Today, 02 September 2015, we worked out the Coulomb energy for the 4-point configuration U_T=(u_T_1, u_T_2, u_T_3, u_T_4) in S^2 defined by the vertices of the regular tetrahedron (say u_T_1=(0, 0, 1) and the other u_T_i=(*, *, -1/3), all with |u_i-u_j|^2=2(1-u_i•u_j)=8/3). And we began proving that U_T minimizes the f-energy E_f(U)=\Sum_{i R (the Coulomb energy with f(t) = 1/√t is a special case). More generally (we'll see 09 September) the same holds for the regular (k-1)-simplex in S^{k-2}. PROJECT 1. Compare the Coulomb energy (or the general E_f) for U_T and for the U_4 consisting of 4 equally spaced points around the equator on S^2. If we go down a dimension to the circle S^1, it turns out that k equally spaced points is also a minimizer, for any k (of course k=3 is a special case of the above, the points at the vertices of the regular 2-simplex, a.k.a. equilateral triangle); although the corresponding equatorial configuration on S^2 is not a minimizer for k>3, show it is critical (in a sense we'll make precise soon). Can you prove the 6-point configuration defined by the vertices of the octahedron, or the 12-point configuration defined by the vertices of the icosahedron, are also E_f minimizers (also try comparing their energies, say for Coulomb, with the energy of 6 or 12 equally spaced points around an equator)? Cohn and Kumar prove this for any f that is "completely monotonic" which is stronger than non-negative, decreasing, and convex - how much about f do you need to assume? Can you at least show these (and the 20-point configuration defined by dodecahedron vertices) are critical? It is unknown whether there are any other "universal minimizers" on S^2 for k other than 4, 6 or 12. * * * I expect to have explained (by 09 September) what it means for U to be a critical configuration, but its physical interpretation is that the net force on each point exerted by the other points of U must be normal to the sphere - in other words, the tangential gradient (which we'll also explain 09 September) of E_f vanishes at U. * * * Here's an excerpt from the Cohn & Kumar paper with some implicit calculus exercises you should try to check too: Recall that a C^∞ [∞'ly differentiable or "smooth"] function f: I → R on an interval I is "completely monotonic" if (−1)^k f^(k)(x) ≥ 0 for all x ∈ I and all k ≥ 0 (see [Wid, p. 145]) and "strictly completely monotonic" if strict inequality always holds in the interior of I. Of course, derivatives at endpoints of intervals denote one-sided derivatives. In this paper, endpoints are irrelevant, because we use half-open intervals closed on the right, and one can show using the mean value theorem that complete monotonicity on the interior implies that it holds also at the right endpoint. If a completely monotonic function fails to be strictly completely monotonic, then it must be a polynomial: if f^(k)(x) = 0, then complete monotonicity implies that f^(k)(y) = 0 for all y > x, in which case f^(k) is identically zero because it is analytic (Theorem 3a in [Wid, p. 146]). All inverse power laws f(r) = 1/r^p with p > 0 are strictly completely monotonic on (0,∞), and they are the most important cases for our purposes. Other examples include f(r) = e^{−cr} with c > 0. It might seem preferable to use completely monotonic functions of distance, rather than squared distance, but squared distance is in fact more natural than it first appears. It simplifies formulas appearing in later sections of this paper, it fits into the general framework described in Section 8, and it is more general than using distance: it is not hard to prove that if r → f(r^2) is completely monotonic on a subinterval (a,b) of (0,∞), then f is completely monotonic on (a^2,b^2), but not vice versa. [Wid] D. V. Widder, The Laplace Transform, Princeton University Press, Princeton, New Jersey, 1941. MR0005923 (3:232d)