Of course, when you try to generalize your theorems you are also interested in the cases where generalization fails. In this case, there is something that happens in a 2-dimensional space, in a 6-, 14- or 30-dimensional space. Mathematicians would say "it happens in 2, 6, 14 or 30 dimensions". I never noticed that this is jargon specific to mathematicians.
Problems in geometry tend to get (at least) exponentially harder to solve computationally as the dimensions grow, e.g. the number of vertices of the n-dimensional cube is literally the exponential of base 2. Which is why they discovered something about 126-dimensional space now, when the results for lower dimensions have been known for decades.
>> but "dimensions 8 and 24" to me sounds...
Note that the article says
> In dimensions 8 and 24, it’s possible to...
you didn't quote the "In". With the "In" it's usual math jargon that means
> "in dimension 4" to mean "when the dimension is equal to 4"
But the title has no "In" and it sounds very weird, perhaps even incorrect. Anyway, note that most of the times the title is not written by the author.
There is an old joke:
How do you imagine a 126-dimensional space? - Simple: imagine an n-dimensional space and set n=126.
The Kervaire invariant is a property of an "n-dimensional manifold", so the paper is likely about 126-dimensional manifolds. That in turn has a formal definition, and although it's not my specialization, I think means it can be locally represented as an n-dimensional Euclidean space.
A simple example would be a circle, which I guess would be a 1-dimensional manifold, because every point on a circle has a tangent where the circle can be approximated by a line passing through the same point.
So they're saying that there are these surfaces which can be locally approximated by 126-dimensional Euclidean spaces. This in turn probably requires that the surface itself is embedded in some higher-dimensional space such as R^127.
> Every smooth n-dimensional manifold can be embedded into R^{2n}.