[math-fun] Distance ratio question
Kevin Buzzard posted this to sci.math.research, and I am taking the liberty of reposting it here: << The following came up in an undergraduate problem-solving group: given 6 distinct points in the plane we can consider the 6-choose-2 distances between pairs of distinct points. If M is the largest of these distances, and m is the smallest, then show that M/m>=sqrt(3). In fact sqrt(3) isn't optimal, but I don't know what the optimal number is. One might ask what the answer is with n>=3 points in the plane: a compactness argument shows that there will be some r(n)>=1 such that M/m is always at least r(n) and furthermore such that r(n) is attained by some configuration of n points. . . . . . .
(I think I have an asymptotic formula for the optimal ratio as n -> oo, but so far not a proof. I'm curious if anyone else comes up with a conjectural asymptotic formula that is asymptotic to mine. Putative asymptotic formula is way, way below.) --Dan Guess: r(n) ~ sqrt(3n/2) as n -> oo. _____________________________________________________________________ "It don't mean a thing if it ain't got that certain je ne sais quoi." --Peter Schickele
Hmm, my asymptotic approximation is significantly less than yours; I get r(n) approaches sqrt(2 sqrt(3)/pi) * sqrt(n) as n approaches infty Unless my math skills have failed miserably.
On Friday 24 October 2008, Dan Asimov wrote: [ratio of maximal to minimal distance given n points in the plane]
(I think I have an asymptotic formula for the optimal ratio as n -> oo, but so far not a proof. I'm curious if anyone else comes up with a conjectural asymptotic formula that is asymptotic to mine.
Putative asymptotic formula is way, way below.)
[spoiler space preserved -- gjm]
Guess: r(n) ~ sqrt(3n/2) as n -> oo.
Naively, the best we can do is going to be something like hexagonal packing in a circle. Let's give the circle radius 1, so area pi, so our points all live in hexagons of area pi/n. In the obvious packing of hexagons with centres d apart, the area of each hexagon is sqrt(3/4) d^2, so d = sqrt(pi/n / sqrt(3/4)). On the other hand, the max distance is going to be ~ 2. So the ratio is 2 / (sqrt(pi*sqrt(3)/2) / sqrt(n)) = sqrt(n) sqrt(sqrt(3)/2pi), modulo any stupid algebraic errors I've made. -- g
On 10/24/08, Dan Asimov <dasimov@earthlink.net> wrote:
Kevin Buzzard posted this to sci.math.research, and I am taking the liberty of reposting it here:
<< The following came up in an undergraduate problem-solving group: given 6 distinct points in the plane we can consider the 6-choose-2 distances between pairs of distinct points. If M is the largest of these distances, and m is the smallest, then show that M/m>=sqrt(3).
In fact sqrt(3) isn't optimal, but I don't know what the optimal number is. One might ask what the answer is with n>=3 points in the plane: a compactness argument shows that there will be some r(n)>=1 such that M/m is always at least r(n) and furthermore such that r(n) is attained by some configuration of n points. . . .
6_C_2 = 15, which divides by 3 but not by 2. Assuming maximal symmetry in the extremum --- not always justified! --- suggests a convex hexagon with 6 sides of equal length 1, and 9 diagonals of equal length x. The Cayley-Menger determinant for a (flat) kite with sides 1,1,x,x and diagonals x,x, reduces to equation x^4 - 4x^2 +1 = 0, with solution (1 + sqrt3)/sqrt2 = 1.931852... [Intriguingly, another solution is the reciprocal of the above --- to what configuration might this correspond?] Any better offers for min(M/m) ? Fred Lunnon
The (5x5 determinant) tetrahedron volume(<edges^2>) formula Fred mentioned is at http://mathworld.wolfram.com/Tetrahedron.html. I futzed the 22 cubic terms down to V = sqrt(s23 ((s14 + s13) s24 - (s24 - s14 - s12) s34 - s14 (s23 + s14 - s13 - s12) - s12 s13) + (s34 - s24 - s13 + s12) (s13 s24 - s12 s34) - (s13 - s12) s14 (s34 - s24))/12 (Best? Mma radicand LeafCount = 64, vs FullSimplify's 75.) Isn't this the purview of optimizing compilers? Rich recently showed me an application for "addition-subtraction-multiplication chains". One could imagine exhaustively (tree?) searching for the shortest instruction sequence yielding the 22 terms. Or if we could find a good proximity metric, would Veit Elser's (http://en.wikipedia.org/wiki/Difference_map_algorithm) methods apply? --rwg (DISTINGUISHEDLY THINLY-DISGUISED)
participants (5)
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Dan Asimov -
Fred lunnon -
Gareth McCaughan -
rwg@sdf.lonestar.org -
Tom Rokicki