④ Metric spaces
§1. Metric spaces¶
Metric spaces¶
Let \(M\) be a set and let \(d\colon M \times M \to \mathbb{R}\) be a function. If, for all \(x,\,y,\,z\in M\), the following conditions hold:
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\(d(x, y) \geq 0\), with \(d(x, y) = 0\) iff \(x = y\);
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\(d(x, y) = d(y, x)\);
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\(d(x, z) \leq d(x, y) + d(y, z)\),
then \(d\) is called a metric on \(M\), and the pair \((M, d)\) is called a metric space.
Let \(M\) be a set. Define a function \(d\colon M \times M \to \mathbb{R}\) as
Then, \(d\) is called a discrete metric on \(M\) and \((M, d)\) is called a discrete metric space. It is easy to verify that \(d\) is indeed a metric.
Open and closed balls¶
Open and closed sets¶
Interiors, closures, and boundaries¶
§2. Convergence¶
Convergent sequences¶
Let \((M, d)\) be a metric space. Let \((a_n)\) be a sequence in \(M\), and let \(a \in M\). We say that \((a_n)\) _converges to _\(a\) if, for all \(\varepsilon > 0\), there exists \(N \in \mathbb{N}\) such that \begin{equation} d(a_m, a) \leq \varepsilon \quad \text{for all }n \in \mathbb{N} \text{ with }n \geq N.\notag \end{equation} Such a sequence is called a convergent sequence.
Cauchy sequences¶
Let \((M, d)\) be a metric space. A sequence \((a_n)\) in \(M\) is Cauchy if for all \(\varepsilon > 0\), there exists \(N \in \mathbb{N}\) such that \begin{equation} d(a_m, a_n) \leq \varepsilon \quad \text{for all }m,\,n \in \mathbb{N} \text{ with }m, n \geq N.\notag \end{equation}
§3. Completeness¶
Complete metric spaces¶
A metric space \((M, d)\) is complete if every Cauchy sequence in \(M\) converges in \(M\).
Banach fixed-point theorem¶
Let \((M, d)\) be a metric space. A function \(f\colon M \to M\) is called a contraction mapping if there exists \(\rho \in (0, 1)\) such that \begin{equation} d(f(x), f(y)) \leq \rho d(x, y) \quad \text{for all } x,\,y\in M.\notag \end{equation}
Every contraction mapping on a metric space has one unique fixed point.
Let \((M, d)\) be a metric space. Let \(f\colon M \to M\) be a contraction mapping with \begin{equation} d(f(x), f(y)) \leq \rho d(x, y) \quad \text{for all } x,\,y\in M.\notag \end{equation} where \(\rho \in (0, 1)\). Define \(f^{n}(x) := \underbrace{(f\circ f \circ \cdots \circ f)}_{n \text{ times}} (x)\).
[Incomplete]
§4. Compactness¶
Let \((M, d)\) be a metric space. A subset \(S \subseteq M\) is compact if every sequence \((x_{m})\) in \(S\) has a subsequence that converges in \(S\).
Heine–Borel theorem¶
TBD
§5. Continuity¶
Continuous functions¶
Lipschitz and uniformly continuous functions¶
Extreme value theorem¶
Upper/lower semicontinuous functions¶
Upper/lower hemicontinuous correspondences¶
References¶
TBD