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Given three points in the plane, the distances between them have to be non-negative and obey the triangle inequalities

but are otherwise unconstrained. But if one has *four* points in the plane, then there is an additional constraint connecting the six distances between them, coming from the Cayley-Menger determinant:

Proposition 1 (Cayley-Menger determinant)If are four points in the plane, then the Cayley-Menger determinant

*Proof:* If we view as vectors in , then we have the usual cosine rule , and similarly for all the other distances. The matrix appearing in (1) can then be written as , where is the matrix

and is the (augmented) Gram matrix

The matrix is a rank one matrix, and so is also. The Gram matrix factorises as , where is the matrix with rows , and thus has rank at most . Therefore the matrix in (1) has rank at most , and hence has determinant zero as claimed.

For instance, if we know that and , then in order for to be coplanar, the remaining distance has to obey the equation

After some calculation the left-hand side simplifies to , so the non-negative quantity is constrained to equal either or . The former happens when form a unit right-angled triangle with right angle at and ; the latter happens when form the vertices of a unit square traversed in that order. Any other value for is not compatible with the hypothesis for lying on a plane; hence the Cayley-Menger determinant can be used as a test for planarity.

Now suppose that we have four points on a sphere of radius , with six distances now measured as lengths of arcs on the sphere. There is a spherical analogue of the Cayley-Menger determinant:

Proposition 2 (Spherical Cayley-Menger determinant)If are four points on a sphere of radius in , then the spherical Cayley-Menger determinant

*Proof:* We can assume that the sphere is centred at the origin of , and view as vectors in of magnitude . The angle subtended by from the origin is , so by the cosine rule we have

Similarly for all the other inner products. Thus the matrix in (2) can be written as , where is the Gram matrix

We can factor where is the matrix with rows . Thus has rank at most and thus the determinant vanishes as required.

Just as the Cayley-Menger determinant can be used to test for coplanarity, the spherical Cayley-Menger determinant can be used to test for lying on a sphere of radius . For instance, if we know that lie on and are all equal to , then the above proposition gives

The left-hand side evaluates to ; as lies between and , the only choices for this distance are then and . The former happens for instance when lies on the north pole , are points on the equator with longitudes differing by 90 degrees, and is also equal to the north pole; the latter occurs when is instead placed on the south pole.

The Cayley-Menger and spherical Cayley-Menger determinants look slightly different from each other, but one can transform the latter into something resembling the former by row and column operations. Indeed, the determinant (2) can be rewritten as

and by further row and column operations, this determinant vanishes if and only if the determinant

vanishes, where . In the limit (so that the curvature of the sphere tends to zero), tends to , and by Taylor expansion tends to ; similarly for the other distances. Now we see that the planar Cayley-Menger determinant emerges as the limit of (3) as , as would be expected from the intuition that a plane is essentially a sphere of infinite radius.

In principle, one can now estimate the radius of the Earth (assuming that it is either a sphere or a flat plane ) if one is given the six distances between four points on the Earth. Of course, if one wishes to do so, one should have rather far apart from each other, since otherwise it would be difficult to for instance distinguish the round Earth from a flat one. As an experiment, and just for fun, I wanted to see how accurate this would be with some real world data. I decided to take , , , be the cities of London, Los Angeles, Tokyo, and Dubai respectively. As an initial test, I used distances from this online flight calculator, measured in kilometers:

Given that the true radius of the earth was about kilometers, I chose the change of variables (so that corresponds to the round Earth model with the commonly accepted value for the Earth’s radius, and corresponds to the flat Earth), and obtained the following plot for (3):

In particular, the determinant does indeed come very close to vanishing when , which is unsurprising since, as explained on the web site, the online flight calculator uses a model in which the Earth is an ellipsoid of radii close to km. There is another radius that would also be compatible with this data at (corresponding to an Earth of radius about km), but presumably one could rule out this as a spurious coincidence by experimenting with other quadruples of cities than the ones I selected. On the other hand, these distances are highly incompatible with the flat Earth model ; one could also see this with a piece of paper and a ruler by trying to lay down four points on the paper with (an appropriately rescaled) version of the above distances (e.g., with , , etc.).

If instead one goes to the flight time calculator and uses flight travel times instead of distances, one now gets the following data (measured in hours):

Assuming that planes travel at about kilometers per hour, the true radius of the Earth should be about of flight time. If one then uses the normalisation , one obtains the following plot:

Not too surprisingly, this is basically a rescaled version of the previous plot, with vanishing near and at . (The website for the flight calculator does say it calculates short and long haul flight times slightly differently, which may be the cause of the slight discrepancies between this figure and the previous one.)

Of course, these two data sets are “cheating” since they come from a model which already presupposes what the radius of the Earth is. But one can input real world flight times between these four cities instead of the above idealised data. Here one runs into the issue that the flight time from to is not necessarily the same as that from to due to such factors as windspeed. For instance, I looked up the online flight time from Tokyo to Dubai to be 11 hours and 10 minutes, whereas the online flight time from Dubai to Tokyo was 9 hours and 50 minutes. The simplest thing to do here is take an arithmetic mean of the two times as a preliminary estimate for the flight time without windspeed factors, thus for instance the Tokyo-Dubai flight time would now be 10 hours and 30 minutes, and more generally

This data is not too far off from the online calculator data, but it does distort the graph slightly (taking as before):

Now one gets estimates for the radius of the Earth that are off by about a factor of from the truth, although the round Earth model still is twice as accurate as the flat Earth model .

Given that windspeed should additively affect flight velocity rather than flight time, and the two are inversely proportional to each other, it is more natural to take a harmonic mean rather than an arithmetic mean. This gives the slightly different values

but one still gets essentially the same plot:

So the inaccuracies are presumably coming from some other source. (Note for instance that the true flight time from Tokyo to Dubai is about greater than the calculator predicts, while the flight time from LA to Dubai is about less; these sorts of errors seem to pile up in this calculation.) Nevertheless, it does seem that flight time data is (barely) enough to establish the roundness of the Earth and obtain a somewhat ballpark estimate for its radius. (I assume that the fit would be better if one could include some Southern Hemisphere cities such as Sydney or Santiago, but I was not able to find a good quadruple of widely spaced cities on both hemispheres for which there were direct flights between all six pairs.)

This will be a more frivolous post than usual, in part due to the holiday season.

I recently happened across the following video, which exploits a simple rhetorical trick that I had not seen before:

If nothing else, it’s a convincing (albeit unsubtle) demonstration that the English language is non-commutative (or perhaps non-associative); a linguistic analogue of the swindle, if you will.

Of course, the trick relies heavily on sentence fragments that negate or compare; I wonder if it is possible to achieve a comparable effect without using such fragments.

A related trick which I have seen (though I cannot recall any explicit examples right now; perhaps some readers know of some?) is to set up the verses of a song so that the last verse is identical to the first, but now has a completely distinct meaning (e.g. an ironic interpretation rather than a literal one) due to the context of the preceding verses. The ultimate challenge would be to set up a Möbius song, in which each iteration of the song completely reverses the meaning of the next iterate (cf. this xkcd strip), but this may be beyond the capability of the English language.

On a related note: when I was a graduate student in Princeton, I recall John Conway (and another author whose name I forget) producing another light-hearted demonstration that the English language was highly non-commutative, by showing that if one takes the free group with 26 generators and quotients out by all relations given by anagrams (e.g. ) then the resulting group was commutative. Unfortunately I was not able to locate this recreational mathematics paper of Conway (which also treated the French language, if I recall correctly); perhaps one of the readers knows of it?

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