Most topology texts go on directly to give definition of topology, then they give some examples and that's it, like they directly tell you right

Let $X$ be a set and let $τ$ be a family of subsets of $X$. Then $τ$ is called a topology on $X$ if:

  1. Both the empty set and $X$ are elements of $τ$
  2. Any union of elements of $τ$ is an element of $τ$
  3. Any intersection of finitely many elements of $τ$ is an element of $τ$

But why did we define it this way? What's the intuition?

Does anyone know a good text on topology which gives the intution behind the concepts, ...etc ?

  • $\begingroup$ Topology by James Munkres $\endgroup$
    – K_user
    Commented Jan 3, 2016 at 15:15
  • 3
    $\begingroup$ @Suhail i was really like struggling with munkres book, that's why i asked this question right $\endgroup$
    – user153330
    Commented Jan 3, 2016 at 15:45
  • 3
    $\begingroup$ You might want to learn real analysis in one variable first. That should provide a plethora of concrete examples of the concepts and definitions. $\endgroup$
    – Future
    Commented Jan 3, 2016 at 16:36
  • $\begingroup$ A lot of the motivation for topology was an attempt to really understand what it means for a function to be continuous - to strip it down to the bare minimum. You've seen $\epsilon-\delta$ definitions, these are really open sets, which means we can do better by getting arid of the concept of distance and focusing on the sets. Of course, like all branches of mathematics, it took on a life of its own and was realized to be a useful branch of study by itself. $\endgroup$
    – Matthew
    Commented Jan 4, 2016 at 6:04
  • $\begingroup$ Undergraduate Topology by Robert H. Kasriel might be helpful for what you want. See my comments at this 28 March 2006 sci.math post archived at Math Forum. $\endgroup$ Commented Jan 4, 2016 at 14:43

6 Answers 6


Here are some general pointers for gaining intuition in topology:

  1. Learn lots of examples early, and use them to guide your understanding. Take the definition of a topology, for instance. The original motivation for this definition comes from familiar topological spaces, such as the real numbers or, more generally, $\mathbb R^n$ or, more generally still, metric spaces. Learn the definition of continuous maps $\mathbb R^m\to \mathbb R^n$ and between metric spaces in general and then try to understand why the 'open-set' definition of a continuous map is equivalent to these definitions. At this point, it is natural to ask how far we can generalize this definition. Topology is really about replacing '$\epsilon$-balls' in metric spaces with more general 'basic open neighbourhoods' that have precisely the right properties that let us make sense of concepts like 'continuous map' or 'small neighbourhood' that we're used to from real analysis.

  2. Learn how to draw pictures of topological spaces. A seasoned topologist will naturally draw the diagram

    for an open set $U$ contained in a topological space $X$ or

    for the product space $X\times Y$, even if the spaces don't actually look like that at all. Drawing a diagram will help you get intuition for writing actual proofs.

  3. Recognize that sometimes you're just going to have to do a lot of topology. The definition of a compact topological space is notoriously difficult for newcomers to the subject to internalize. Looking back at my own mathematical development, I don't think that there's anything that anyone could have said to me at the time that would have helped me understand it better. After a few years of using this definition, and working with compact spaces - primarily the closed interval $[0,1]$, I've got a much better understanding of its importance. Indeed, my advice to anyone who wants to understand compactness is to learn a proof of the Heine-Borel theorem (i.e., $[0,1]$ is compact) and then go back and write new proofs of the following theorems from real analysis using only the fact that $[0,1]$ is a compact topological space:

    • the Bolzano-Weierstrass theorem
    • every continuous function $[0,1]\to\mathbb R$ is bounded
    • the Lebesgue number lemma
    • the closed graph theorem: a function $f\colon[0,1]\to\mathbb R$ is continuous if and only if its graph $$\Gamma_f=\{(x,f(x))\colon x\in\mathbb R\}\subset[0,1]\times\mathbb R$$ is a closed set.
  4. Keep asking (yourself) questions. You're doing exactly the right thing by questioning the definitions you're seeing. If you blindly accept every definition you're taught without questioning whether it's natural or 'correct' then you'll find that you get to the end of a course in topology without really understanding anything you've been taught. Every time you see a definition, ask yourself 'Why has it been defined this way?' At the same time...

  5. Understand that there's no hurry. If you don't immediately get why a definition is used, don't worry about it and try and move on. Topology has been gone over and refined many times in the hundred or so years it's been around and you can be sure that the definitions you are seeing are natural and very useful. You can also be sure that, over the course of your studies in mathematics, you will come across topology again and again, and this will give you a chance to keep re-asking the questions you've been asking yourself. Each time you'll get more and more answers.

  6. (optional) Learn equivalent definitions. The reason this is optional is that plenty of people have survived perfectly well with the usual definitions from topology, and you certainly shouldn't spend your time learning lots of other definitions if you're having trouble with the existing ones. However, it can be useful to learn some alternative ways of looking at things. For example, here are some alternatives to the 'open set' definition of a topology:

    • System of basic open neighbourhoods - This is pretty similar to the 'open set definition', but rather than requiring that our collection of sets be closed under unions and all finite intersections, we only require that the intersection of two basic open neighbourhoods can be written as the union of basic open neighbourhoods. This definition is technically less precise than the usual definition, since different systems of b.o.n.s can give rise to the same topology, but it is sometimes more natural. For example, the topology on a metric space is induced by the system of basic open neighbourhoods given by $\epsilon$-balls $B(x,\epsilon)$.

    • Closure operator It's interesting that the topology on a space $X$ can be deduced from the closure operator $\text{Cl}\colon\mathcal P(X)\to\mathcal P(X)$. This gives rise to an equivalent definition of a topological space; see Wikipedia.

    For compactness:

    • Sequential compactness. This only works for metric spaces, but is still fun. A metric space is compact if and only if it is sequentially compact - every sequence has a convergent subsequence

    • Categorical compactness. A topological space $X$ is compact if and only if for every topological space $Y$ the projection map $\pi_Y\colon X\times Y\to Y$ is a closed map. See this note.

  • $\begingroup$ Wow, what an answer! do you mind (for completeness) to give a few references? $\endgroup$
    – user153330
    Commented Jan 3, 2016 at 16:14
  • $\begingroup$ @user153330 I can try. What references do you mean? $\endgroup$ Commented Jan 3, 2016 at 16:25
  • $\begingroup$ some good textbooks on topology which focus on intuition and give plenty of examples $\endgroup$
    – user153330
    Commented Jan 3, 2016 at 16:43
  • $\begingroup$ @user153330 I suggest working through the online notes found at dpmms.cam.ac.uk/~twk/Top.pdf. Though they don't really focus on intuition, they do give examples, and you'll gain the intuition by working through the proofs (all theorems are given without proof and you are encouraged to find the proofs yourself. Hints and the proofs themselves are found in the appendix if you get stuck.) $\endgroup$ Commented Jan 3, 2016 at 16:46
  • $\begingroup$ i really like the style of terence tao, i read his analysis I, i'll do analysis II later (it seems he talks a bit about some point set topology) but it seems he gave a course on point set topology, but i can't seem to find his notes, ...; anyway when i get enough rep. i'll give you a bounty thanks! :DDD $\endgroup$
    – user153330
    Commented Jan 3, 2016 at 16:50

Your question calls for a textbook. Until you find one, you might try to connect this definition to what you may know about continuous functions of a real variable. Suppose $\tau$ is the set of all unions of open intervals $(a,b)$. Try to write the "$\epsilon-\delta$" definition of continuity using elements of $\tau$ instead of intervals.


I would suggest first studying a good, advanced textbook on multivariable calculus, with a focus on the distance function in Euclidean space, the concept of open subsets of Euclidean space, and the multitude of $\epsilon-\delta$ proofs in multivariable calculus.

Next, I would suggest finding a good textbook on metric spaces, again focussing on the concept of open subsets in relation to $\epsilon-\delta$ proofs. I quite like this book.

With that background, you should have developed a good intuition for open sets, preparing you for the abstract definitions of Topology.

  • 1
    $\begingroup$ i perfectly understand open sets, closed sets, metric spaces, but i'm really struggling with other concepts such as that of a topology and of a topological space $\endgroup$
    – user153330
    Commented Jan 3, 2016 at 15:47

Topology is about to supply a set $X$ with the simplest possible non trivial concept of vicinity, where a point in $X$ could be close to a subset of $X$ without eventually being a member of the set. Those points are the points in the closure of a set.

Topology can alternatively be defined by the closure function.

Set theory is about which points or elements that is members of a set. In topology a structure is added: beyond the question of which points that are members now the question of which points that are in the closure of the set can be answered.

Example: $1\notin (0,1)\subset\mathbb R$ but any open set including $1$ also includes some points of this open intervall $(0,1)$: $1$ is close to $(0,1)$, or better, $1$ is in the closure of $(0,1)$. If $\mathcal O$ is an open set including $1$, then $\mathcal O \cap (0,1)\neq \emptyset$. The way the set $\mathbb R$ is defined, supplies $\mathbb R$ with it's well known topology (vincinity).

  • $\begingroup$ very interesting, thanks, but can you please give more detail to this " point in X could be close to a subset of X without eventually being a member of the set" not entirely clear to me right $\endgroup$
    – user153330
    Commented Jan 17, 2016 at 20:39

[This is just about basis of a topology.]

Recall the notion of open sets in ${ X }$ ${ = \mathbb{R} ^n }.$ We call ${ U \subseteq \mathbb{R} ^n }$ open if for every ${ p \in U }$ there is a "bulge" ${ B(p,r) }$ with ${ p \in B(p,r) }$ ${ \subseteq U }.$ An issue with generalising this to an arbitrary set ${ X }$ is the lack of any notion of "bulge". Turns out one can remedy this.

Let ${ X }$ be a set, and ${ \mathscr{F} }$ a collection of subsets of ${ X }.$

Def: Let ${ p \in X }.$ For brevity, an ${ \mathscr{F} - }$bulge of ${ p }$ is simply an element of ${ \mathscr{F} }$ containing ${ p }.$

Def: ${ \mathscr{F} }$ is a collection of proper bulges if :
i) Every ${ p \in X }$ has an ${ \mathscr{F} - }$ bulge.
ii) Say ${ A,B }$ are two ${ \mathscr{F} - }$ bulges of ${ p }.$ Then we can pick a smaller ${ \mathscr{F} -}$ bulge ${ C }$ with ${ p \in C }$ ${ \subseteq A \cap B }.$

Informally, i) says we can bulge every point, and ii) says given any two bulges of ${ p }$ we can pick a bulge of ${ p }$ "smaller than both" (in the sense "contained in both").

Now that we have a reasonable notion of bulging...

Let ${ X }$ be a set, and ${ \mathscr{F} }$ ${ \subseteq \mathscr{P}(X) }$ a collection of proper bulges.

Def: Subset ${ U \subseteq X }$ is open (in ${ \mathscr{F} }$ sense) if for every ${ p \in U }$ there is an ${ \mathscr{F} - }$bulge ${ B }$ with ${ p \in B }$ ${ \subseteq U }.$

That is, ${ U }$ is open if and only if it is some union of elements of ${ \mathscr{F} }.$

The collection of all such open sets is called a topology ${ \tau _{\mathscr{F} } }.$

Let ${ X }$ be a set.

We see any topology ${ \tau _{\mathscr{F}} }$ (where ${ \mathscr{F} }$ is a collection of proper bulges) is closed under arbitrary unions and finite intersections, and has ${ \emptyset, X }$ in it.

Conversely, if ${ S \subseteq \mathscr{P}(X) }$ is closed under arbitrary unions and finite intersections, and has ${ \emptyset, X }$ in it, then ${ S }$ is a topology (because ${ S }$ itself is a collection of proper bulges, and ${ S = \tau _{S} }$).

This gives the usual characterisation of a topology.


[In metric spaces, open, closed sets have definitions in terms of boundary points.]

Let ${ (X, d) }$ be a metric space and ${ A \subseteq X }.$
Def: A point ${ p \in X }$ is boundary point of ${ A }$ if every open ball ${ B(p, r) }$ intersects both ${ A }$ and ${ X \setminus A }.$
Def: ${ A }$ is open (in ${ X }$) if it contains none of its boundary points.
Def: ${ A }$ is closed (in ${ X }$) if it contains all of its boundary points.

Let ${ (X, d) }$ be a metric space and ${ A \subseteq X }.$
Obs: ${ A }$ is open in ${ X }$ if and only if every ${ p \in A }$ admits an open ball ${ p \in B(p,r) \subseteq A }.$
Obs: ${ A }$ is closed in ${ X }$ if and only if ${ X \setminus A }$ is open in ${ X }.$


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