I have just started with a course on convex optimization and have been introduced to the concept of the interior of a set. I have a fairly basic question. I am still trying to understand this topic, so please forgive me if this is a stupid or incorrect question.
Why is not the definition of the interior of a set not tied to the dimension of the space it is lying in?
For e.g. Consider a square in $\mathbb{R}^2$ i.e. $\mathcal{S} = \{(x,y)|x\in[-1,1],y\in[-1,1]\}$. By definition, points inside the square are interior points, because all points within an open '${disc}$' of radius $\epsilon>0$, around the point under consideration, lie inside the set.
But in 3 dimensions, this 2D figure has $\varnothing$ interior, since all points inside an open '$ball$' around any of the points inside $\mathcal{S}$, do not belong to $\mathcal{S}$
So, shouldn't the definition of the interior of a set be tied to the dimension of the space from which we are looking at the set? Else, how does one know whether to use a disc or a ball to find the interior of a set.
Thanks in advance!
You're correct; the context in which interiors are taken matters.
It is a mathematical meteprinciple that the way to formalize "widening of context" is by leveraging the concept of an embedding. Nobody has (so far) proposed a definition of embedding that works in all cases, but the correct definition for metric spaces is surely that of an isometry, sometimes called an isometric embedding. (Note: isometries are always injective; however, contrary to what you might expect from the prefix iso-, they needn't be invertible, nor surjective.)
The importance of context for the taking of interiors can therefore be phrased as follows. Let $X$ and $Y$ denote metric spaces, and suppose $f : X \rightarrow Y$ is an isometry (i.e. an isometric embedding, in other words a widening of context). Then given a subset $S \subseteq X$, all we can say is that $f(\mathrm{int}(S)) \supseteq \mathrm{int}(f(S)).$ In particular, the reverse inclusion needn't hold.
Here's a simple example, a slight variant on the example you give. Bind the variables $u$ and $v$ to the real number line. Take $X = \mathbb{R}^2, \,Y = \mathbb{R}^3$, and let $f : X \rightarrow Y$ denote the function specified as follows. $$f(u,v) = (u,v,0)$$
(Check that this is an isometry; i.e. a widening of context.)
Now let $S \subseteq X$ be defined as follows. $$S=\{(u,v) \in X\,|\,u∈(−1,1),v∈(−1,1)\}$$
Then:
$\mathrm{int}(S) = S,$ so $f(\mathrm{int}(S)) = \{(u,v,0) \in Y\,|\,u∈(−1,1),v∈(−1,1)\},$ which is not empty.
On the other hand, we have $f(S) = \{(u,v,0) \in Y\,|\,u∈(−1,1),v∈(−1,1)\},$ so $\mathrm{int}(f(S)) = \emptyset_Y$.
So yes, context matters. It is considerations such as these that led to the by-now dominant way of looking at mathematical structures. If we're thinking of $\mathbb{R}^2$ and $\mathbb{R}^3$ as metric spaces, then we imagine them "floating free" in the universe. We do not imagine that $\mathbb{R}^2 \subseteq \mathbb{R}^3$. Rather, there are many embeddings $f : \mathbb{R}^2 \rightarrow \mathbb{R}^3$, and each of these gives us a way of viewing $\mathbb{R}^2$ as a subspace of $\mathbb{R}^3$. But these $f$'s are not harmless; as we've just seen, widening the context actually changes things; some constructions are preserved under embeddings, but many are not.