Uniform space

In mathematics, and more specifically in topology, the notions of a uniform structure and a uniform space generalize the notions of a metrics (distance function) and a metric space respectively. As a human activity, the theory of uniform spaces is a chapter of general topology. From the formal point of view, the notion of a uniform space is a sibling of the notion of a topological space. While uniform spaces are significant for mathematical analysis, the notion seems less fundamental than that of a topological space. The notion of uniformity is auxiliary rather than an object to be studied for their own sake (specialists on uniform spaces may disagree though).

For two points of a metric space, their distance is given, and it is a measure of how close each of the given two points is to another. The notion of uniformity catches the idea of two points being near one another in a more general way, without assigning a numerical value to their distance. Instead, given a subset $W\subseteq X\times X\$, we may say that two points  $x,y\in X\$ are W-near one to another, when $\ (x,y)\in W$; certain such sets $W\subseteq X\times X\$ are called entourages (see below), and then Roman Sikorski would write suggestively:

$d(x,y)<W\$

meaning that this whole mathematical phrase stands for: $W\$ is an entourage, and $\ (x,y)\in W$.  Thus we see that in the general case of uniform spaces, the distance between two points is (not measured but) estimated by the entourages to which the ordered pair of the given two points belongs.

A different but equivalent approach was developed by Soviet topologists. They axiomatized the notion of two sets approaching one another (infinitely closely, possibly overlapping). In terms of entourages, two sets approach one another if for every entourage $W\$ there is an ordered pair of points $\ (x,y)$, one from each of the given two sets, for which the above Sikorski's inequality holds.

Historical remarks

The uniform ideas, in the context of finite dimensional real linear spaces (Euclidean spaces), appeared already in the work of the pioneers of the precision in mathematical analysis (A.-L. Cauchy, E. Heine).Next, George Cantor constructed the real line by metrically completing the field of rational numbers, while Frechet introduced metric spaces. Then Felix Hausdorff extended the Cantor's completion construction onto arbitrary metric spaces. General uniform spaces were introduced by Andre Weil in 1937. A different but equivalent construction was introduced and developed by Soviet topologists.

Definition

Given a set $\ X$, and $V,W\subseteq X\times X$, let's use the notation:

$\Delta _{X}\ :=\ \{(x,x):x\in X\}$

and

$V^{-1}\ :=\ \{(y,x):(x,y)\in V\}$

and

$W\circ \,V:=\{(x,z):\exists _{y\in X}\ \left((x,y)\in V,\ \ (y,z)\in W\right)\}$

An ordered pair $(X,{\mathcal {U}})$, consisting of a set $\ X$ and a family ${\mathcal {U}}$ of subsets of $\ X\times X$, is called a uniform space, and ${\mathcal {U}}$ is called a uniform structure in $\ X$, if the following five properties (axioms) hold:

1. ${\mathcal {U}}\neq \emptyset$
2. $\forall _{W\in {\mathcal {U}}}\ \Delta _{X}\subseteq W$
3. $\forall _{V\in {\mathcal {U}}}\ (V\subseteq W\subseteq X\times X\ \Rightarrow \ W\in {\mathcal {U}})$
4. $\forall _{V,W\in {\mathcal {U}}}\ V\cap W^{-1}\in {\mathcal {U}}$
5. $\forall _{W\in {\mathcal {U}}}\exists _{V\in {\mathcal {U}}}\ V\circ V\subseteq W$

Members of ${\mathcal {U}}$ are called entourages.

Example:   $X\times X\$  is an entourage of every uniform structure in $\ X$.

Two extreme examples

The single element family ${\mathcal {U}}:=\{X\times X\}$ is a uniform structure in $\ X$; it is called the weakest uniform structure (in $\ X$).

Family

${\mathcal {U}}\ :=\ \{W\subseteq X\times X:\Delta _{X}\subseteq W\}$

is a uniform structure in $\ X$ too; it is called the strongest uniform structure or the discrete uniform structure in $\ X$.

Uniform base

A family ${\mathcal {B}}$ is called to be a base of a uniform structure ${\mathcal {U}}$ in $\ X$ if  ${\mathcal {U}}={\mathcal {U}}_{\mathcal {B}}$, where:

${\mathcal {U}}_{\mathcal {B}}\ :=\ \{W\subseteq X\times X:\exists _{B\in {\mathcal {B}}}\ B\subseteq W\}$

Remark  Uniform bases are also called fundamental systems of neighborhoods of the uniform structure (by Bourbaki).

Instead of starting with a uniform structure, we may begin with a family ${\mathcal {B}}$. If family ${\mathcal {U}}_{\mathcal {B}}\$ is a uniform structure in $\ X$, then we simply say that ${\mathcal {B}}$ is a uniform base (without mentioning explicitly any uniform structure).

Metric spaces

Let $\ (X,d)$ be a metric space. Let

$B_{t}\ :=\ \{(x,y):d(x,y)<t\}$

for every real $\ t>0$.  Define now

${\mathcal {B}}_{d}\ :=\ \{B_{t}:t>0\}$

and finally:

${\mathcal {U}}_{d}\ :=\ \{W:\exists _{t}\ B_{t}\subseteq W\subseteq X\times X\}$

Then ${\mathcal {U}}_{d}$ is a uniform structure in $\ X$; it is called the uniform structure induced by metric $\ d$  (in $\ X$).

Family ${\mathcal {B}}_{d}\$ is a base of the structure ${\mathcal {U}}_{d}\$ (see above). Observe that:

• $\Delta _{X}\ \subseteq \ B_{t}$
• $B_{t}^{-1}\ =\ B_{t}$
• $B_{s}\cap B_{t}\ =\ B_{\,\min(s,t)}$
• $B_{t}\circ B_{t}\ \subseteq \ B_{2\cdot t}$

for arbitrary real numbers  $\ s,t>0$.  This is why ${\mathcal {B}}_{d}\$ is a uniform base, and ${\mathcal {U}}_{d}$ is a uniform structure (see the axioms of the uniform structure above).

Remark (!)   Everything said in this text fragment is true more generally for arbitrary pseudo-metric space $\ (X,d)$; instead of the standard metric axiom:

$d(x,y)=0\ \Leftrightarrow x=y\$

a pseudo-metric space is assumed to satisfy only a weaker axiom:

$d(x,x)=0\$

(for arbitrary  $\ x,y\in X$).

The induced topology

First another piece of auxiliary notation--given a set $\ X$, and $W\subseteq X\times X$, let

$W(x)\ :=\ \{y:(x,y)\in W\}=W\cap (\{x\}\times X)$

Let $(X,{\mathcal {U}})$ be a uniform space. Then families

${\mathcal {U}}_{x}\ :=\ \{W(x):W\in {\mathcal {U}}\}$

where $\ x$ runs over $\ X$, form a topology defining system of neighborhoods in $\ X$. The topology itself is defined as:

${\mathcal {T}}\ :=\ \{G\subseteq X:\forall _{x\in G}\ G\in {\mathcal {U}}_{x}\}$

• The topology induced by the weakest uniform structure is the weakest topology.
• The topology induced by the strongest (discrete) uniform structure is the strongest (discrete) topology.
• The topology induced by a metrics is the same as the topology induced by the uniform structure induced by that metrics.

Uniform continuity

Let $(X,{\mathcal {U}})$ and $(Y,{\mathcal {V}})$ be uniform spaces. Function $\ f:X\rightarrow Y$ is called uniformly continuous if

$\forall _{V\in {\mathcal {V}}}\ (f\times f)^{-1}(V)\in {\mathcal {U}}$

A more elementary calculus δε-like equivalent definition would sound like this (UV play the role of δε respectively):

$f\$  is uniformly continuous if (and only if) for every  $V\in {\mathcal {V}}\$  there exists  $U\in {\mathcal {U}}\$  such that for every  $x',x''\in X\$  if  $(x',x'')\in {\mathcal {U}}\$  then  $(f(x'),f(x''))\in {\mathcal {V}}$.

Every uniformly continuous map is continuous with respect to the topologies induced by the ivolved uniform structures.

Example Every constant map from one uniform space to another is uniformly continuous.

The category of the uniform spaces

The identity function $\ {\mathcal {I}}_{X}:X\rightarrow X$, which maps every point onto itself, is a uniformly continuous map of $(X,{\mathcal {U}})$ onto itself, for every uniform structure ${\mathcal {U}}$ in $\ X$.

Also, if $\ f:X\rightarrow Y\$ and $\ g:Y\rightarrow Z\$ are uniformly continuous maps of $\ (X,{\mathcal {U}})\$ into $\ (Y,{\mathcal {V}})\$, and of $\ (Y,{\mathcal {V}})\$ into $\ (Z,{\mathcal {W}})\$ respectively, then $\ g\circ f:X\rightarrow Z\$ is a uniformly continuous map of $\ (X,{\mathcal {U}})$ into $\ (Z,{\mathcal {W}})$.

These two properties of the uniformly continuous maps mean that the uniform spaces (as objects) together with the uniform maps (as morphisms) form a category  ${\mathit {US}}\$  (for Uniform Spaces).

Remark A morphism in category  ${\mathit {US}}\$  is more than a set function; it is an ordered triple consisting of two objects (domain and range) and one set function (but it must be uniformly continuous). This means that one and the same function may serve more than one morphism in  $\ {\mathit {US}}$.