The square root spiral and the Gamma function: entwined analogies

The topic discussed here is something on which considerable serious mathematical literature has published by P.J Davis, W. Gautschi and others. This partly historical narration is just a personal account of our journey through the same as a non-mathematician. As for the detour on the Gamma function its allure has been so much that everyone from the ordinary college lecturer to the Fields medalist Manjul Bhargava has written something about it. Its invisible hand is felt in science especially in the form of various statistical distributions that show up in as disparate phenomena as the distribution of the number of molecules of widely expressed proteins or the distribution of positions in a protein’s sequence evolving at different rates. Thus, we could not pass up the opportunity for a little mention of it.

The story begins with a problem which one might have encountered in the context of elementary geometric puzzles that one is asked to solve as a youth: If you have a circle of radius R then how do you dissect it into n concentric circular rings of equal area using just a compass and straight edge? Of course the first “ring” would be disc rather than a ring. It is achieved by means of the below construction (Figure 1):

circle_dissectionFigure 1

1) Let point A be the center of the circle of radius R which we seek to dissect into n rings.
2) Construct a unit of length of r=\tfrac{R}{\sqrt{n}}.
3) Draw \overline{AB}=r. Then draw a segment of the same unit length r perpendicular to \overline{AB} at point B. Join A to the free end B1 of this new segment.
4) Draw a further segment of length r perpendicular to \overline{AB1} and join its free end to A.
5) Repeat this procedure n times; n=17 in figure 1. Draw circles with A as center with each of the segments beginning with A as their respective radii. This completes the required dissection.

One can see from the figure that the construction results in a sequence of side-sharing right triangles whose hypotenuses increase successively as the square roots of the natural numbers. Their legs of unit length trace out a spiral path. Hence, this figure might be termed the square root spiral (SRS). One may also see that as the number of dissections n\rightarrow \infty we are left with thinner and thinner rings that are essentially the circumference of the circle: \tfrac{\text{d}A}{\text{d}r}=2\pi r.

In the above construction we used n=17 because adding one more unit results in the spiral going past the first turn (Figure 2). Thus, 17 is the whole number in turn 1; 54 in turn 2; 110 in turn 3. Now, based on this number 17 it has been claimed on flimsy evidence that this figure might have been constructed by Plato’s teacher Theodorus in Greek antiquity. Plato, with his characteristic eye for interesting mathematics, records the following conversation (at ~360 BCE) between Socrates and his friend the mathematician Theaetetus who laid the foundations of some key aspects of Greek mathematics. Here Theaetetus is telling Socrates regarding his study of square roots with another mathematician Theodorus (Theaetetus, Jowett translation):

Theaet.: Theodorus was writing out for us something about roots, such as the roots of three or five, showing that they are incommensurable by the unit: he selected other examples up to seventeen — there he stopped. Now as there are innumerable roots, the notion occurred to us of attempting to include them all under one name or class.
Soc.: And did you find such a class?
Theaet.: I think that we did; but I should like to have your opinion.
Soc.: Let me hear.
Theaet.: We divided all numbers into two classes: those which are made up of equal factors multiplying into one another, which we compared to square figures and called square or equilateral numbers — that was one class.
Soc.: Very good.
Theaet.: The intermediate numbers, such as three and five, and every other number which is made up of unequal factors, either of a greater multiplied by a less, or of a less multiplied by a greater, and when regarded as a figure, is contained in unequal sides;-all these we compared to oblong figures, and called them oblong numbers.
Soc.: Capital;…

It is clear from what Theaetetus tells Socrates that they were talking about dividing all natural numbers into perfect squares like 1, 4, 9, 16, … which yield a root which is measurable as units and all other numbers in between which do not. These Theaetetus considered oblong numbers for they needed unequal factors to constitute them. The question is when Theodorus wrote out those numbers to illustrate the non-perfect squares why did he stop at 17? It has been speculated that in establishing their being “incommensurable by the unit” Theodorus had made use of a construction as in figure 1 and he stopped at 17 because he had reached maximum number of natural numbers that can be accommodated in a single turn of the spiral. Of course there is no evidence that this was the real reason for his choice of 17 (17 had some importance in Indo-European tradition so there could be other reasons).

squareroot_spiralFigure 2

Interestingly, while we drew out this figure of the SRS for ourselves as part of the geometric constructions we indulged in in our youth, it has sparked much mathematical activity only in the last 3 decades. As is clear from figure 2 this spiral is a discrete spiral in that the radius increases in jumps of the square roots of the natural numbers. The mathematician Davis (also a historian of Euler’s and Gauss’ studies on special functions) asked an interesting question: Can one find a smooth, analytic curve that describes the square root spiral and interpolates all the intermediate values between the discrete square root radii of the discrete spiral? Davis the solved this question rather remarkably following the footsteps of Leonhard Euler.

Before we get to that we shall first create a further generalization of the discrete SRS: After having constructed the initial discrete SRS as described above, reflect (invert) the point B which initiates the spiral on the \sqrt{2} hypotenuse to get a new point. Then reflect the outer end of the \sqrt{2} hypotenuse on the \sqrt{3} hypotenuse; then reflect the outer end of the \sqrt{3} hypotenuse on the 2 hypotenuse, so on. This yields the second branch of the discrete SRS (in red in figure 2). So the Davis problem in its more general form requires one to interpolate a smooth curve through both the branches of of the discrete SRS.

The approach taken by Davis to solve it along with the solution has some striking parallels the story one of the great problems in the history of modern mathematics (described by Davis himself). Hence, we shall take detour to look a bit at that famous problem. The factorial function was originally discovered by Hindu mathematicians. For instance, it is clearly provided by the Kashmirian polymath finance minister of the Seuna Yādava rulers Śārṅgadeva in his work on the theory of Hindu music the Saṃgīta-Ratnākara in 1225 CE. This original form of the factorial function is organically described as the serial product of natural numbers: n!=1\times 2\times...(n-1)\times n. In the first half of the 1700s it was noticed that these discrete points of the factorial function seemed to define a curve. But the question was how does one find the intermediate points of the curve like say 2.5!. The interest in this type of interpolation problem was likely initiated by Newton in England and passed on to his junior associate, the Frenchman de Moivre. In course of his study of probability de Moivre discovered the first continuous function that was an approximate fit to the discrete factorials:
n! \sim k\cdot \sqrt{n}\left(\dfrac{n}{e}\right)^n; where k is a constant.
His junior associate Stirling after some experimentation refined the value of the constant as k=\sqrt{2\pi} leading to many people wrongly attributing the formula to him instead of de Moivre.

In this context we might note that Srinivasa Ramanujan discovered another close approximation for the factorial function:
y= \dfrac{\log(\pi)}{2}-n+n\log(n)+\dfrac{\log(n(1+4n(1+2n)))}{6}; \; n! \approx e^y

This formula of de Moivre indicated how the curve fitting the discrete factorials should approximately look at intermediate values. However, the precise fitting function was a problem baffled all attempts made by Stirling, Daniel Bernoulli and Goldbach. Finally, in 1729 CE Goldbach brought the problem to the 22 year old Leonhard Euler’s attention in his letter from Moscow to the latter at St. Petersburg. Euler, giving a taste of his unrivaled greatness, solved the problem in his letters responding to Goldbach the same year and the next year published a detailed paper on his use of “higher” calculus to solve the problem. Answer to the general interpolation problem was the Gamma function \Gamma(x); In modern notation n!=\Gamma(n+1) and the values of the function at intermediate positions provides the smooth interpolation between the discrete factorial values.

One of Euler’s definitions of \Gamma(x) was the Eulerian integral:
\Gamma(x)=\displaystyle \int_0^\infty e^{-t}t^{x-1} dt

While there is no general way of solving this integral one can see the following:
If x=1, \Gamma(1)=\displaystyle \int_0^\infty e^{-t}dt=-e^{-t} \Bigr |_0^\infty=0-(-1)=1

Now, if we make the substitution x\rightarrow x+1 then we get:
\Gamma(x+1)=\displaystyle \int_0^\infty e^{-t}t^{x} dt; on which we use integration by parts,
\int u dv = u\cdot v - \int v du ,
thus for the above we have:
\displaystyle -\int_0^\infty e^{-t}t^{x} dt=e^{-t}t^{x}\Bigr |_0^\infty- \int_0^\infty e^{-t}xt^{x-1} dt=-e^{-t}t^{x}\Bigr |_0^\infty+x \int_0^\infty e^{-t}t^{x-1}dt =\lim_{t \to \infty} -\dfrac{t^x}{e^t}-0^x\cdot e^{-0}+ x\Gamma(x)
Since, in the above expression the exponential function in the denominator will always catch with the power function in the numerator that limit will be 0. Thus we get,

One will notice right away that this captures the discrete factorial function when x is a natural number. Further, all we need to do is to somehow obtain the values for \Gamma(x) from 0:1 then we can use the above relationship to extend it for other positive intervals. Thus, Euler’s \Gamma(x) provides a function to extrapolate the factorial for the intermediate values but the question remains as the how do we get the values from 0:1. One of those values x=\tfrac{1}{2} can be obtained using relatively straightforward means from the Eulerian integral:
\Gamma(\tfrac{1}{2})= \displaystyle \int_0^\infty \dfrac{e^{-t}}{\sqrt{t}}dt
We resort to the substitution t=u^2 \; \therefore dt=2u du
\therefore \Gamma(\tfrac{1}{2})= \displaystyle 2 \int_0^\infty e^{-u^2} du
Remarkably, the core of above integral is the one specifying half the area under a Gaussian Bell curve; so it evaluates to \tfrac{\sqrt{\pi}}{2}
\therefore \Gamma(\tfrac{1}{2})=2 \dfrac{\sqrt{\pi}}{2}=\sqrt{\pi}
This is one of those deep results that when you see and imbibe for the first time it produces a profound effect on you — how the problem of generalizing the factorial function leads you to the squaring of the circle and the limit from the famed central limit theorem i.e. the normal distribution. Thus, in the least we can get \Gamma(1.5), \Gamma(2.5) etc trivially using the above recurrence relationship.

However, Euler himself obtained \Gamma(\tfrac{1}{2}) by using a product formula. It was such product formulae and other series which Euler, Gauss and their successors used to provide the other values of \Gamma(x). Gauss with his student, the astronomer Friedrich Nicolai, who was a calculating prodigy, prepared tables of the \Gamma(x) which served the mathematical community throughout the 1800s. In his investigations on \Gamma(x) Gauss, building on Euler’s product formula developed the famous product formula:
\Gamma(x)=\displaystyle \lim_{n \to \infty} \dfrac{n^x n!}{x(x+1)...(x+n)}
This formula is quite slow in converging and rakes up huge numbers in the calculation: e.g. with n=100 we get \Gamma(0.1) \approx 9.51 correct to 2 places after the decimal point when rounded.

It is this kind of product formulae that bring us back to our original question of interpolation of the square root spiral. Armed with his deep knowledge of the history of the methods of Euler and Gauss in attacking the Gamma function, Davis solved the SRS problem by producing a product formula, which for a given number \alpha, which corresponds to the natural numbers 0,1,2,3… or any value between them, produces the exact coordinates of the SRS in the complex plane. This remarkable formula is:

T(\alpha)=\displaystyle \prod_{k=1}^{\infty} \dfrac{1+\dfrac{i}{\sqrt{k}}}{1+\dfrac{i}{\sqrt{k+\alpha-1}}}, where i=\sqrt{-1}, \alpha \ge 0
Here |T(\alpha)|=\sqrt{\alpha} This captures the basic square root radius or hypotenuse seen in the discrete SRS.

Strikingly, analogous to the Gamma function the SRS equation also has a recurrence formula:
From these relationships we get:
|T(\alpha+1)-T(\alpha)|=|T(\alpha)+\dfrac{iT(\alpha)}{\sqrt{\alpha}}-T(\alpha)|=|i|\dfrac{\sqrt{\alpha}}{\sqrt{\alpha}}=-i\cdot i=1
This captures the basic relationship of the successive natural numbers in the discrete SRS. Like with \Gamma(x) all we need to do is to calculate the values of T(\alpha) from 0:1. Then using the recurrence relationship we can extend it for all other values.

Like the Gauss product formula for \Gamma(x) the T(\alpha) formula is also slow converging. To get reasonable accuracy we need to calculate at least 20000 terms of the above product. E.g. with this computation we get T(2)=1.414213562373095. Thankfully, this can be done quite fast with even your modern laptop and thus we get the continuous SRS in figure 3.

Sqrt_spiralFigure 3

With this in place we can look at a few other things. For example, if one plots the positions of the perfect squares (those which Theaetetus mentions to Socrates) on the SRS we surprisingly find them to lie on a triradiate pattern of gently curving spirals radiating from the number 1. The three arms have respectively:

\alpha=4, 25, 64, 121...\rightarrow 9k^2+12k+4
\alpha=9, 36, 81, 144... \rightarrow 9k^2+18k+9
\alpha=16, 49, 100, 169... \rightarrow 9k^2+24k+16 where k=0,1,2,3...

The next question is how does one capture the second branch of the SRS which was obtained in its discrete form via reflection on the subsequent hypotenuse. For this Davis figured out that one could use a generalized reflection formulation which gives S(\alpha) i.e. the position in the complex plane for the second branch:
Thus once we have T(\alpha) we can now use this reflection formula to get the points on second branch. The thus computed complete continuous SRS is shown in Figure 4.

Sqrt_spiral_2Figure 4

Here again one can see a parallel to the \Gamma(x): How does one gets its values for negative x. This brings out a remarkable connection between the \Gamma(x) and the trigonometric functions in analogous reflection formula:

\Gamma(-x)=-\dfrac{\pi}{\sin(\pi x)x\Gamma(x)}

Thus, once we know the \Gamma(x) for positive values we can get the negative ones by this reflection formula. Unlike the positive x for which grows explosively we see oscillations in negative x arising from the trigonometric connection.

Davis then investigated the slope of tangent to the SRS at the point where it cuts the x-axis for the first time after the origin, i.e. the derivative of T(\alpha) at 1, T'(1). Gautschi termed this number \theta in the honor of Theodorus and it is given by the simple but interesting series:
\theta=\displaystyle \sum_{k=1}^{\infty}\dfrac{1}{k^{3/2}+\sqrt{k}}

This is an awfully slow converging series: by computing the above sum for 1000000 terms we obtain rounded off to two places after decimal point \theta=1.86, which is correct for those two places. There are complicated, faster-converging methods which have been published in computer science studies. One such discovered by Phillips involves getting the sum \theta_{n-1} as above till k=n-1 where n is relatively small and then adding a monstrous remainder term derived from the Euler summation formula:


Plugging n=15 we now effortlessly get \theta= 1.8600250790563 which is correct to 9 decimal places after the point.

Again there is a parallel to the \Gamma(x). Euler discovered that the slope of the tangent to \Gamma(x) at x=1 is \Gamma'(1)=-\gamma. This \gamma is the famous Euler’s constant and is similarly given by an infinite sum:

\gamma =\displaystyle \sum_{k=1}^\infty \dfrac{1}{k}-\log\left(1+\dfrac{1}{k}\right)

This sum converges more quickly: with 100 terms we get rounded of to 4 places \gamma=0.5772 which is correct for that many places after the decimal point. This \gamma is an important constant in science coming up a lot not just in the calculation of \Gamma(x) but also the famed zeta function and various statistical distributions. Euler with his prodigious mental computational abilities attacked it several times in his life computing it to 16 decimal places before his death. Later the Mascheroni computed it to more places. Gauss himself capable of extraordinary numeration found that Mascheroni had made a mistake in the 21st place and asked his student, the astronomer Nicolai, who was a human computer of his age to to verify his result. Nicolai obtained the value correct to 40 decimal places, a record which stood for 50 years. Ramanujan discovered some really dramatic looking formulae relating to \gamma, including those with fast convergence; however we shall not talk about them here.

Sqrt_spiral_pispacingFigure 5

In figure 5 we see that each successive turn of the SRS is greater than the previous one by a value of nearly \pi. The SRS turn separation indeed converges towards \pi asymptotically. This leads to the question of whether there is a way to calculate the number of discrete radii that lie within each turn of the SRS. For this Hlawka calculated something called Schneckenkonstante K = -2.157782 based on which Kochiemba/Wilson have computed the sequence of the number of discrete radii ( nr[n]; OEIS: A072895) contained within the turn n of the SRS thus:
nr[n]=\text{trunc}\left(\left(n\pi -\dfrac{K}{2}\right)^2 - \dfrac{1}{6}\right)
This yields the sequence: 0, 17, 54, 110, 186, 281, 396, 532, 686, 861, 1055… as the number of discrete radii per turn. The difference between the square roots of successive terms of this sequence (Figure 6) fluctuates around \pi with the fluctuations decreasing in amplitude as the number of turns increase. The value can come quite close to \pi. For the first 100 turns \sqrt{nr[85]}-\sqrt{nr[84]}=\sqrt{70210}-\sqrt{68555}=3.1415990193488, which comes within 6.366 \times 10^{-6} of \pi.

Sqrt_spiral_pi_convergenceFigure 6

Finally, coming back to where we started, there is a simple a map in the complex plane discovered by Davis that produces discrete points of all manner of spirals including the SRS:
Here a and b are constants or vary with each iteration. When a=1;\; b=i; \; z_0=1 we get the discrete points on the SRS (Figure 7). When |a| \ne 1;\; Im(a) \ne 0; \; b=0 we get discrete points on the logarithmic spiral discovered by Rene Descartes. When |a|=1; \; a \ne 1,-1; \; b=k\cdot a; k>0 we get an Archimedean spiral. When a=\cos\left(\tfrac{\pi}{4}\right)+i\sin\left(\tfrac{\pi}{4}\right); b=\overline{a}, z_0=1 we get something that grows like the SRS but has a more complex wave like internal pattern (Figure 7). This is reminiscent of the convergences seen in the Henon map, only that these are divergences. When a=1.1+.3i; \; b=-a; \; z_0=1.1 the map shows chaotic behavior but the attractor is localized to 4 concentric circular shells (Figure 7). Finally, when a=\cos\left(\tfrac{\pi}{4}\right)+i\sin\left(\tfrac{\pi}{4}\right) and b varies with each iteration n as b=\sin(n)+\sin\left(\tfrac{n}{5}\right); \; z_0=1 we get a complex braided spiral arrangement of the points (Figure 7).

Sqrt_Spiral_cmplex_mapFigure 7

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