d\) defined by

\[ d(x,y) = \Big(\sum_{j \in \mathbb{N}} | x(j) - y(j) |^p\Big)^\frac{1}{p}, \]

for all \(x,y \in l^p\) is complete.

Proof:

Let \((x_n)_{n \in \mathbb{N}}\) be a Cauchy sequence in \((l^p,d)\), then we have

\[ \forall \varepsilon > 0 \exists N \in \mathbb{N}: n, m > N: d(x_n, x_m) = \Big(\sum_{j \in \mathbb{N}} |x_n(j) - x_m(j)|^p\Big)^\frac{1}{p} < \varepsilon, \]

obtains for all \(j \in \mathbb{N}\): \(|x_n(j) - x_m(j)| <\varepsilon\).

Which shows that \((x_m(j))_{m \in \mathbb{N}}\) for fixed \(j \in \mathbb{N}\) is a Cauchy sequence in \(\mathbb{C}\). Since \(\mathbb{C}\) is complete the sequence converges; \(x_m(j) \to x(j)\) as \(m \to \infty\).

Thus, for \(m \to \infty\) we have

\[ d(x_n, x) = \Big(\sum_{j \in \mathbb{N}} |x_n(j) - x(j)|^p\Big)^\frac{1}{p} < \varepsilon, \]

implies that \(x_n - x \in l^p\) and \(x = x_n - (x_n - x) \in l^p \implies x \in l^p\) and \(x_n \to x\) as \(n \to \infty\) which implies that \(l^p\) is complete.

Proposition 7: the space \(l^\infty\) with the metric \(d\) defined by

\[ d(x,y) = \sup_{j \in \mathbb{N}} | x(j) - y(j) |, \]

for all \(x,y \in l^\infty\) is complete.

Proof:

Let \((x_n)_{n \in \mathbb{N}}\) be a Cauchy sequence in \((l^\infty,d)\), then we have

\[ \forall \varepsilon > 0 \exists N \in \mathbb{N}: n, m > N: d(x_n, x_m) = \sup_{j \in \mathbb{N}} | x_n(j) - x_m(j) | < \varepsilon, \]

obtains for all \(j \in \mathbb{N}\): \(|x_n(j) - x_m(j)| <\varepsilon\).

Which shows that \((x_m(j))_{m \in \mathbb{N}}\) for fixed \(j \in \mathbb{N}\) is a Cauchy sequence in \(\mathbb{C}\). Since \(\mathbb{C}\) is complete the sequence converges; \(x_m(j) \to x(j)\) as \(m \to \infty\).

Thus, for \(m \to \infty\) we have

\[ d(x_n, x) = \sup_{j \in \mathbb{N}} | x_n(j) - x(j) | < \varepsilon \implies |x_n(j) = x(j)| < \varepsilon. \]

Since \(x_n \in l^\infty\) there exists a \(k_n \in \mathbb{R}: |x_n(j)| \leq k_n\) for all \(j \in \mathbb{N}\). Hence

\[ |x(j)| \leq |x(j) - x_n(j)| + |x_n(j)| < \varepsilon + k_n, \]

for all \(j \in \mathbb{N}\) which implies that \(x \in l^\infty\) and \(x_n \to x\) as \(n \to \infty\) obtaining that $ l^\infty$ is complete.