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Section 2.4 Normed and Inner Product Spaces

Note on the exam.

The statement of the theorem below is very much examinable, as is the general idea of the proof. The full details of the proof are not examinable, except in as much as they are involved in assigned problem sheet questions.
There are analogues of Theorem 2.10 and Theorem 2.11 for normed spaces and for inner product spaces.

Proof.

Let \((X,\n\blank_X)\) be a normed space. Following the proof of Theorem 2.10, we write \(\seq xn \sim \seq yn\) if \(\lim_{n \to \infty} \n{x_n-y_n}_X = 0\text{,}\) set
\begin{align*} \hat X \amp = \{ \text{Cauchy sequences in }(X,\n\blank_X) \} / \sim,\\ \hat X_0 \amp = \{ [(x)_{n\in\N}] : x \in X \}\text{,} \end{align*}
and define a bijection \(f \maps X \to \hat X_0\) by \(f(x) = [(x)_{n \in \N}]\text{.}\) We then define our norm \(\n\blank_{\hat X}\maps \hat X \to \R\) by
\begin{equation} \big\|[\seq xn]\big\|_{\hat X} = \lim_{n\to \infty} \n {x_n}_X\text{.}\tag{2.6} \end{equation}
This is an extension of \(\n\blank_X\) in the sense that \(\n{f(x)}_{\hat X} = \n x_X\) for all \(x \in X\text{.}\)
It is not at all obvious from its definition that \(\hat X\) is a vector space, or even how the relevant operations should be defined. A natural guess, though, it to try and ‘commute’ everything past the equivalence class brackets. That is, for Cauchy sequences \(\seq xn\) and \(\seq yn\) in \((X,\n\blank_X)\) and real numbers \(\alpha \in \R\text{,}\) we define
\begin{equation} [\seq xn] + [\seq yn] = [(x_n+y_n)_{n\in \N}], \qquad \alpha [\seq xn] = [\seq{\alpha x}n].\tag{2.7} \end{equation}
Since equivalence classes are involved, we must check that these are well defined, in particular that they do not depend on which representatives we choose. We request the details in Exercise 2.4.1 and Exercise 2.4.2.
Now that we know \(\hat X\) is a vector space, we must show that \(\n\blank_{\hat X}\) defined in (2.6) is a norm on \(\hat X\text{.}\) As in the proof of Theorem 2.10, this follows by taking limits of the axioms for \(\n\blank_X\text{.}\) For instance, to see the triangle inequality, let \(\seq xn\) and \(\seq yn\) be Cauchy sequences in \((X,\n\blank_X)\text{.}\) Then for each \(n \in \N\text{,}\) the triangle inequality for \(\n\blank_X\) gives
\begin{equation*} \n{x_n+y_n}_X \le \n{x_n}_X + \n{y_n}_X \text{.} \end{equation*}
Sending \(n \to \infty\) and using (2.7), we conclude that
\begin{align*} \big\Vert[\seq xn] + [\seq yn]\big\Vert_{\hat X} \amp = \big\Vert[(x_n+y_n)_{n\in\N}]\big\Vert_{\hat X}\\ \amp \le \big\Vert[\seq xn]\big\Vert_{\hat X} + \big\Vert[\seq yn]\big\Vert_{\hat X}\text{.} \end{align*}
The density of \(\hat X_0\) and the fact that it is isometric to \(X\) follow exactly as in the proof of Theorem 2.10. The proof for inner product spaces is likewise very similar, with the natural definition
\begin{equation*} \big\langle[\seq xn],[\seq yn]\big\rangle_{\hat X} = \lim_{n\to\infty} \scp{x_n}{y_n}_X\text{.} \end{equation*}
We omit the details.

Exercises Exercises

1. Vector addition and Cauchy sequences.

Let \(\seq xn\) and \(\seq yn\) be Cauchy sequences in a normed space \((X,\n\blank_X)\text{.}\)
(a)
Show that \((x_n+y_n)_{n \in \N}\) is also a Cauchy sequence.
(b)
Suppose that \(\seq {x'}n\) and \(\seq {y'}n\) are Cauchy sequences in \((X,\n\blank_X)\text{.}\) Show that \(\seq {x'}n \sim \seq xn\) and \(\seq {y'}n \sim \seq yn\) implies \((x_n+y_n)_{n\in\N} \sim (x'_n+y'_n)_{n\in\N}\text{,}\) where here \(\seq an \sim \seq bn\) means \(\lim_{n\to \infty}\n{a_n-b_n}=0\text{.}\)

2. (PS6) Scalar multiplication and Cauchy sequences.

Let \(\alpha \in \R\) and let \(\seq xn\) be a Cauchy sequence in a normed space \((X,\n\blank_X)\text{.}\)
(a)
Show that \(\seq{\alpha x}n\) is also a Cauchy sequence.
(b)
Let \(\seq {x'}n\) be another Cauchy sequence in \((X,\n\blank_X)\text{.}\) Show that \(\seq {x'}n \sim \seq xn\) implies \(\seq{\alpha x'}n \sim \seq{\alpha x}n\text{,}\) where here \(\seq an \sim \seq bn\) means \(\lim_{n\to \infty}\n{a_n-b_n}_X=0\text{.}\)