Julia set

In the context of complex dynamics, a topic of mathematics, the Julia set and the Fatou set are two complementary sets (Julia "laces" and Fatou "dusts") defined from a function. Informally, the Fatou set of the function consists of values with the property that all nearby values behave similarly under repeated iteration of the function, and the Julia set consists of values such that an arbitrarily small perturbation can cause drastic changes in the sequence of iterated function values.
Thus the behavior of the function on the Fatou set is "regular", while on the Julia set its behavior is "chaotic".
The Julia set of a function is commonly denoted formula_1 and the Fatou set is denoted formula_2 These sets are named after the French mathematicians Gaston Julia and Pierre Fatou whose work began the study of complex dynamics during the early 20th century.
Formal definition.
Let formula_3 be a nonconstant holomorphic function from the Riemann sphere onto itself. Such functions formula_3 are precisely the nonconstant complex rational functions, that is, formula_5 where formula_6 and formula_7 are complex polynomials. Assume that "p" and "q" have no common roots and at least one has degree larger than 1. Then there is a finite number of open sets formula_8, that are left invariant by formula_9 and are such that:
The last statement means that the termini of the sequences of iterations generated by the points of formula_13 are either precisely the same set, which is then a finite cycle, or they are finite cycles of circular or annular shaped sets that are lying concentrically. In the first case the cycle is "attracting", in the second it is "neutral".
These sets formula_13 are the Fatou domains of formula_3 and their union is the Fatou set formula_16 of formula_17 Each of the Fatou domains contains at least one critical point of formula_9 that is, a (finite) point "z" satisfying formula_19 or formula_20 if the degree of the numerator formula_21 is at least two larger than the degree of the denominator formula_22 or if formula_23 for some "c" and a rational function formula_24 satisfying this condition.
The complement of formula_16 is the Julia set formula_26 of formula_17 If all the critical points are preperiodic, that is they are not periodic but eventually land on a periodic cycle, then formula_26 is all the sphere; otherwise, formula_26 is a nowhere dense set (it is without interior points) and an uncountable set (of the same cardinality as the real numbers). Like formula_30 formula_26 is left invariant by formula_3 and on this set the iteration is repelling, meaning that formula_33 for all "w" in a neighbourhood of "z" [within formula_34]. This means that formula_35 behaves chaotically on the Julia set. Although there are points in the Julia set whose sequence of iterations is finite, there are only a countable number of such points (and they make up an infinitesimal part of the Julia set). The sequences generated by points outside this set behave chaotically, a phenomenon called "deterministic chaos".
There has been extensive research on the Fatou set and Julia set of iterated rational functions, known as rational maps. For example, it is known that the Fatou set of a rational map has either 0, 1, 2 or infinitely many components. Each component of the Fatou set of a rational map can be classified into one of four different classes.
Properties of the Julia set and Fatou set.
The Julia set and the Fatou set of "f" are both completely invariant under iterations of the holomorphic function "f":
Examples.
For formula_44 the Julia set is the unit circle and on this the iteration is given by doubling of angles (an operation that is chaotic on the points whose argument is not a rational fraction of formula_45). There are two Fatou domains: the interior and the exterior of the circle, with iteration towards 0 and ∞, respectively.
For formula_46 the Julia set is the line segment between −2 and 2. There is one Fatou domain: the points not on the line segment iterate towards ∞. (Apart from a shift and scaling of the domain, this iteration is equivalent to formula_47 on the unit interval, which is commonly used as an example of chaotic system.)
The functions f and g are of the form formula_48, where "c" is a complex number. For such an iteration the Julia set is not in general a simple curve, but is a fractal, and for some values of "c" it can take surprising shapes. See the pictures below.
For some functions "f"("z") we can say beforehand that the Julia set is a fractal and not a simple curve. This is because of the following result on the iterations of a rational function:
Theorem. Each of the Fatou domains has the same boundary, which consequently is the Julia set.
This means that each point of the Julia set is a point of accumulation for each of the Fatou domains. Therefore, if there are more than two Fatou domains, "each" point of the Julia set must have points of more than two different open sets infinitely close, and this means that the Julia set cannot be a simple curve. This phenomenon happens, for instance, when "f"("z") is the Newton iteration for solving the equation formula_49:
The image on the right shows the case "n" = 3.
Quadratic polynomials.
A very popular complex dynamical system is given by the family of complex quadratic polynomials, a special case of rational maps. Such quadratic polynomials can be expressed as 
where "c" is a complex parameter. Fix some formula_52 large enough that formula_53 (For example, if formula_54 is in the Mandelbrot set, then formula_55 so we may simply let formula_56) Then the filled Julia set for this system is the subset of the complex plane given by
where formula_58 is the "n"th iterate of formula_59 The Julia set formula_60 of this function is the boundary of formula_61
The parameter plane of quadratic polynomials – that is, the plane of possible "c" values – gives rise to the famous Mandelbrot set. Indeed, the Mandelbrot set is defined as the set of all "c" such that formula_62 is connected. For parameters outside the Mandelbrot set, the Julia set is a Cantor space: in this case it is sometimes referred to as Fatou dust.
In many cases, the Julia set of "c" looks like the Mandelbrot set in sufficiently small neighborhoods of "c". This is true, in particular, for so-called Misiurewicz parameters, i.e. parameters "c" for which the critical point is pre-periodic. For instance:
In other words, the Julia sets formula_62 are locally similar around Misiurewicz points.
Generalizations.
The definition of Julia and Fatou sets easily carries over to the case of certain maps whose image contains their domain; most notably transcendental meromorphic functions and Adam Epstein's finite-type maps.
Julia sets are also commonly defined in the study of dynamics in several complex variables.
Pseudocode.
The below pseudocode implementations hard code the functions for each fractal. Consider implementing complex number operations to allow for more dynamic and reusable code.
Pseudocode for normal Julia sets.
R = escape radius # choose R > 0 such that R**2 - R >= sqrt(cx**2 + cy**2)
for each pixel (x, y) on the screen, do: 
 zx = scaled x coordinate of pixel # (scale to be between -R and R)
 # zx represents the real part of z.
 zy = scaled y coordinate of pixel # (scale to be between -R and R)
 # zy represents the imaginary part of z.
 iteration = 0
 max_iteration = 1000
 while (zx * zx + zy * zy < R**2 AND iteration < max_iteration) 
 xtemp = zx * zx - zy * zy
 zy = 2 * zx * zy + cy 
 zx = xtemp + cx
 iteration = iteration + 1 
 
 if (iteration == max_iteration)
 return black;
 else
 return iteration;
Pseudocode for multi-Julia sets.
R = escape radius # choose R > 0 such that R**n - R >= sqrt(cx**2 + cy**2)
for each pixel (x, y) on the screen, do:
 zx = scaled x coordinate of pixel # (scale to be between -R and R)
 zy = scaled y coordinate of pixel # (scale to be between -R and R)
 iteration = 0
 max_iteration = 1000
 while (zx * zx + zy * zy < R**2 AND iteration < max_iteration) 
 xtmp = (zx * zx + zy * zy) ^ (n / 2) * cos(n * atan2(zy, zx)) + cx;
 zy = (zx * zx + zy * zy) ^ (n / 2) * sin(n * atan2(zy, zx)) + cy;
 zx = xtmp;
 iteration = iteration + 1
 if (iteration == max_iteration)
 return black;
 else
 return iteration;
The potential function and the real iteration number.
The Julia set for formula_66 is the unit circle, and on the outer Fatou domain, the "potential function" φ("z") is defined by φ("z") = log|"z"|. The equipotential lines for this function are concentric circles. As formula_67 we have
where formula_69 is the sequence of iteration generated by "z". For the more general iteration formula_64, it has been proved that if the Julia set is connected (that is, if "c" belongs to the (usual) Mandelbrot set), then there exist a biholomorphic map ψ between the outer Fatou domain and the outer of the unit circle such that formula_71. This means that the potential function on the outer Fatou domain defined by this correspondence is given by:
This formula has meaning also if the Julia set is not connected, so that we for all "c" can define the potential function on the Fatou domain containing ∞ by this formula. For a general rational function "f"("z") such that ∞ is a critical point and a fixed point, that is, such that the degree "m" of the numerator is at least two larger than the degree "n" of the denominator, we define the "potential function" on the Fatou domain containing ∞ by:
where "d" = "m" − "n" is the degree of the rational function.
If "N" is a very large number (e.g. 10100), and if "k" is the first iteration number such that formula_74, we have that
for some real number formula_76, which should be regarded as the real iteration number, and we have that:
where the last number is in the interval [0, 1).
For iteration towards a finite attracting cycle of order "r", we have that if "z*" is a point of the cycle, then formula_78 (the "r"-fold composition), and the number
is the "attraction" of the cycle. If "w" is a point very near "z*" and "w"' is "w" iterated "r" times, we have that
Therefore the number formula_81 is almost independent of "k". We define the potential function on the Fatou domain by:
If ε is a very small number and "k" is the first iteration number such that formula_83, we have that
for some real number formula_76, which should be regarded as the real iteration number, and we have that:
If the attraction is ∞, meaning that the cycle is "super-attracting", meaning again that one of the points of the cycle is a critical point, we must replace α by
where "w"' is "w" iterated "r" times and the formula for φ("z") by:
And now the real iteration number is given by:
For the colouring we must have a cyclic scale of colours (constructed mathematically, for instance) and containing "H" colours numbered from 0 to "H"−1 ("H" = 500, for instance). We multiply the real number formula_76 by a fixed real number determining the density of the colours in the picture, and take the integral part of this number modulo "H".
The definition of the potential function and our way of colouring presuppose that the cycle is attracting, that is, not neutral. If the cycle is neutral, we cannot colour the Fatou domain in a natural way. As the terminus of the iteration is a revolving movement, we can, for instance, colour by the minimum distance from the cycle left fixed by the iteration.
Field lines.
In each Fatou domain (that is not neutral) there are two systems of lines orthogonal to each other: the "equipotential lines" (for the potential function or the real iteration number) and the "field lines".
If we colour the Fatou domain according to the iteration number (and "not" the real iteration number formula_76, as defined in the previous section), the bands of iteration show the course of the equipotential lines. If the iteration is towards ∞ (as is the case with the outer Fatou domain for the usual iteration formula_92), we can easily show the course of the field lines, namely by altering the colour according as the last point in the sequence of iteration is above or below the "x"-axis (first picture), but in this case (more precisely: when the Fatou domain is super-attracting) we cannot draw the field lines coherently - at least not by the method we describe here. In this case a field line is also called an external ray.
Let "z" be a point in the attracting Fatou domain. If we iterate "z" a large number of times, the terminus of the sequence of iteration is a finite cycle "C", and the Fatou domain is (by definition) the set of points whose sequence of iteration converges towards "C". The field lines issue from the points of "C" and from the (infinite number of) points that iterate "into" a point of "C". And they end on the Julia set in points that are non-chaotic (that is, generating a finite cycle). Let "r" be the order of the cycle "C" (its number of points) and let "z*" be a point in "C". We have formula_93 (the r-fold composition), and we define the complex number α by
If the points of "C" are formula_95, α is the product of the "r" numbers formula_96. The real number 1/|α| is the "attraction" of the cycle, and our assumption that the cycle is neither neutral nor super-attracting, means that 1 < 1/|α| < ∞. The point "z*" is a fixed point for formula_97, and near this point the map formula_97 has (in connection with field lines) character of a rotation with the argument β of α (that is, formula_99).
In order to colour the Fatou domain, we have chosen a small number ε and set the sequences of iteration formula_100 to stop when formula_83, and we colour the point "z" according to the number "k" (or the real iteration number, if we prefer a smooth colouring). If we choose a direction from "z*" given by an angle θ, the field line issuing from "z*" in this direction consists of the points "z" such that the argument ψ of the number formula_102 satisfies the condition that
For if we pass an iteration band in the direction of the field lines (and away from the cycle), the iteration number "k" is increased by 1 and the number ψ is increased by β, therefore the number formula_104 is constant along the field line.
A colouring of the field lines of the Fatou domain means that we colour the spaces between pairs of field lines: we choose a number of regularly situated directions issuing from "z*", and in each of these directions we choose two directions around this direction. As it can happen that the two field lines of a pair do not end in the same point of the Julia set, our coloured field lines can ramify (endlessly) in their way towards the Julia set. We can colour on the basis of the distance to the center line of the field line, and we can mix this colouring with the usual colouring. Such pictures can be very decorative (second picture).
A coloured field line (the domain between two field lines) is divided up by the iteration bands, and such a part can be put into a one-to-one correspondence with the unit square: the one coordinate is (calculated from) the distance from one of the bounding field lines, the other is (calculated from) the distance from the inner of the bounding iteration bands (this number is the non-integral part of the real iteration number). Therefore, we can put pictures into the field lines (third picture).
Plotting the Julia set.
Methods : 
Using backwards (inverse) iteration (IIM).
 
As mentioned above, the Julia set can be found as the set of limit points of the set of pre-images of (essentially) any given point. So we can try to plot the Julia set of a given function as follows. Start with any point "z" we know to be in the Julia set, such as a repelling periodic point, and compute all pre-images of "z" under some high iterate formula_105 of "f".
Unfortunately, as the number of iterated pre-images grows exponentially, this is not feasible computationally. However, we can adjust this method, in a similar way as the "random game" method for iterated function systems. That is, in each step, we choose at random one of the inverse images of "f".
For example, for the quadratic polynomial "fc", the backwards iteration is described by
At each step, one of the two square roots is selected at random.
Note that certain parts of the Julia set are quite difficult to access with the reverse Julia algorithm. For this reason, one must modify IIM/J ( it is called MIIM/J) or use other methods to produce better images.
Using DEM/J.
As a Julia set is infinitely thin we cannot draw it effectively by backwards iteration from the pixels. It will appear fragmented because of the impracticality of examining infinitely many startpoints. Since the iteration count changes vigorously near the Julia set, a partial solution is to imply the outline of the set from the nearest color contours, but the set will tend to look muddy.
A better way to draw the Julia set in black and white is to estimate the distance of pixels (DEM) from the set and to color every pixel whose center is close to the set. The formula for the distance estimation is derived from the formula for the potential function φ("z"). When the equipotential lines for φ("z") lie close, the number formula_107 is large, and conversely, therefore the equipotential lines for the function formula_108 should lie approximately regularly. It has been proven that the value found by this formula (up to a constant factor) converges towards the true distance for z converging towards the Julia set.
We assume that "f"("z") is rational, that is, formula_109 where "p"("z") and "q"("z") are complex polynomials of degrees "m" and "n", respectively, and we have to find the derivative of the above expressions for φ("z"). And as it is only formula_69 that varies, we must calculate the derivative formula_111 of formula_69 with respect to "z". But as formula_113 (the "k"-fold composition), formula_111 is the product of the numbers formula_115, and this sequence can be calculated recursively by formula_116, starting with formula_117 ("before" the calculation of the next iteration formula_118).
For iteration towards ∞ (more precisely when "m" ≥ "n" + 2, so that ∞ is a super-attracting fixed point), we have
("d" = "m" − "n") and consequently:
For iteration towards a finite attracting cycle (that is not super-attracting) containing the point "z*" and having order "r", we have
and consequently:
For a super-attracting cycle, the formula is:
We calculate this number when the iteration stops. Note that the distance estimation is independent of the attraction of the cycle. This means that it has meaning for transcendental functions of "degree infinity" (e.g. sin("z") and tan("z")).
Besides drawing of the boundary, the distance function can be introduced as a 3rd dimension to create a solid fractal landscape.