Theorem 20.4 The uniform topology on \(\mathbb{R}^J\) is finer than the product topology and coarser than the box topology; these three topologies are all different if \(J\) is infinite.

Proof: a) Prove the uniform topology is finer than the product topology.

Analysis: Look inside an open ball in the product topology for an open ball in the uniform topology and then apply Lemma 20.2. It should be also noted that the product topology on \(\mathbb{R}^J\) has each of its coordinate space assigned the standard topology, which is consistent with both topologies induced from the two metrics \(d\) and \(\bar{d}\) according to example 2 in this section and Theorem 20.1.

According to the second part of Theorem 19.2, let \(\prod_{\alpha \in J} B_{\alpha}\) be an arbitrary basis element for the product topology on \(\mathbb{R}^J\), where only a finite number of \(B_{\alpha}\)s are open intervals in \(\mathbb{R}\) and not equal to \(\mathbb{R}\). Let the indices for these \(B_{\alpha}\)s be \(\{\alpha_1, \cdots, \alpha_n\}\) and for all \(i \in \{1, \cdots, n\}\), \(B_{\alpha_i} = (a_i, b_i)\). Then for all \(\vect{x} \in \prod_{\alpha \in J} B_{\alpha}\) and for all \(\alpha \in J\), \(x_{\alpha} \in B_{\alpha}\). Specifically, for all \(i \in \{1, \cdots, n\}\), \(x_{\alpha_i} \in B_{\alpha_i}\). Let \(\varepsilon_{\alpha_i} = \min \{ x_{\alpha_i} - a_i, b_i - x_{\alpha_i} \}\) and \(\varepsilon = \min_{1 \leq i \leq n} \{\varepsilon_{\alpha_1}, \cdots, \varepsilon_{\alpha_n}\}\). Then we’ll check the open ball \(B_{\bar{\rho}}(\vect{x}, \varepsilon)\) in \(\mathbb{R}^J\) with the uniform topology is contained in the basis element \(\prod_{\alpha \in J} B_{\alpha}\).

For all \(\vect{y} \in B_{\bar{\rho}}(\vect{x}, \varepsilon)\), \(\bar{\rho}(\vect{x}, \vect{y}) < \varepsilon\), i.e. \(\sup_{\forall \alpha \in J} \{\bar{d}(x_{\alpha}, y_{\alpha})\} < \varepsilon\). Therefore, for all \(i \in \{1, \cdots, n\}\), \(\bar{d}(x_{\alpha_i}, y_{\alpha_i}) < \varepsilon\). Note that when \(\varepsilon > 1\), \(B_{\bar{\rho}}(\vect{x}, \varepsilon) = \mathbb{R}^J\), which is not what we desire. Instead, we need to define the open ball’s radius as \(\varepsilon' = \min\{\varepsilon, 1\}\). Then we have for all \(\vect{y} \in B_{\bar{\rho}}(\vect{x}, \varepsilon')\), \(\bar{d}(x_{\alpha_i}, y_{\alpha_i}) = d(x_{\alpha_i}, y_{\alpha_i}) < \varepsilon'\), i.e. \(y_{\alpha_i} \in (x_{\alpha_i} - \varepsilon', x_{\alpha_i} + \varepsilon') \subset B_{\alpha_i}\). For other coordinate indices \(\alpha \notin \{\alpha_1, \cdots, \alpha_n\}\), because \(B_{\alpha} = \mathbb{R}\), \(y_{\alpha} \in (x_{\alpha} - \varepsilon', x_{\alpha} + \varepsilon') \subset B_{\alpha}\) holds trivially.

Therefore, the uniform topology is finer than the product topology.

b) Prove the uniform topology is strictly finer than the product topology, when \(J\) is infinite.

When \(J\) is infinite, for an open ball \(B_{\bar{\rho}}(\vect{x}, \varepsilon)\) with \(\varepsilon \in (0, 1]\), there are infinite number of coordinate components comprising this open ball which are not equal to \(\mathbb{R}\). Therefore, there is no basis element for the product topology which is contained in \(B_{\bar{\rho}}(\vect{x}, \varepsilon)\).

c) Prove the box topology is finer than the uniform topology.

For any basis element \(B_{\bar{\rho}}(\vect{x}, \varepsilon)\) for the uniform topology, when \(\varepsilon > 1\), \(B_{\bar{\rho}}(\vect{x}, \varepsilon) = \mathbb{R}^J\). Then for all \(\vect{y} \in B_{\bar{\rho}}(\vect{x}, \varepsilon)\), any basis element for the box topology containing this \(\vect{y}\) is contained in \(B_{\bar{\rho}}(\vect{x}, \varepsilon)\).

When \(\varepsilon \in (0, 1]\), \(\bar{d}\) is equivalent to \(d\) on \(\mathbb{R}\). Then for all \(\vect{y} \in B_{\bar{\rho}}(\vect{x}, \varepsilon)\), we have

\[
\sup_{\alpha \in J} \{ \bar{d}(x_{\alpha}, y_{\alpha}) \} = \sup_{\alpha \in J} \{ d(x_{\alpha}, y_{\alpha}) \} < \varepsilon.
\]

Therefore, for all \(\alpha \in J\), \(y_{\alpha} \in (x_{\alpha} - \varepsilon, x_{\alpha} + \varepsilon)\). Then we may tend to say that \(\prod_{\alpha \in J} (x_{\alpha} - \varepsilon, x_{\alpha} + \varepsilon)\) is a basis element for the box topology containing \(\vect{y}\), which is contained in \(B_{\bar{\rho}}(\vect{x}, \varepsilon)\). However, this is not true. Because \(\vect{y}\) can be thus selected such that as \(\alpha\) changes in \(J\), \(\bar{d}(x_{\alpha}, y_{\alpha})\) can be arbitrarily close to \(\varepsilon\), which leads to \(\sup_{\alpha \in J} \{ \bar{d}(x_{\alpha}, y_{\alpha}) \} = \varepsilon\). This makes \(\vect{y} \notin B_{\bar{\rho}}(\vect{x}, \varepsilon)\) and \(\prod_{\alpha \in J} (x_{\alpha} - \varepsilon, x_{\alpha} + \varepsilon)\) is not contained in \(B_{\bar{\rho}}(\vect{x}, \varepsilon)\). Such example can be given for \(\mathbb{R}^{\omega}\), where we let \(\vect{y} = \{y_n = x_n + \varepsilon - \frac{\varepsilon}{n}\}_{n \in \mathbb{Z}_+}\). When \(n \rightarrow \infty\), \(\bar{d}(x_n, y_n) \rightarrow \varepsilon\).

With this point clarified, a smaller basis element should be selected for the box topology, such as \(\prod_{\alpha \in J} (x_{\alpha} - \frac{\varepsilon}{2}, x_{\alpha} + \frac{\varepsilon}{2})\). For all \(\vect{y}\) in this basis element, \(\sup_{\alpha \in J} \{ \bar{d}(x_{\alpha}, y_{\alpha}) \} \leq \frac{\varepsilon}{2} < \varepsilon\). Hence \(\prod_{\alpha \in J} (x_{\alpha} - \frac{\varepsilon}{2}, x_{\alpha} + \frac{\varepsilon}{2}) \subset B_{\bar{\rho}}(\vect{x}, \varepsilon)\) and the box topology is finer than the uniform topology.

Remark: The proof in the book for this part inherently adopts the definition of open set via topological basis introduced in section 13.

d) Prove the box topology is strictly finer than the uniform topology, when \(J\) is infinite.

Analysis: Because the open ball in the uniform topology sets an upper bound on the dimension of each coordinate component, it can be envisioned that if we construct a basis element for the box topology with the dimension for each coordinate component approaching to zero, it cannot cover any open ball in the uniform topology with a fixed radius no matter how small it is.

Let’s consider the case in \(\mathbb{R}^{\omega}\). Select a basis element for the box topology as \(\prod_{n = 1}^{\infty} (x_n - \frac{c}{n}, x_n + \frac{c}{n})\) with \((c > 0)\). Then for all \(\varepsilon > 0\), there exists \(\vect{y}_0 \in B_{\bar{\rho}}(\vect{x}, \varepsilon)\) such that \(\vect{y}_0 \notin \prod_{n = 1}^{\infty} (x_n - \frac{c}{n}, x_n + \frac{c}{n})\). For example, we can select \(\vect{y}_0 = (x_n + \frac{\varepsilon}{2})_{n \geq 1}\). Then there exists an \(n_0 \in \mathbb{Z}_+\) such that when \(n > n_0\), \(\frac{c}{n} < \frac{\varepsilon}{n}\) and \(y_n \notin (x_n - \frac{c}{n}, x_n + \frac{c}{n})\). Hence, the box topology is strictly finer than the uniform topology.

James Munkres Topology: Theorem 20.4的更多相关文章

  1. James Munkres Topology: Theorem 20.3 and metric equivalence

    Proof of Theorem 20.3 Theorem 20.3 The topologies on \(\mathbb{R}^n\) induced by the euclidean metri ...

  2. James Munkres Topology: Theorem 19.6

    Theorem 19.6 Let \(f: A \rightarrow \prod_{\alpha \in J} X_{\alpha}\) be given by the equation \[ f( ...

  3. James Munkres Topology: Theorem 16.3

    Theorem 16.3 If \(A\) is a subspace of \(X\) and \(B\) is a subspace of \(Y\), then the product topo ...

  4. James Munkres Topology: Sec 18 Exer 12

    Theorem 18.4 in James Munkres “Topology” states that if a function \(f : A \rightarrow X \times Y\) ...

  5. James Munkres Topology: Sec 22 Exer 6

    Exercise 22.6 Recall that \(\mathbb{R}_{K}\) denotes the real line in the \(K\)-topology. Let \(Y\) ...

  6. James Munkres Topology: Sec 22 Exer 3

    Exercise 22.3 Let \(\pi_1: \mathbb{R} \times \mathbb{R} \rightarrow \mathbb{R}\) be projection on th ...

  7. James Munkres Topology: Lemma 21.2 The sequence lemma

    Lemma 21.2 (The sequence lemma) Let \(X\) be a topological space; let \(A \subset X\). If there is a ...

  8. James Munkres Topology: Sec 37 Exer 1

    Exercise 1. Let \(X\) be a space. Let \(\mathcal{D}\) be a collection of subsets of \(X\) that is ma ...

  9. James Munkres Topology: Sec 22 Example 1

    Example 1 Let \(X\) be the subspace \([0,1]\cup[2,3]\) of \(\mathbb{R}\), and let \(Y\) be the subsp ...

随机推荐

  1. Djangon

    2.怎么样从浏览器获得用户输入的数据? request.浏览器的八种申请方式.get(条件) request.浏览器的八种申请方式[] request.浏览器的八种申请方式(这里什么也不要写)> ...

  2. js变速动画函数封装 回调函数及层级还有透明度

    //点击按钮,改变宽度到达一个目标值,高度到达一个目标值 //获取任意一个元素的任意一个属性的当前的值---当前属性的位置值 function getStyle(element, attr) { re ...

  3. 获取本地的jvm信息,进行图形化展示

    package test1; import java.lang.management.CompilationMXBean; import java.lang.management.GarbageCol ...

  4. 【WC2018】即时战略

    题目描述 小M在玩一个即时战略(Real Time Strategy)游戏.不同于大多数同类游戏,这个游戏的地图是树形的. 也就是说,地图可以用一个由 n个结点,n?1条边构成的连通图来表示.这些结点 ...

  5. wp系统笔记

    1.了解了justified-image-grid是wp插件,继而查看wp,wp是一个免费建站系统.内置主题和插件.博客,CMS,企业站等.php+mysql 环境至少5.0以上 2.在zh-word ...

  6. PTA数组作业一查找整数

    代码 #include<stdio.h> int main(void){ int a[20],n,flag=0,x; int i; scanf("%d%d",& ...

  7. js上传图片压缩,并转化为base64

    <input type="file" onchange="startUpload(this,'front')" id="renm"/& ...

  8. Hadoop记录-JMX参数

    Yarn metrics参数说明 获取Yarn jmx信息:curl -i http://xxx:8088/jmx Hadoop:service=ResourceManager,name=FSOpDu ...

  9. beanPostProcessor与beanFactoryPostProcessor

    BeanFactoryPostProcessor的典型应用:PropertyPlaceholderConfigurer BeanFactoryPostProcessor会在所有的bean配置载入之后执 ...

  10. 数字化IT人才与组织

    企业的数字化目标 数字时代需要怎样的IT 数字化平台战略 产品一体化交付能力 产品设计与规划的能力 路线图 数字人才框架 Tips: 赋能授权(Empowerment)是近年来应最多的商业语汇之一.赋 ...