If and a convex polytope satisfies , then it has at least facets. Its outward facet normals define spherical caps covering the unit sphere; the spherical cap area upper bound supplies the estimate.
Let be the number of facets of the convex polytope . Its facet description can be written
Because , each supporting closed half-space has . For any , follow the ray to its last point in . Its radius is at most one because . At least one facet is active there, giving
Thus the unit sphere is covered by the spherical caps centred at with angular radius . Since , this radius lies in and the spherical cap area upper bound applies. Subadditivity of surface area gives
Using for ,
The facet lower bound for ball approximations is exponential in the dimension.
Use the same normalized spherical cap area , constant and function as above. Put . The supplied ratio estimate gives
The middle inequality holds for every , since . Applying the upper projection bound for the spherical cap at yields
so .
Recall
At the expression in parentheses is positive, because and . It increases up to and then decreases strictly to a negative value at . Hence it crosses zero exactly once on , from positive to negative. The minimum of is again an endpoint value; and . This proves the stronger range of the spherical cap area upper bound:
Normalize the surface area of the spherical cap by writing
Two elementary descriptions of a spherical cap are useful. The spherical polar coordinates formula gives
Projecting orthogonally onto the last coordinates gives
Indeed, the upper hemisphere is the graph , whose surface area factor is on . This establishes the upper projection bound directly.
Set . The supplied ratio bound implies for . Consequently, at ,
Also,
On , the expression in parentheses is strictly decreasing; it starts positive and ends negative. Thus first increases and then decreases, so its minimum on this interval is at an endpoint. Since , both endpoint values are nonnegative. The spherical cap area upper bound follows: