(Remark: The proof presented in this post is a reorganization and interpretation of that given by James Munkres in his book "Topology".)

Theorem 37.3 (Tychonov Theorem) The product of arbitrary number of compact spaces is compact in the product topology, i.e.
\[
X = \prod_{i \in I} X_i
\]
is compact if \(X_i\) is compact for all \(i \in I\).

Basic thoughts about proving the Tychonov Theorem

  • Although compactness is originally defined via finite open covering, it has another equivalent formulation via finite intersection property (FIP) of a collection of closed sets. The compactness of the product space \(X\) will be proved by following this FIP route.
  • A strict partial order based on the set inclusion relation will be assigned to the system or superset of collections of subsets in the product space which have the FIP. It can be envisioned that every such collection of subsets dwells in a chain which has an upper bound. The Zorn's Lemma can then be used to prove the existence of a maximal collection \(\mathcal{D}\).
  • For any collection \(\mathcal{A}\) of subsets in the product space \(X\) having the FIP, a point \(\vect{x}\) in \(X\) will be constructed with each of its component belonging to the intersection of the closures of the corresponding component of each subset in \(\mathcal{A}\).
  • The properties of the maximal collection \(\mathcal{D}\) will be explored, which can be used to prove that any subbasis and hence basis element containing the constructed \(\vect{x}\) belongs to \(\mathcal{D}\). Based on these conclusions, this \(\vect{x}\) can be proved to be in the intersection of all the elements in \(\mathcal{A}\) and the Tychonov theorem is proved.

Compactness and finite intersection property

Lemma 26.9 A topological space \(X\) is compact if and only if every collection \(\mathcal{F}\) of closed sets in \(X\) with the finite intersection property has a nonempty intersection.

Proof: This lemma will be proved by using reduction to absurdity.

  1. Prove in the forward direction

    Let \(X\) be a compact space. For any of its opening covering \(\{U_i\}_{i \in I}\), there exists an finite sub-covering \(\{U_{i_k}\}_{k=1}^n\), from which we have
    \[
    \bigcap_{i \in I} U_i^c = \varPhi
    \]

    and

    \[
    \bigcap_{k=1}^n U_{i_k}^c = \varPhi,
    \]

    where each \(U_i^c\) is a closed set in \(X\). From this we learns that if a topological space \(X\) is compact, for any collection of closed sets in \(X\) having an empty intersection, it must have a finite sub-collection, which also has an empty intersection.

    Then, assume that there exists a collection \(\mathcal{F}\) of closed sets with their intersection being empty. \(\mathcal{F}\) must have a finite sub-collection which also has an empty intersection. However, this contradicts the fact that \(\mathcal{F}\) should have the FIP. Therefore, every collection \(\mathcal{F}\) of closed sets must has a nonempty intersection.

  2. Prove in the inverse direction

    Assume \(X\) is not compact, then there exists an open covering \(\{U_i\}_{i \in I}\) of \(X\), which has no finite sub-covering. From this, we have
    \[
    \bigcap_{i \in I} U_i^c = \varPhi
    \]
    and for any of its finite sub-collections \(\{U_{i_k}\}_{k = 1}^n\),
    \[
    \bigcap_{k = 1}^n U_{i_k}^c \neq \varPhi.
    \]
    Therefore, the collection of closed sets \(\{U_i^c\}_{i \in I}\) has the FIP. According to the given condition, the intersection of all \(U_i^c\) should be nonempty, which contradicts the conclusion derived from the assumption.

Summarizing the above two steps, Lemma 26.9 is proved.

Construction of the maximal collection \(\mathcal{D}\)

Lemma 37.1 Let \(X\) be a set and \(\mathcal{A}\) be a collection of subsets of \(X\) having the finite intersection property. Then there exists a collection \(\mathcal{D}\) of subsets of \(X\) such that \(\mathcal{A} \subset \mathcal{D}\) and \(\mathcal{D}\) has the finite intersection property. In addition, there is no larger collection, which also has the finite intersection property, containing \(\mathcal{D}\).

Proof: Let \(\mathbb{A}\) be a superset, each element of which has the FIP and contains the collection \(\mathcal{A}\). Assign this superset \(\mathbb{A}\) with a strict partial order based on the proper set inclusion relation \(\subsetneq\). Then let \(\mathbb{B}\) be a subset of \(\mathbb{A}\), which itself is also a superset, such that \(\mathbb{B}\) is simply ordered by \(\subsetneq\).

Let \(\mathcal{C}\) be the union of all the elements in \(\mathbb{B}\), i.e.
\[
\mathcal{C} = \bigcup_{\mathcal{B} \in \mathbb{B}} \mathcal{B}.
\]
Next, we need to show that \(\mathcal{C}\) belongs to \(\mathbb{A}\) and is an upper bound of the chain \(\mathbb{B}\).

The upper bound property based on the proper set inclusion relation has already been ensured by the construction of \(\mathcal{C}\) via the union operation. We only need to prove \(\mathcal{C} \in \mathbb{A}\), which requires the following two conditions to be fulfilled:

  1. \(\mathcal{C}\) contains \(\mathcal{A}\).

    This is obvious, because for every \(\mathcal{B}\) in \(\mathbb{B}\), \(\mathcal{A}\) is contained in \(\mathcal{B}\) and \(\mathcal{B}\) is contained in \(\mathcal{C}\).

  2. \(\mathcal{C}\) has the FIP.

    Let \(\{C_1, \cdots, C_n\}\) be a finite collection selected from \(\mathcal{C}\). Because \(\mathcal{C}\) is the union of all the collections in the superset \(\mathbb{B}\), there exists a \(\mathcal{B}_i\) in \(\mathbb{B}\) such that \(C_i \in \mathcal{B}_i\) for all \(i = 1, \cdots, n\). Then \(\{\mathcal{B}_1, \cdots, \mathcal{B}_n\}\) is a finite chain which must have a largest element and we here let it be \(\mathcal{B}_k\). Hence we have \(C_i \in \mathcal{B}_k\) for all \(i = 1, \cdots, n\).

    Because each element of \(\mathbb{B}\) including \(\mathcal{B}_k\) is also an element of \(\mathbb{A}\) which has the FIP and the finite collection \(\{C_1, \cdots, C_n\}\) is contained in \(\mathcal{B}_k\), \(\mathcal{C}\) has the FIP.

Summarizing the above, we know that \(\mathcal{C}\) is really an upper bound in \(\mathbb{A}\) of the chain \(\mathbb{B}\). According to the Zorn's Lemma, there is a maximal element, let it be \(\mathcal{D}\), such that \(\mathcal{D}\) has the FIP and contains \(\mathcal{A}\).

Properties of the maximal collection \(\mathcal{D}\)

Lemma 37.2 Let \(X\) be a set and \(\mathcal{D}\) be a collection of subsets of \(X\) which is maximal with respect to the FIP and strict partial order based on the proper set inclusion relation. Then:

  1. Any finite intersection of elements of \(\mathcal{D}\) is also an element of \(\mathcal{D}\).
  2. If a subset of \(X\) intersects every element of \(\mathcal{D}\), this subset is also an element of \(\mathcal{D}\).

Proof:

  • Let \(B\) be the finite intersection of elements in \(\mathcal{D}\). Let's see if we can construct a collection which is larger than \(\mathcal{D}\) by appending the element \(B\) to the collection \(\mathcal{D}\). If this is not achievable, we know that the appended element \(B\) must belong to \(\mathcal{D}\).

    Let \(\mathcal{E} = \mathcal{D} \cup \{B\}\). Because \(\mathcal{D} \subset \mathcal{E}\), \(\mathcal{D}\) and \(\mathcal{E}\) belong to the same chain. Then we check if \(\mathcal{E}\) has the FIP.

    • When the finite number of elements extracted from \(\mathcal{E}\) are all selected from \(\mathcal{D}\), their intersection is not empty due to the FIP of \(\mathcal{D}\).

    • When the selected finite number of elements include \(B\), their intersection has the following formulation:
      \[
      D_1 \cap \cdots \cap D_m \cap B,
      \]
      where \(D_1, \cdots, D_m \in \mathcal{D}\).

    Because \(B\) is also a finite intersection of elements in \(\mathcal{D}\), \(D_1 \cap \cdots \cap D_m \cap B\) is a finite intersection of elements in \(\mathcal{D}\) as well, which is of course not empty.

    Summarizing the above, we know that \(\mathcal{E}\) has the FIP and \(\mathcal{D} \subset \mathcal{E}\). Because \(\mathcal{D}\) is a maximal element, we have \(\mathcal{D} = \mathcal{E}\). Therefore, \(B \in \mathcal{D}\).

  • Let \(A\) be the subset of \(X\) which intersects every element of \(\mathcal{D}\). Similarly as above, let \(\mathcal{E} = \mathcal{D} \cup \{A\}\) and we have the following two facts:

    • When the finite number of elements are all selected from \(\mathcal{D}\), their intersection is nonempty due to the FIP of \(\mathcal{D}\).

    • When the selected finite number of elements include \(A\), their intersection has the following formulation:
      \[
      D_1 \cap \cdots \cap D_m \cap A.
      \]
      According to the already proved conclusion 1 in this lemma, \(D = D_1 \cap \cdots \cap D_m\) is also an element of \(\mathcal{D}\). Because \(A \cap D \neq \varPhi\) from the given condition, the intersection \(D_1 \cap \cdots \cap D_m \cap A\) is not empty.

    Summarizing the above, we know that \(\mathcal{E}\) has the FIP and is larger than \(\mathcal{D}\). Because \(\mathcal{D}\) is a maximal element, we have \(\mathcal{D} = \mathcal{E}\) and \(A \in \mathcal{D}\).

Tychonov Theorem

Finally, we come to the proof of the Tychonov Theorem.

Proof: Let \(\{X_i\}_{i \in I}\) be a collection of compact spaces. Their product is
\[
X = \prod_{i \in I} X_i.
\]
Let \(\mathcal{A}\) be any collection of subsets of \(X\) having the FIP. Then the closures of the elements in \(\mathcal{A}\) also have the FIP. As long as we can prove
\[
\bigcap_{A \in \mathcal{A}} \bar{A} \neq \varPhi,
\]
\(X\) is compact according to Theorem 26.9.

According to Lemma 37.1, there exists a maximal element \(\mathcal{D}\) in the sense of FIP and strict partial order based on the proper set inclusion relation. Because \(\mathcal{D}\) contains \(\mathcal{A}\), if
\[
\bigcap_{D \in \mathcal{D}} \bar{D} \neq \varPhi,
\]
there is also
\[
\bigcap_{A \in \mathcal{A}} \bar{A} \neq \varPhi.
\]
Let \(\pi_i: X \rightarrow X_i\) for all \(i \in I\) be the projection map. Because \(\mathcal{D}\) has the FIP, for a specific index \(i\), the collection of the component sets \(\{\pi_i(D) \vert D \in \mathcal{D} \}\) also has the FIP.

Because the component space \(X_i\) is compact, according to Theorem 26.9, there exists an \(x_i\) such that
\[
\begin{equation}
x_i \in \bigcap_{D \in \mathcal{D}} \overline{\pi_i(D)} \quad (\forall i \in I).
\label{eq:x_i_range}
\end{equation}
\]
Let all these \(\{x_i\}_{i \in I}\) form an element \(\vect{x}\) in the product space \(X\). We will prove that this \(\vect{x}\) really belongs to \(\cap_{D \in \mathcal{D}} \bar{D}\) in the following, during which the concept of subbasis is adopted, whose finite intersection forms the topological basis of the product space.

Let \(U_i\) be any open set in \(X_i\) containing \(x_i\) and \(\pi_i^{-1}(U_i)\) be the corresponding subbasis element. For all \(D \in \mathcal{D}\), we have
\[
D \cap \pi_i^{-1}(U_i) = \prod_{j \in I} \pi_j(D) \cap \pi_j(\pi_i^{-1}(U_i)).
\]
There are the following two cases:

  1. When \(j = i\), the corresponding component in the above product is \(\pi_i(D) \cap U_i\). Because of equation \eqref{eq:x_i_range} and \(U_i\) being any open set in \(X_i\) containing \(x_i\), there exists a \(y_i \in \pi_i(D) \cap U_i\), i.e. \(\pi_i(D) \cap U_i \neq \varPhi\).

    For if \(\pi_i(D) \cap U_i = \varPhi\), because \(U_i\) being any open set in \(X_i\) containing \(x_i\), then \(x_i \in \left( \overline{\pi_i(D)} \right)^c\), which contradicts the fact that \(x_i \in \overline{\pi_i(D)}\).

  2. When \(j \neq i\),
    \[
    \pi_j(D) \cap \pi_j(\pi_i^{-1}(U_i)) = \pi_j(D) \cap X_j = \pi_j(D).
    \]

Summarizing the above, we know that as long as we select a \(\vect{y}\) from \(D\) with its \(i\)th component being \(y_i \in \pi_i(D) \cap U_i\), we have \(\vect{y} \in D \cap \pi_i^{-1}(U_i)\) for all \(D \in \mathcal{D}\). According to Lemma 37.2 (2), the subbasis element \(\pi_i^{-1}(U_i)\) for all \(i \in I\) belongs to \(\mathcal{D}\). We also see that \(\vect{x} \in \pi_i^{-1}(U_i)\).

In addition, the finite intersection of these subbasis elements, which is a basis element of the product space, is not empty due to the FIP of \(\mathcal{D}\). Then according to Lemma 37.2 (1), the basis elements of \(X\) which contain \(\vect{x}\) also belong to \(\mathcal{D}\).

Because \(\mathcal{D}\) has the FIP, for all basis element \(B\) containing \(\vect{x}\) and for all element \(D\) of \(\mathcal{D}\), their intersection is not empty. Assume there exists a \(D_0 \in \mathcal{D}\) such that \(\vect{x} \notin \bar{D}_0\), or rather \(\vect{x} \in X - \bar{D}_0\), which is open in \(X\). Then there exits a basis element \(B_0\) containing \(\vect{x}\) such that \(B_0 \cap \bar{D}_0 = \varPhi\) and hence \(B_0 \cap D_0 = \varPhi\). This contradicts the fact that for all such basis element \(B\), \(B \cap D_0 \neq \varPhi\).

Now we arrive at the conclusion that for all \(D \in \mathcal{D}\), \(\vect{x} \in \bar{D}\), and for any collection \(\mathcal{A}\) of subsets in \(X\) having the FIP with \(\mathcal{D}\) being the maximal element on the same chain, \(\cap_{A \in \mathcal{A}} \bar{A} \neq \varPhi\). According to Lemma 26.9, the product space \(X\) is compact.

Tychonov Theorem的更多相关文章

  1. Parseval's theorem 帕塞瓦尔定理

    Source: wiki: Parseval's theorem As for signal processing, the power within certain frequency band = ...

  2. 利用Cayley-Hamilton theorem 优化矩阵线性递推

    平时有关线性递推的题,很多都可以利用矩阵乘法来解决. 时间复杂度一般是O(K3logn)因此对矩阵的规模限制比较大. 下面介绍一种利用利用Cayley-Hamilton theorem加速矩阵乘法的方 ...

  3. Kernel Methods (6) The Representer Theorem

    The Representer Theorem, 表示定理. 给定: 非空样本空间: \(\chi\) \(m\)个样本:\(\{(x_1, y_1), \dots, (x_m, y_m)\}, x_ ...

  4. 加州大学伯克利分校Stat2.2x Probability 概率初步学习笔记: Section 4 The Central Limit Theorem

    Stat2.2x Probability(概率)课程由加州大学伯克利分校(University of California, Berkeley)于2014年在edX平台讲授. PDF笔记下载(Acad ...

  5. 生成树的个数——基尔霍夫定理(Matrix-Tree Theorem)

    树有很多种形态,给定结点个数,求生成不同形态二叉树的个数,显然要用到Catalan数列. 那如果给定一个图(Graph)\(G=(V,E)\),要求其最小生成树G',最好的方法莫过于Prim或Krus ...

  6. uva 11178 - Morley's Theorem

    http://uva.onlinejudge.org/index.php?option=com_onlinejudge&Itemid=8&page=show_problem&p ...

  7. Dirichlet's Theorem on Arithmetic Progressions 分类: POJ 2015-06-12 21:07 7人阅读 评论(0) 收藏

    Dirichlet's Theorem on Arithmetic Progressions Time Limit: 1000MS   Memory Limit: 65536K Total Submi ...

  8. [转]A plain english introduction to cap theorem

    Kaushik Sathupadi Programmer. Creator. Co-Founder. Dad. See all my projects and blogs → A plain engl ...

  9. hdu 1788 Chinese remainder theorem again(最小公倍数)

    Problem Description 我知道部分同学最近在看中国剩余定理,就这个定理本身,还是比较简单的: 假设m1,m2,-,mk两两互素,则下面同余方程组: x≡a1(mod m1) x≡a2( ...

随机推荐

  1. thinkphp提示不支持mysqli或者mysql

    确认php是否安装了php-mysql组件,nginx或apache的php服务进程

  2. 统一门户与业务系统的sso整合技术方案(单点登录)

    一.单点登录(SSO,Single Sign On)整合目前计划接入统一门户的所有业务系统均为基于JavaEE技术的B/S架构系统.由于统一门户的单点登录技术选用的是JA-SIG组织开发的Cas Se ...

  3. Java:自动设置环境变量(转载)

    引用: https://blog.csdn.net/qq_22498277/article/details/72149038 脚本下载地址:http://files.cnblogs.com/floww ...

  4. Mysql41道练习题

    1.自行创建测试数据 2.查询“生物”课程比“物理”课程成绩高的所有学生的学号.ps:针对的是自己的生物成绩比物理成绩高,再把符合条件的学生的学号查出来: # 查到 生物 和 物理的 id: sele ...

  5. 【原创】大叔问题定位分享(33)beeline连接presto报错

    hive2.3.4 presto0.215 使用hive2.3.4的beeline连接presto报错 $ beeline -d com.facebook.presto.jdbc.PrestoDriv ...

  6. Go语言从入门到放弃(三) 布尔/数字/格式化输出

    本章主要介绍Go语言的数据类型 布尔(bool) 布尔指对或者错,也就是说bool只有两个值, True 或 False 两个类型相同的值可以使用比较运算符来得出一个布尔值 当两个值是完全相同的情况下 ...

  7. 彻底搞透OAuth 2.0

    OAuth是一个关于授权(authorization)的开放网络标准,在全世界得到广泛应用,目前的版本是2.0版. 本文对OAuth 2.0的设计思路和运行流程,做一个简明通俗的解释,主要参考材料为R ...

  8. Java红黑树详谈

    定义 红黑树的主要是想对2-3查找树进行编码,尤其是对2-3查找树中的3-nodes节点添加额外的信息.红黑树中将节点之间的链接分为两种不同类型,红色链接,他用来链接两个2-nodes节点来表示一个3 ...

  9. easyui datagrid 隔行变色

    easyui datagrid  隔行变色 一:实现样图 二:实现代码 $('#dataGrid').datagrid({ rowStyler:function(index,row){ if (row ...

  10. Django项目的创建及基本使用

    安装步骤 Django是Python进行Web开发的框架,目前应用比较广泛.使用python进行Web开发,能够很快的搭建所需的项目,可以运用于原型开发,也可以部署到实际的应用环境. 使用Django ...