# How can you describe topology to a non-mathematician without using continuous deformations?

One of the most frequently used ways to describe topology to non-mathematicians is that it studies the properties of objects that are preserved under deformations where ripping or tearing is not allowed.

I like this definition, but I've realized recently that it gives the wrong idea. In fact, this describes isotopy instead of homeomorphism.

Does it matter? Take an annulus, cut it into a strip of paper. Twist it once and glue, then you get a Möbius strip. Twist is twice and glue, what you get is another annulus.

But there is no way to deform a standard annulus into a doubly twisted annulus. So the intuition is very wrong here.

In addition topology is much bigger than manifolds and isotopies anyways. So my question is:

What is an effective way to describe topology that will give an intuitive understanding of continuity, connectedness, and compactness, without using the idea of smooth deformations?

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I've usually tried using "closeness" as a starting point. After all, topology education often begins with points of closure. If you plan on using a metric topology as an example, then you will have the intuition of a metric at your disposal for this.

That also sets you up for a good approximation for what continuity does: continuous functions preserve closeness (since they are preserving points of closure.) You can probably also riff off of that onto (path) connectedness, since a path is sort of like a string of points shoulder to shoulder.

Getting open sets across is a fun challenge. I've always found the picture of them being sets with "fuzzy edges" helpful. (It works best for metric spaces, but I suppose the picture is not universally applicable.) "Near" is a fuzzy notion after all, right? So if you are a point and you are "near" to another set by all measures of nearness that you have (these measures are open sets) then you are a point of closure to the set, and that makes you as close as possible.

I guess that means that you can try to convey closed set as having sharp, or well-defined edges. That helps a bit more with general connectedness, because "splitting" a space into two pieces with sharp edges makes it seem like the cut is a clean one. Clopen sets do not really play well into the fuzzy-sharp picture though :(

Compactness will probably always be a challenge. You can always try to motivate them as generalizations of finite sets. I know this can be problematic, though, since not only does it depend on the points of the space, it depends on how rich the topology is. After all, the antidiscrete topology on any space makes it compact, no matter how big the space is. I guess to get across this gap, you'd might fix a set and talk about different topologies on it. Specifically, you might use $\Bbb R$ with the order topology and then with the discrete topology. This gives you an opportunity to show what differences choice in open sets makes in the topology of a space.

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It's kind of uncanny that a friend who's majoring in biology asked me this question just now.

For me, I think it's best to start with the concept of basis for a topology on a set $X$.

A basis is best described as building blocks of a space.

I think it's kind of difficult to describe a continuous function for a general topological space to a non-mathematician. However, maybe a subset of it, metric spaces, we can describe continuous functions as maps that preserves distances between points.

For connectedness, we can describe it as a property of a space that cannot be split into any two building blocks or unions of building blocks. (The concept of only the empty set and the whole space being clopen)

For compactness, I think it's best described as being able to find finitely many building blocks that can eclipse the space. But then again, the definition of finite may differ across non-mathematicians. Or maybe you can try asking the questions: "What do you think being compact is? What's the dictionary definition of compact?" Maybe all these will stir some form of intuition.

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