A pure geometry problem presented itself as I wondered about the math of compressive sensing.
Consider the nD cube {(x1, … xn) | 0 < j ≤ n → 0 < xj < 1}. The subset of the cube with coordinates that sum to 1 is an n−1 dimensional regular simplex. What shape is the subset whose coordinates sum to 2? In general what of the subset P(n, k) where the coordinate sum is k < n?
It is of course still an n−1 dimensional convex polytope. P(3, 2) is another regular simplex and in general P(p+q, p) is congruent to P(p+q, q) for p, q > 0.
In general P(n, k) has C(n, k) vertices. (C(n, k) = the binomial coefficient = n!/(k!(n-k)!).) What’s P(4, 2)? The vertices are the 6 points with two 1’s as coordinates and 0’s as the other coordinates. It is clearly the regular octahedron.
P(5, 2) Miscellaneous facts
We see thus that P(5, 2) is bounded by five regular tetrahedra and five regular octahedra. I am sure it would be a lovely figure to contemplate, but it is not platonic for its faces are not congruent to each other. When two of the five coordinates are stuck at 0 the other three sum to 2 and so produce a triangle which bounds two octahedra. There are ten such triangles between octahedra. When one coordinate is stuck at 0 and another at 1, the other three sum to 1 and we have a triangle between an octahedron and a tetrahedron. There are 20 of these triangles.
Another way to see what is happening is to consider P(5, 1.1). This is nearly the 4D simplex but with its 5 vertices clipped off. The exposed small face at each clipping is a tetrahedron. We have a truncated 4 simplex. As x moves from 0 to 1, the truncation of P(5, 1+x) increases until the exposed faces meet at points such as (1, 1, 0, 0, 0). At this phase the faces of the 4D simplex, which begin as tetrahedra have also been truncated to become octahedra.
This general process can be extended recursively to yet higher dimensions but with receding possibilities of visualization.