Mandelbrot set and Julia sets of fractional order
Abstract
In this paper the fractional-order Mandelbrot and Julia sets in the sense of -th Caputo-like discrete fractional differences, for , are introduced and several properties are analytically and numerically studied. Some intriguing properties of the fractional models are revealed. Thus, for , contrary to expectations, it is not obtained the known shape of the Mandelbrot of integer order, but for . Also, we conjecture that for , the fractional-order Mandelbrot set is similar to the integer-order Mandelbrot set, while for and , one of the underlying fractional-order Julia sets is similar to the integer-order Mandelbrot set. In support of our conjecture, several extensive numerical experiments were done. To draw the Mandelbrot and Julia sets of fractional order, the numerical integral of the underlying initial values problem of fractional order is used, while to draw the sets, the escape-time algorithm adapted for the fractional-order case is used. The algorithm is presented as pseudocode.
keywords: Mandelbrot set of fractional order; Julia set of fractional order; Caputo-like discrete fractional difference
1 Introduction
The study of the dynamics of complex maps was initiated by P. Fatou and G. Julia in the early of twentieth century, before being revived by B. Mandelbrot. As know, in the complex plane , the Integer Order (IO) Mandelbrot set represents the set of complex numbers (parameters) for which the quadratic map (Mandelbrot map) does not diverge to infinity when it is iterated with from . This set, has been first defined and drawn by Robert W. Brooks and Peter Matelski in 1978 [1], and later made famous by Benoit Mandelbrot (see e.g. [2]). The dynamics generates by represent a huge sources of fractal structures (see e.g. [3, 4, 5, 6]).
Julia sets are made of all points which under iterations do not go to an attractor which may be at infinity. Compared to Mandelbrot set, where is variable in the parametric plane , Julia sets are obtained for fixed and the origin of iterations variable in .
The Mandelbrot set is known as the set of all points for which Julia sets are compact and connected.
Details and background on Mandelbrot set and Julia sets can be found in the following works [2, 7, 8, 9, 10, 3, 11], to cite only few of them.
Due the description of memory and hereditary properties, Fractional Order (FO) difference equations still receive increasing attention. However, as mentioned in [12], overall, fractional calculus, closely related to classical calculus, is not direct generalization of classical calculus in the sense of rigorous mathematics. One of the first definitions of a fractional difference operator has been proposed in 1974 [13]. While there are many works on fractional differential equations, there still are only few works in the theory of the fractional finite difference equations. In [14, 15, 16] problems related to Caputo fractional sums and differences can be found, while in [29] Initial Value Problems (IVPs) in fractional differences are studied. For stability of fractional differences compare [17, 18], while properties of fractional discrete logistic map, weakly fractional difference equations, symmetry-breaking of fractional maps can be found in [19, 20, 21]. The nonexistence of periodic solutions in fractional difference equations is analyzed in [22].
Notations utilized in this paper:
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: Mandelbrot of IO;
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: Filled Julia set of IO;
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: Julia set of IO;
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: Mandelbrot set of FO;
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: Filled Julia set of FO;
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DEM: Distance Estimator Method;
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IIM: Inverse Iteration Method
2 Mandelbrot set and Julia sets of integer order
In this section, few of the most important characteristics of set, and sets, which will be revealed analytically or numerically in the cases of Mandelbrot and Julia sets of FO, are briefly presented.
The iteration of is obtained by the relation
(1) |
which generates the sequence
(2) |
where by one understands .
A complex number set if the absolute value of in the sequence (2) remains bounded for all , , for all .
As proposed by Mandelbrot, the boundary of the Mandelbrot set represents a fractal curve (Fig. 1 (a)). For the history related to the origin of the set compare [23].
Consider the set of all points which tend to through the iteration (1)
The set depends on , and his frontier represents the set of .
The filled Julia set for fixed , of IO, related to , which, for computationally reasons is considered in this paper, is the set of all points for which the orbit (2) is bounded
The set is contained in the set and is the boundary of the set
In this paper, beside some new properties related to the Mandelbrot set of FO, the following known properties of Mandelbrot set and Julia sets of IO will be analytically or numerically studied on their FO counterparts.
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1.
The sets for purely real , and set, are symmetric about the real axis (reflection symmetry). Julia sets of are symmetric about the origin.
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2.
As known, it is conjectured that the Mandelbrot set is locally connected [7, 23], the full conjecture of this very technical and complicated property being still open. Mandelbrot had decided empirically that his isolated islands were actually connected to the mainland by very thin filaments [24]. In this paper we are interested in the connectivity property as a computationally property which by using, beside the escape-time algorithm (see Appendix A), a performing method (Distance Estimator Method), revel the filaments connecting the apparently isolated islands to the mainland of the Mandelbrot set or Julia sets, of IO or FO. Empirical small areas are considered.
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3.
The set is the set of all parameters for which are connected sets;
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4.
The set is bounded;
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5.
For situated outside of one obtains Cantor sets (“dust” sets composed of infinitely disjoint points);
- 6.
In this paper the filled Julia sets are considered.
Hereafter, by point in the complex plane, one understands the image in the complex plane of a complex number.
Drawing Mandelbrot set and Julia sets of IO and FO, bases on the theorem which states that iterating , with starting value , only one of the following possibilities happens: either the obtained orbit remains bounded by , or diverges to [5].
In Fig. 1 (a) is presented the set, while in Figs. 1 (c)-(j) there are presented several sets for different values. In Fig. 1 (c), there is presented an set with no interior, with , while in Fig.1 (d) there are presented comparatively, both the and sets for the same value of parameter , obtained with the time-escape algorithm and IIM, [5], respectively.
3 Fractional Order Mandelbrot map
In this section the fractional discretization of the Mandelbrot and Julia sets of FO, in the sense of Caputo-like are introduced.
To obtain the fractional discretization of the , consider the time scale . For and the -th Caputo-like discrete fractional difference of a function is defined as is defined [29, 30] as
(3) |
for and .
is the -th order forward difference operator,
while represents the fractional sum of order of , namely,
with the falling factorial in the following form:
The fractional operator maps functions defined on to functions on (for time scales see, e.g., [31]).
For the case considered in this paper, , when , , and starting point , -th Caputo’s fractional derivative, , becomes
(4) |
Consider next, the FO autonomous IVP in the sense of Caputo’s derivative
(5) |
with a continuous real valued map and . The numerical solution is
(6) |
or, in the convenient form for numerical simulation [21]
(7) |
The recursive iteration implies that (7) is equivalent to the IVP (5) [29] and, therefore, the study of the IVP (5) can be realized, both analytically and numerically, on (7).
(8) |
with a complex continuous function of variable and . Then, the numerical integral (7) of the IVP (8) becomes
(9) |
If one consider the FO variant of the IVP (1), with scaled within a parametric complex domain, , one obtains the numerical integral defining the map
(10) |
To facilitate understanding the numerical implementation of (10), with , , one gets the following scalar form
(11) |
where .
4 Properties of the map
If , the orbits generating by (10) are bounded111Boundedness property of for is not analyzed here (The proof, for , is presented in Proposition 5).. Then
with , so if then also .
Thus, one finds the known property of the set
Proposition 1
set is symmetric about the real axis.
Also, for purely real, following the same reasoning, because , like for sets, one has the following property
Proposition 2
For , the sets are symmetric with respect the real axis.
Next, for one has
Using
(14) |
one obtains for
Thus, we get
Proposition 3
For any , , set.
Property 3 is verified numerically too as indicated by the light blue line AB where and , and set in Fig. 3 (a) for and also Fig. 5 (a) for .
Furthermore, for and , one obtains
Assuming
(15) |
one obtains .
Suppose
for specified latter, and an . Then
(16) |
Next
If
(17) |
one obtains .
Finally, consider
Assuming
(18) |
one obtains .
If in (17) one takes
(19) |
inserting (19) into (16) and (18), one obtains
which is equivalent to
Using , the following relations are obtained
Summarizing, if
(20) |
then equalities (15), (17) and (18) hold with (19), and applying the mathematical induction principle, one obtain
For , these estimates along with (14) allow to derive
as . The above arguments lead to the next result.
Proposition 4
For any and , satisfying (20), .
Proposition 5
, i.e., the real part of set is a bounded subset of .
Remark 6
Considering the coefficients , , clearly one obtains
Thus letting in (9), we get
(21) |
which corresponds to iteration of a map . Furthermore,
For , while for , we have
Thus letting in (9), we get
(22) |
which corresponds to iteration of a map only if and, in general, it gives different iterations. Of course this holds just for finite/bounded times of iterations. Indeed, if for any , from (9) one obtains
So the iterations do depend on on .
If the IVP (8) is considered in the sense of map (with scanning and ), for ,the numerical integral (21) becomes
(23) |
while for
(24) |
If the IVP (8) is considered in the sense of sets (with scanning and fixed ), for , the numerical integral (21) becomes
(25) |
while for
(26) |
Propositions 4 and 5 are verified numerically as well. Thus, for , from (20) one gets , values for which does not exists (see Fig. 5 (a), wherefrom one can see that the projection of the on the real axis is included in the segment . These properties are verified also for the case , when one gets , and where the set does not exists and the projection of the on the real is contained in the segment (Fig. 3 (a)).
Remark 7
Studying the dynamics of the case in general is challenging task. For instance, consider the general relation
(27) |
for and . Then
Thus if then . If , then . The relation (27) has the only equilibrium , so the limit point is not an equilibrium of (27). Next, taking , we get the new limit point , and repeating this procedure, we get a sequence of limit points . If then this sequence tends to . If then this sequence oscillates on the unit circle . If then this sequence tends to .
One can see that the dynamics of (27) for is much more complicated then for the standard linear map .
5 Numerical approach of set and sets
set and sets are generated with the escape-time algorithm adapted to complex FO discrete equations and is presented in Appendix A.
In (10), numerically, can take the limit value 1 (see Remark 6)). Therefore, hereafter, the limit case will be considered .
Regarding the other limit case, , due to the fact is not defined and the limit is considered on small intervals, in this paper for numerically reasons, the limit has been considered empirically, as , and will be denoted .
Remark 8
For , linked to Remark 6, one get numerically the following important identity properties (congruent-like shapes) which, for now, are introduced as conjectures
Conjecture 1
For , =. (Fig. 4 (a)).
Conjecture 2
For , and , =. (Fig. 4 (i)).
sets are generated for , and, for some cases, for close to neighborhood. To verify the connectedness property, some empirical zoomed details are considered, where DEM [5] is used.
In Figs. 2 (a)-(d) four representative cases of sets for , , and , respectively, are comparatively presented.
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1.
Consider the for (Figs. 3). As can be seen, there are several differences compared to the IO case. Thus, contrary to expectations, according to which should be similar with while approaches (FO cases are considered, generally, that they are generalizations of IO cases), the set for is far from being similar to the set. Also, the connectedness property of the seems to be broken. For example, the zoom of the detail D in Fig. 3 (a), obtained with DEM method (Fig. 3 (b)), shows that the seems to not have the connectedness property. On the other hand, again contrary to expectations, for , sets look similar to IO Julia sets, but translated with along the real axis. See for example, the and (Fig 3 (j) and Fig. 1 (j)), or and (Fig. 3 (i) and Fig. 1 (i)). Also, the central symmetry encountered at sets is verified, but not with respect the origin, but with respect to a horizontally translated center. Like for the set, points within generate connected (Figs. 3 (d), (f), (h-j)), while points outside generate disconnected fractals (Fig. 3 (c)). Due to the inherent numerical errors, connectedness property cannot be precisely numerically stated for points close to frontier (see e.g. Fig. 3 (e) or (g)).
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2.
Let the other extreme case, (Figs. 4). Again, contrary to expectations, in this case, when approaches , the is similar to (Conjecture 1). Empirically verified connectedness property seems to verify (see detail D and his zoom in Fig. 4 (a) and (b)). The sets look like some parts of a set (probably parts of the ) obtained with a magnifier-like. Another property is the fact that, for all values of , within or outside the set, the sets still look connected sets. Also, except the points on the real axis, the sets have not central symmetry. However, probably the most important property is the fact that for , the set is actually the set (see the red rectangle in Fig. 4 (i) and Conjecture 2).
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3.
For the intermediate case , see Figs. 5. Now, excepting the values of belonging to the real axis, where the sets are symmetric with respect the real axis (see Figs. 5 (h), (g), (e), (d) and Proposition 2), the central symmetry and also connectedness of the are lost (see the zoom of detail D in Fig. 5 (a), presented in Fig. 5 (b)). Also, the frontier of the is not connected (see the zoomed detail of the region , Figs. 5 (e) and (f)).
Conclusion and open problems
In this paper the FO Mandelbrot map and set and FO Julia sets in the Caputo’s sense are introduced. Some properties of the map and are analytically studied and some of them numerically verified. The set and sets are obtained with the escape-time algorithm adapted for FO discrete complex maps, while to verify computationally the connectedness properties for some cases, zoomed details are obtained with DEM adapted to FO discrete complex maps. Similarities, and especially differences, between the IO case and FO case are summarizing next.
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Excepting the case , the sets have not central symmetry;
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For and also for some , the sets are imbedded within rectangular domains which, contrary to the sets, are not centered at the origin, but translated along the real axis (see Paragraphs 1 and 3, Section 5);
- •
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For , sets presents a central symmetry with respect a translated center (see Fig. 3);
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Contrary to the IO case, except the case , for , the sets have not central symmetry (see Paragraphs 2 and Paragraph 3, Section 5);
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The FO discretization for the Mandelbrot set, for , is not as expected, a generalization of the set (Fig. 3).
Beside the results obtained in this paper with the aid of the analytical and numerical approach, several other open problems remain, such as:
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the proof of the translation of the sets like in the case (Figs. 3);
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the fact that for the shape of the set (Fig. 3 (a)) does not lead, as expected, to the shape of the set, is typical only to this complex FO system, or apply to other discrete FO systems (real or complex) too? Similar question is open for the case ;
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the proof that in the case of , the known filled disk for corresponding to the for , looks identical with the filled circled ( set) for (Fig. 3 (i));
- •
- •
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is the translated center of the symmetry of sets related with the critical point of the sets which, for the sets of a quadratic polynomial need not be ?
Acknowledgement
The authors would like to thank Reviewers for taking the necessary time and effort to review the manuscript.
Conflict of Interest: The authors declare that they have no conflict of interest





Appendices
A Escape-time algoritm for set and sets
There are several algorithms to plot the sets as the escape-time method, the boundary scanning method, the inverse iteration method. Also there are several optimizations to increase the speed and images accuracy (see e.g. [5]). For the exposition clarity, in this paper only black/white coloring scheme is used (for color schemes see e.g. [5]).
In this paper the Mandelbrot and Julia sets, of IO or FO, are obtained with the slow, but easy to understand escape-time algorithm based on the theorem which states that iterating , with starting value , only one of the following possibilities happens: either the obtained orbit remains bounded by 2, or diverges to . For Mandelbrot set , and is varied within a complex parametric domain, usually rectangular, while for Julia sets is varied and fixed. This well known algorithm is considered in order to facilitate the presentation of the algorithm for the and sets. For simplicity, in this paper the complex parametric plane of and the plane of the complex variable are considered similar.
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1.
To generate the set with the escape-time algorithm, consider in the cartesian plane the image of a rectangular domain of complex numbers , , with an equidistant grid of points , . The exploration of numbers within the considered complex domain , can be realized with two nested loops, while a third, inner cycle (steps (9)-(13), Fig.A), the core of the algorithm, makes the escape-time verification. The inside cycle implements the integrals (11) and (13). As for , for the is taken . The domain is explored with the steps , and . To generate the , to each within , one applies the recurrence (11) until, either after a chosen finite number of iterations, (in this paper ), , , , remains less than 2 and the underlying point belongs to being plotted black, or becomes greater or equal to 2 (escape radius), when and is not plotted. Note that because of the symmetry of the , if one intends to generate the entire set, one might save about of drawing time if the algorithm is run only on the superior half of the complex plane, with and plotting .
The pseudocode is presented in Fig. A.
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2.
To generate sets, one iterates the map , but with fixed and variable inside with the recurrence (13). The initial condition, variable, is denoted . If after iterations, , remains less than 2, the underlying point (of coordinates and ) belongs to and is plotted black. If becomes greater or equal to 2, and is not plotted. The input data are and data defining ( and ), and . For most of sets, , not as for sets. The exploration of the domain is realized with , and .
The pseudocode is presented in Fig. B. variables and are designed for the inner loop.
Several speed improvements can be done, such as calculating instead , or calculating only once the expressions and , or plotting after the domain is explored and so on. Also, the algorithm can be written y using e.g. the vectorial calculus, such as the performing matrix calculus of Matlab. Regarding the implementation in Matlab, a solution for the zero index can be found in [20].
,
,
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