In mathematics, a **fractal** is a geometric shape containing detailed structure at arbitrarily small scales, usually having a fractal dimension strictly exceeding the topological dimension. Many fractals appear similar at various scales, as illustrated in successive magnifications of the Mandelbrot set.^{ [1] }^{ [2] }^{ [3] }^{ [4] } This exhibition of similar patterns at increasingly smaller scales is called self-similarity, also known as expanding symmetry or unfolding symmetry; if this replication is exactly the same at every scale, as in the Menger sponge, the shape is called affine self-similar.^{ [5] } Fractal geometry lies within the mathematical branch of measure theory.

- Etymology
- Introduction
- History 2
- Definition and characteristics
- Common techniques for generating fractals
- Applications
- Simulated fractals
- Natural phenomena with fractal features
- Fractals in cell biology
- In creative works
- Physiological responses
- Applications in technology
- See also
- Notes
- References
- Further reading
- External links

One way that fractals are different from finite geometric figures is how they scale. Doubling the edge lengths of a filled polygon multiplies its area by four, which is two (the ratio of the new to the old side length) raised to the power of two (the conventional dimension of the filled polygon). Likewise, if the radius of a filled sphere is doubled, its volume scales by eight, which is two (the ratio of the new to the old radius) to the power of three (the conventional dimension of the filled sphere). However, if a fractal's one-dimensional lengths are all doubled, the spatial content of the fractal scales by a power that is not necessarily an integer and is in general greater than its conventional dimension.^{ [1] } This power is called the fractal dimension of the geometric object, to distinguish it from the conventional dimension (which is formally called the topological dimension).^{ [6] }

Analytically, many fractals are nowhere differentiable.^{ [1] }^{ [4] } An infinite fractal curve can be conceived of as winding through space differently from an ordinary line – although it is still topologically 1-dimensional, its fractal dimension indicates that it locally fills space more efficiently than an ordinary line.^{ [1] }^{ [6] }

Starting in the 17th century with notions of recursion, fractals have moved through increasingly rigorous mathematical treatment to the study of continuous but not differentiable functions in the 19th century by the seminal work of Bernard Bolzano, Bernhard Riemann, and Karl Weierstrass,^{ [7] } and on to the coining of the word * fractal * in the 20th century with a subsequent burgeoning of interest in fractals and computer-based modelling in the 20th century.^{ [8] }^{ [9] }

There is some disagreement among mathematicians about how the concept of a fractal should be formally defined. Mandelbrot himself summarized it as "beautiful, damn hard, increasingly useful. That's fractals."^{ [10] } More formally, in 1982 Mandelbrot defined *fractal* as follows: "A fractal is by definition a set for which the Hausdorff–Besicovitch dimension strictly exceeds the topological dimension."^{ [11] } Later, seeing this as too restrictive, he simplified and expanded the definition to this: "A fractal is a rough or fragmented geometric shape that can be split into parts, each of which is (at least approximately) a reduced-size copy of the whole."^{ [1] } Still later, Mandelbrot proposed "to use *fractal* without a pedantic definition, to use * fractal dimension * as a generic term applicable to *all* the variants".^{ [12] }

The consensus among mathematicians is that theoretical fractals are infinitely self-similar iterated and detailed mathematical constructs, of which many examples have been formulated and studied.^{ [1] }^{ [2] }^{ [3] } Fractals are not limited to geometric patterns, but can also describe processes in time.^{ [5] }^{ [4] }^{ [13] }^{ [14] }^{ [15] }^{ [16] } Fractal patterns with various degrees of self-similarity have been rendered or studied in visual, physical, and aural media^{ [17] } and found in nature,^{ [18] }^{ [19] }^{ [20] }^{ [21] } technology,^{ [22] }^{ [23] }^{ [24] }^{ [25] } art,^{ [26] }^{ [27] } architecture ^{ [28] } and law.^{ [29] } Fractals are of particular relevance in the field of chaos theory because they show up in the geometric depictions of most chaotic processes (typically either as attractors or as boundaries between basins of attraction).^{ [30] }

The term "fractal" was coined by the mathematician Benoît Mandelbrot in 1975.^{ [31] } Mandelbrot based it on the Latin * frāctus *, meaning "broken" or "fractured", and used it to extend the concept of theoretical fractional dimensions to geometric patterns in nature.^{ [1] }^{ [32] }^{ [33] }

The word "fractal" often has different connotations for the lay public as opposed to mathematicians, where the public is more likely to be familiar with fractal art than the mathematical concept. The mathematical concept is difficult to define formally, even for mathematicians, but key features can be understood with a little mathematical background.

The feature of "self-similarity", for instance, is easily understood by analogy to zooming in with a lens or other device that zooms in on digital images to uncover finer, previously invisible, new structure. If this is done on fractals, however, no new detail appears; nothing changes and the same pattern repeats over and over, or for some fractals, nearly the same pattern reappears over and over. Self-similarity itself is not necessarily counter-intuitive (e.g., people have pondered self-similarity informally such as in the infinite regress in parallel mirrors or the homunculus, the little man inside the head of the little man inside the head ...). The difference for fractals is that the pattern reproduced must be detailed.^{ [1] }^{: 166, 18 }^{ [2] }^{ [32] }

This idea of being detailed relates to another feature that can be understood without much mathematical background: Having a fractal dimension greater than its topological dimension, for instance, refers to how a fractal scales compared to how geometric shapes are usually perceived. A straight line, for instance, is conventionally understood to be one-dimensional; if such a figure is rep-tiled into pieces each 1/3 the length of the original, then there are always three equal pieces. A solid square is understood to be two-dimensional; if such a figure is rep-tiled into pieces each scaled down by a factor of 1/3 in both dimensions, there are a total of 3^{2} = 9 pieces.

We see that for ordinary self-similar objects, being n-dimensional means that when it is rep-tiled into pieces each scaled down by a scale-factor of 1/*r*, there are a total of *r*^{n} pieces. Now, consider the Koch curve. It can be rep-tiled into four sub-copies, each scaled down by a scale-factor of 1/3. So, strictly by analogy, we can consider the "dimension" of the Koch curve as being the unique real number *D* that satisfies 3^{D} = 4. This number is called the *fractal dimension* of the Koch curve; it is not the conventionally perceived dimension of a curve. In general, a key property of fractals is that the fractal dimension differs from the *conventionally understood* dimension (formally called the topological dimension).

This also leads to understanding a third feature, that fractals as mathematical equations are "nowhere differentiable". In a concrete sense, this means fractals cannot be measured in traditional ways.^{ [1] }^{ [4] }^{ [34] } To elaborate, in trying to find the length of a wavy non-fractal curve, one could find straight segments of some measuring tool small enough to lay end to end over the waves, where the pieces could get small enough to be considered to conform to the curve in the normal manner of measuring with a tape measure. But in measuring an infinitely "wiggly" fractal curve such as the Koch snowflake, one would never find a small enough straight segment to conform to the curve, because the jagged pattern would always re-appear, at arbitrarily small scales, essentially pulling a little more of the tape measure into the total length measured each time one attempted to fit it tighter and tighter to the curve. The result is that one must need infinite tape to perfectly cover the entire curve, i.e. the snowflake has an infinite perimeter.^{ [1] }

The history of fractals traces a path from chiefly theoretical studies to modern applications in computer graphics, with several notable people contributing canonical fractal forms along the way.^{ [8] }^{ [9] } A common theme in traditional African architecture is the use of fractal scaling, whereby small parts of the structure tend to look similar to larger parts, such as a circular village made of circular houses.^{ [35] } According to Pickover, the mathematics behind fractals began to take shape in the 17th century when the mathematician and philosopher Gottfried Leibniz pondered recursive self-similarity (although he made the mistake of thinking that only the straight line was self-similar in this sense).^{ [36] }

In his writings, Leibniz used the term "fractional exponents", but lamented that "Geometry" did not yet know of them.^{ [1] }^{: 405 } Indeed, according to various historical accounts, after that point few mathematicians tackled the issues and the work of those who did remained obscured largely because of resistance to such unfamiliar emerging concepts, which were sometimes referred to as mathematical "monsters".^{ [34] }^{ [8] }^{ [9] } Thus, it was not until two centuries had passed that on July 18, 1872 Karl Weierstrass presented the first definition of a function with a graph that would today be considered a fractal, having the non-intuitive property of being everywhere continuous but nowhere differentiable at the Royal Prussian Academy of Sciences.^{ [8] }^{: 7 }^{ [9] }

In addition, the quotient difference becomes arbitrarily large as the summation index increases.^{ [37] } Not long after that, in 1883, Georg Cantor, who attended lectures by Weierstrass,^{ [9] } published examples of subsets of the real line known as Cantor sets, which had unusual properties and are now recognized as fractals.^{ [8] }^{: 11–24 } Also in the last part of that century, Felix Klein and Henri Poincaré introduced a category of fractal that has come to be called "self-inverse" fractals.^{ [1] }^{: 166 }

One of the next milestones came in 1904, when Helge von Koch, extending ideas of Poincaré and dissatisfied with Weierstrass's abstract and analytic definition, gave a more geometric definition including hand-drawn images of a similar function, which is now called the Koch snowflake.^{ [8] }^{: 25 }^{ [9] } Another milestone came a decade later in 1915, when Wacław Sierpiński constructed his famous triangle then, one year later, his carpet. By 1918, two French mathematicians, Pierre Fatou and Gaston Julia, though working independently, arrived essentially simultaneously at results describing what is now seen as fractal behaviour associated with mapping complex numbers and iterative functions and leading to further ideas about attractors and repellors (i.e., points that attract or repel other points), which have become very important in the study of fractals.^{ [4] }^{ [8] }^{ [9] }

Very shortly after that work was submitted, by March 1918, Felix Hausdorff expanded the definition of "dimension", significantly for the evolution of the definition of fractals, to allow for sets to have non-integer dimensions.^{ [9] } The idea of self-similar curves was taken further by Paul Lévy, who, in his 1938 paper *Plane or Space Curves and Surfaces Consisting of Parts Similar to the Whole*, described a new fractal curve, the Lévy C curve.^{ [notes 1] }

Different researchers have postulated that without the aid of modern computer graphics, early investigators were limited to what they could depict in manual drawings, so lacked the means to visualize the beauty and appreciate some of the implications of many of the patterns they had discovered (the Julia set, for instance, could only be visualized through a few iterations as very simple drawings).^{ [1] }^{: 179 }^{ [34] }^{ [9] } That changed, however, in the 1960s, when Benoit Mandelbrot started writing about self-similarity in papers such as * How Long Is the Coast of Britain? Statistical Self-Similarity and Fractional Dimension *,^{ [38] }^{ [39] } which built on earlier work by Lewis Fry Richardson.

In 1975^{ [32] } Mandelbrot solidified hundreds of years of thought and mathematical development in coining the word "fractal" and illustrated his mathematical definition with striking computer-constructed visualizations. These images, such as of his canonical Mandelbrot set, captured the popular imagination; many of them were based on recursion, leading to the popular meaning of the term "fractal".^{ [40] }^{ [34] }^{ [8] }^{ [36] }

In 1980, Loren Carpenter gave a presentation at the SIGGRAPH where he introduced his software for generating and rendering fractally generated landscapes.^{ [41] }

One often cited description that Mandelbrot published to describe geometric fractals is "a rough or fragmented geometric shape that can be split into parts, each of which is (at least approximately) a reduced-size copy of the whole";^{ [1] } this is generally helpful but limited. Authors disagree on the exact definition of *fractal*, but most usually elaborate on the basic ideas of self-similarity and the unusual relationship fractals have with the space they are embedded in.^{ [1] }^{ [5] }^{ [2] }^{ [4] }^{ [42] }

One point agreed on is that fractal patterns are characterized by fractal dimensions, but whereas these numbers quantify complexity (i.e., changing detail with changing scale), they neither uniquely describe nor specify details of how to construct particular fractal patterns.^{ [43] } In 1975 when Mandelbrot coined the word "fractal", he did so to denote an object whose Hausdorff–Besicovitch dimension is greater than its topological dimension.^{ [32] } However, this requirement is not met by space-filling curves such as the Hilbert curve.^{ [notes 2] }

Because of the trouble involved in finding one definition for fractals, some argue that fractals should not be strictly defined at all. According to Falconer, fractals should be only generally characterized by a gestalt of the following features;^{ [2] }

- Self-similarity, which may include:

- Exact self-similarity: identical at all scales, such as the Koch snowflake
- Quasi self-similarity: approximates the same pattern at different scales; may contain small copies of the entire fractal in distorted and degenerate forms; e.g., the Mandelbrot set's satellites are approximations of the entire set, but not exact copies.
- Statistical self-similarity: repeats a pattern stochastically so numerical or statistical measures are preserved across scales; e.g., randomly generated fractals like the well-known example of the coastline of Britain for which one would not expect to find a segment scaled and repeated as neatly as the repeated unit that defines fractals like the Koch snowflake.
^{ [4] } - Qualitative self-similarity: as in a time series
^{ [13] } - Multifractal scaling: characterized by more than one fractal dimension or scaling rule

- Fine or detailed structure at arbitrarily small scales. A consequence of this structure is fractals may have emergent properties
^{ [44] }(related to the next criterion in this list). - Irregularity locally and globally that cannot easily be described in the language of traditional Euclidean geometry other than as the limit of a recursively defined sequence of stages. For images of fractal patterns, this has been expressed by phrases such as "smoothly piling up surfaces" and "swirls upon swirls";
^{ [6] }*see Common techniques for generating fractals*.

As a group, these criteria form guidelines for excluding certain cases, such as those that may be self-similar without having other typically fractal features. A straight line, for instance, is self-similar but not fractal because it lacks detail, and is easily described in Euclidean language without a need for recursion.^{ [1] }^{ [4] }

Images of fractals can be created by fractal generating programs. Because of the butterfly effect, a small change in a single variable can have an unpredictable outcome.

*Iterated function systems (IFS)*– use fixed geometric replacement rules; may be stochastic or deterministic;^{ [45] }e.g., Koch snowflake, Cantor set, Haferman carpet,^{ [46] }Sierpinski carpet, Sierpinski gasket, Peano curve, Harter-Heighway dragon curve, T-square, Menger sponge*Strange attractors*– use iterations of a map or solutions of a system of initial-value differential or difference equations that exhibit chaos (e.g., see multifractal image, or the logistic map)*L-systems*– use string rewriting; may resemble branching patterns, such as in plants, biological cells (e.g., neurons and immune system cells^{ [21] }), blood vessels, pulmonary structure,^{ [47] }etc. or turtle graphics patterns such as space-filling curves and tilings*Escape-time fractals*– use a formula or recurrence relation at each point in a space (such as the complex plane); usually quasi-self-similar; also known as "orbit" fractals; e.g., the Mandelbrot set, Julia set, Burning Ship fractal, Nova fractal and Lyapunov fractal. The 2d vector fields that are generated by one or two iterations of escape-time formulae also give rise to a fractal form when points (or pixel data) are passed through this field repeatedly.*Random fractals*– use stochastic rules; e.g., Lévy flight, percolation clusters, self avoiding walks, fractal landscapes, trajectories of Brownian motion and the Brownian tree (i.e., dendritic fractals generated by modeling diffusion-limited aggregation or reaction-limited aggregation clusters).^{ [4] }

*Finite subdivision rules*– use a recursive topological algorithm for refining tilings^{ [48] }and they are similar to the process of cell division.^{ [49] }The iterative processes used in creating the Cantor set and the Sierpinski carpet are examples of finite subdivision rules, as is barycentric subdivision.

Fractal patterns have been modeled extensively, albeit within a range of scales rather than infinitely, owing to the practical limits of physical time and space. Models may simulate theoretical fractals or natural phenomena with fractal features. The outputs of the modelling process may be highly artistic renderings, outputs for investigation, or benchmarks for fractal analysis. Some specific applications of fractals to technology are listed elsewhere. Images and other outputs of modelling are normally referred to as being "fractals" even if they do not have strictly fractal characteristics, such as when it is possible to zoom into a region of the fractal image that does not exhibit any fractal properties. Also, these may include calculation or display artifacts which are not characteristics of true fractals.

Modeled fractals may be sounds,^{ [17] } digital images, electrochemical patterns, circadian rhythms,^{ [50] } etc. Fractal patterns have been reconstructed in physical 3-dimensional space^{ [24] }^{: 10 } and virtually, often called "in silico" modeling.^{ [47] } Models of fractals are generally created using fractal-generating software that implements techniques such as those outlined above.^{ [4] }^{ [13] }^{ [24] } As one illustration, trees, ferns, cells of the nervous system,^{ [21] } blood and lung vasculature,^{ [47] } and other branching patterns in nature can be modeled on a computer by using recursive algorithms and L-systems techniques.^{ [21] }

The recursive nature of some patterns is obvious in certain examples—a branch from a tree or a frond from a fern is a miniature replica of the whole: not identical, but similar in nature. Similarly, random fractals have been used to describe/create many highly irregular real-world objects. A limitation of modeling fractals is that resemblance of a fractal model to a natural phenomenon does not prove that the phenomenon being modeled is formed by a process similar to the modeling algorithms.

Approximate fractals found in nature display self-similarity over extended, but finite, scale ranges. The connection between fractals and leaves, for instance, is currently being used to determine how much carbon is contained in trees.^{ [51] } Phenomena known to have fractal features include:

- Actin cytoskeleton
^{ [52] } - Algae
- Animal coloration patterns
- Blood vessels and pulmonary vessels
^{ [47] } - Brownian motion (generated by a one-dimensional Wiener process).
^{ [53] } - Clouds and rainfall areas
^{ [54] } - Coastlines
- Craters
- Crystals
^{ [55] } - DNA
- Dust grains
^{ [56] } - Earthquakes
^{ [25] }^{ [57] } - Fault lines
- Geometrical optics
^{ [58] } - Heart rates
^{ [18] } - Heart sounds
- Lake shorelines and areas
^{ [59] }^{ [60] }^{ [61] } - Lightning bolts
- Mountain goat horns
- Polymers
- Percolation
- Mountain ranges
- Ocean waves
^{ [62] } - Pineapple
- Proteins
^{ [63] } - Psychedelic Experience
- Purkinje cells
^{ [64] } - Rings of Saturn
^{ [65] }^{ [66] } - River networks
- Romanesco broccoli
- Snowflakes
^{ [67] } - Soil pores
^{ [68] } - Surfaces in turbulent flows
^{ [69] }^{ [70] } - Trees

- Frost crystals occurring naturally on cold glass form fractal patterns
- Fractal basin boundary in a geometrical optical system
^{ [58] } - A fractal is formed when pulling apart two glue-covered acrylic sheets
- High-voltage breakdown within a 4 in (100 mm) block of acrylic glass creates a fractal Lichtenberg figure
- Romanesco broccoli, showing self-similar form approximating a natural fractal
- Fractal defrosting patterns, polar Mars. The patterns are formed by sublimation of frozen CO
_{2}. Width of image is about a kilometer. - Slime mold
*Brefeldia maxima*growing fractally on wood

Fractals often appear in the realm of living organisms where they arise through branching processes and other complex pattern formation. Ian Wong and co-workers have shown that migrating cells can form fractals by clustering and branching.^{ [71] } Nerve cells function through processes at the cell surface, with phenomena that are enhanced by largely increasing the surface to volume ratio. As a consequence nerve cells often are found to form into fractal patterns.^{ [72] } These processes are crucial in cell physiology and different pathologies.^{ [73] }

Multiple subcellular structures also are found to assemble into fractals. Diego Krapf has shown that through branching processes the actin filaments in human cells assemble into fractal patterns.^{ [58] } Similarly Matthias Weiss showed that the endoplasmic reticulum displays fractal features.^{ [74] } The current understanding is that fractals are ubiquitous in cell biology, from proteins, to organelles, to whole cells.

Since 1999 numerous scientific groups have performed fractal analysis on over 50 paintings created by Jackson Pollock by pouring paint directly onto horizontal canvasses.^{ [75] }^{ [76] }^{ [77] }

Recently, fractal analysis has been used to achieve a 93% success rate in distinguishing real from imitation Pollocks.^{ [78] } Cognitive neuroscientists have shown that Pollock's fractals induce the same stress-reduction in observers as computer-generated fractals and Nature's fractals.^{ [79] }

Decalcomania, a technique used by artists such as Max Ernst, can produce fractal-like patterns.^{ [80] } It involves pressing paint between two surfaces and pulling them apart.

Cyberneticist Ron Eglash has suggested that fractal geometry and mathematics are prevalent in African art, games, divination, trade, and architecture. Circular houses appear in circles of circles, rectangular houses in rectangles of rectangles, and so on. Such scaling patterns can also be found in African textiles, sculpture, and even cornrow hairstyles.^{ [27] }^{ [81] } Hokky Situngkir also suggested the similar properties in Indonesian traditional art, batik, and ornaments found in traditional houses.^{ [82] }^{ [83] }

Ethnomathematician Ron Eglash has discussed the planned layout of Benin city using fractals as the basis, not only in the city itself and the villages but even in the rooms of houses. He commented that "When Europeans first came to Africa, they considered the architecture very disorganised and thus primitive. It never occurred to them that the Africans might have been using a form of mathematics that they hadn’t even discovered yet."^{ [84] }

In a 1996 interview with Michael Silverblatt, David Foster Wallace admitted that the structure of the first draft of * Infinite Jest * he gave to his editor Michael Pietsch was inspired by fractals, specifically the Sierpinski triangle (a.k.a. Sierpinski gasket), but that the edited novel is "more like a lopsided Sierpinsky Gasket".^{ [26] }

Some works by the Dutch artist M. C. Escher, such as Circle Limit III, contain shapes repeated to infinity that become smaller and smaller as they get near to the edges, in a pattern that would always look the same if zoomed in.

- A fractal that models the surface of a mountain (animation)
- 3D recursive image
- Recursive fractal butterfly image

Humans appear to be especially well-adapted to processing fractal patterns with D values between 1.3 and 1.5.^{ [85] } When humans view fractal patterns with D values between 1.3 and 1.5, this tends to reduce physiological stress.^{ [86] }^{ [87] }

- Fractal antennas
^{ [88] } - Fractal transistor
^{ [89] } - Fractal heat exchangers
^{ [90] } - Digital imaging
- Architecture
^{ [28] } - Urban growth
^{ [91] }^{ [92] } - Classification of histopathology slides
- Fractal landscape or Coastline complexity
- Detecting 'life as we don't know it' by fractal analysis
^{ [93] } - Enzymes (Michaelis-Menten kinetics)
- Generation of new music
- Signal and image compression
- Creation of digital photographic enlargements
- Fractal in soil mechanics
- Computer and video game design
- Computer Graphics
- Organic environments
- Procedural generation
- Fractography and fracture mechanics
- Small angle scattering theory of fractally rough systems
- T-shirts and other fashion
- Generation of patterns for camouflage, such as MARPAT
- Digital sundial
- Technical analysis of price series
- Fractals in networks
- Medicine
^{ [24] } - Neuroscience
^{ [19] }^{ [20] } - Diagnostic Imaging
^{ [23] } - Pathology
^{ [94] }^{ [95] } - Geology
^{ [96] } - Geography
^{ [97] } - Archaeology
^{ [98] }^{ [99] } - Soil mechanics
^{ [22] } - Seismology
^{ [25] } - Search and rescue
^{ [100] } - Technical analysis
- Morton order space filling curves for GPU cache coherency in texture mapping,
^{ [101] }^{ [102] }^{ [103] }rasterisation^{ [104] }^{ [105] }and indexing of turbulence data.^{ [106] }^{ [107] }

- Banach fixed point theorem
- Bifurcation theory
- Box counting
- Cymatics
- Determinism
- Diamond-square algorithm
- Droste effect
- Feigenbaum function
- Form constant
- Fractal cosmology
- Fractal derivative
- Fractalgrid
- Fractal string
- Fracton
- Graftal
- Greeble
- Infinite regress
- Lacunarity
- List of fractals by Hausdorff dimension
- Mandelbulb
- Mandelbox
- Macrocosm and microcosm
- Matryoshka doll
- Menger Sponge
- Multifractal system
- Newton fractal
- Percolation
- Power law
- Publications in fractal geometry
- Random walk
- Self-reference
- Self-similarity
- Systems theory
- Strange loop
- Turbulence
- Wiener process

- ↑ The original paper, Lévy, Paul (1938). "Les Courbes planes ou gauches et les surfaces composées de parties semblables au tout".
*Journal de l'École Polytechnique*: 227–247, 249–291., is translated in Edgar, pages 181–239. - ↑ The Hilbert curve map is not a homeomorphism, so it does not preserve topological dimension. The topological dimension and Hausdorff dimension of the image of the Hilbert map in
**R**^{2}are both 2. Note, however, that the topological dimension of the*graph*of the Hilbert map (a set in**R**^{3}) is 1.

**Benoit B.****Mandelbrot** was a Polish-born French-American mathematician and polymath with broad interests in the practical sciences, especially regarding what he labeled as "the art of roughness" of physical phenomena and "the uncontrolled element in life". He referred to himself as a "fractalist" and is recognized for his contribution to the field of fractal geometry, which included coining the word "fractal", as well as developing a theory of "roughness and self-similarity" in nature.

**Chaos theory** is an interdisciplinary area of scientific study and branch of mathematics focused on underlying patterns and deterministic laws of dynamical systems that are highly sensitive to initial conditions, and were once thought to have completely random states of disorder and irregularities. Chaos theory states that within the apparent randomness of chaotic complex systems, there are underlying patterns, interconnection, constant feedback loops, repetition, self-similarity, fractals, and self-organization. The butterfly effect, an underlying principle of chaos, describes how a small change in one state of a deterministic nonlinear system can result in large differences in a later state. A metaphor for this behavior is that a butterfly flapping its wings in Brazil can cause a tornado in Texas.

In mathematics, **Hausdorff dimension** is a measure of *roughness*, or more specifically, fractal dimension, that was first introduced in 1918 by mathematician Felix Hausdorff. For instance, the Hausdorff dimension of a single point is zero, of a line segment is 1, of a square is 2, and of a cube is 3. That is, for sets of points that define a smooth shape or a shape that has a small number of corners—the shapes of traditional geometry and science—the Hausdorff dimension is an integer agreeing with the usual sense of dimension, also known as the topological dimension. However, formulas have also been developed that allow calculation of the dimension of other less simple objects, where, solely on the basis of their properties of scaling and self-similarity, one is led to the conclusion that particular objects—including fractals—have non-integer Hausdorff dimensions. Because of the significant technical advances made by Abram Samoilovitch Besicovitch allowing computation of dimensions for highly irregular or "rough" sets, this dimension is also commonly referred to as the *Hausdorff–Besicovitch dimension.*

The **Mandelbrot set** is the set of complex numbers for which the function does not diverge to infinity when iterated from , i.e., for which the sequence , , etc., remains bounded in absolute value.

In mathematics, a **self-similar** object is exactly or approximately similar to a part of itself. Many objects in the real world, such as coastlines, are statistically self-similar: parts of them show the same statistical properties at many scales. Self-similarity is a typical property of fractals. Scale invariance is an exact form of self-similarity where at any magnification there is a smaller piece of the object that is similar to the whole. For instance, a side of the Koch snowflake is both symmetrical and scale-invariant; it can be continually magnified 3x without changing shape. The non-trivial similarity evident in fractals is distinguished by their fine structure, or detail on arbitrarily small scales. As a counterexample, whereas any portion of a straight line may resemble the whole, further detail is not revealed.

The **Sierpiński triangle**, also called the **Sierpiński gasket** or **Sierpiński sieve**, is a fractal attractive fixed set with the overall shape of an equilateral triangle, subdivided recursively into smaller equilateral triangles. Originally constructed as a curve, this is one of the basic examples of self-similar sets—that is, it is a mathematically generated pattern that is reproducible at any magnification or reduction. It is named after the Polish mathematician Wacław Sierpiński, but appeared as a decorative pattern many centuries before the work of Sierpiński.

The **Koch snowflake** is a fractal curve and one of the earliest fractals to have been described. It is based on the Koch curve, which appeared in a 1904 paper titled "On a Continuous Curve Without Tangents, Constructible from Elementary Geometry" by the Swedish mathematician Helge von Koch.

**Fractal art** is a form of algorithmic art created by calculating fractal objects and representing the calculation results as still digital images, animations, and media. Fractal art developed from the mid-1980s onwards. It is a genre of computer art and digital art which are part of new media art. The mathematical beauty of fractals lies at the intersection of generative art and computer art. They combine to produce a type of abstract art.

A **fractal antenna** is an antenna that uses a fractal, self-similar design to maximize the effective length, or increase the perimeter, of material that can receive or transmit electromagnetic radiation within a given total surface area or volume.

A **pattern** is a regularity in the world, in human-made design, or in abstract ideas. As such, the elements of a pattern repeat in a predictable manner. A **geometric pattern** is a kind of pattern formed of geometric shapes and typically repeated like a wallpaper design.

A **fractal landscape** or **fractal surface** is generated using a stochastic algorithm designed to produce fractal behavior that mimics the appearance of natural terrain. In other words, the surface resulting from the procedure is not a deterministic, but rather a random surface that exhibits fractal behavior.

In mathematics, a **fractal dimension** is a term invoked in the science of geometry to provide a rational statistical index of complexity detail in a pattern. A fractal pattern changes with the scale at which it is measured. It has also been mythologized as a measure of the space-filling capacity of a pattern that tells how a fractal scales differently and in a fractal dimension, i.e. one that does not have to be an integer.

A **Lévy flight** is a random walk in which the step-lengths have a stable distribution, a probability distribution that is heavy-tailed. When defined as a walk in a space of dimension greater than one, the steps made are in isotropic random directions. Later researchers have extended the use of the term "Lévy flight" to also include cases where the random walk takes place on a discrete grid rather than on a continuous space.

"**How Long Is the Coast of Britain? Statistical Self-Similarity and Fractional Dimension**" is a paper by mathematician Benoit Mandelbrot, first published in *Science* on 5 May 1967. In this paper, Mandelbrot discusses self-similar curves that have Hausdorff dimension between 1 and 2. These curves are examples of *fractals*, although Mandelbrot does not use this term in the paper, as he did not coin it until 1975. The paper is one of Mandelbrot's first publications on the topic of fractals.

A **fractal curve** is, loosely, a mathematical curve whose shape retains the same general pattern of irregularity, regardless of how high it is magnified, that is, its graph takes the form of a fractal. In general, fractal curves are nowhere rectifiable curves — that is, they do not have finite length — and every subarc longer than a single point has infinite length.

The **coastline paradox** is the counterintuitive observation that the coastline of a landmass does not have a well-defined length. This results from the fractal curve-like properties of coastlines; i.e., the fact that a coastline typically has a fractal dimension. Although the "paradox of length" was previously noted by Hugo Steinhaus, the first systematic study of this phenomenon was by Lewis Fry Richardson, and it was expanded upon by Benoit Mandelbrot.

In fractal geometry, the **H tree** is a fractal tree structure constructed from perpendicular line segments, each smaller by a factor of the square root of 2 from the next larger adjacent segment. It is so called because its repeating pattern resembles the letter "H". It has Hausdorff dimension 2, and comes arbitrarily close to every point in a rectangle. Its applications include VLSI design and microwave engineering.

**Fractal analysis** is assessing fractal characteristics of data. It consists of several methods to assign a fractal dimension and other fractal characteristics to a dataset which may be a theoretical dataset, or a pattern or signal extracted from phenomena including topography, natural geometric objects, ecology and aquatic sciences, sound, market fluctuations, heart rates, frequency domain in electroencephalography signals, digital images, molecular motion, and data science. Fractal analysis is now widely used in all areas of science. An important limitation of fractal analysis is that arriving at an empirically determined fractal dimension does not necessarily prove that a pattern is fractal; rather, other essential characteristics have to be considered. Fractal analysis is valuable in expanding our knowledge of the structure and function of various systems, and as a potential tool to mathematically assess novel areas of study. Fractal calculus was formulated which is a generalization of ordinary calculus.

**Patterns in nature** are visible regularities of form found in the natural world. These patterns recur in different contexts and can sometimes be modelled mathematically. Natural patterns include symmetries, trees, spirals, meanders, waves, foams, tessellations, cracks and stripes. Early Greek philosophers studied pattern, with Plato, Pythagoras and Empedocles attempting to explain order in nature. The modern understanding of visible patterns developed gradually over time.

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*Fractals Everywhere*. Boston: Academic Press Professional, 1993. ISBN 0-12-079061-0 - Duarte, German A.;
*Fractal Narrative. About the Relationship Between Geometries and Technology and Its Impact on Narrative Spaces*. Bielefeld: Transcript, 2014. ISBN 978-3-8376-2829-6 - Falconer, Kenneth;
*Techniques in Fractal Geometry*. John Wiley and Sons, 1997. ISBN 0-471-92287-0 - Jürgens, Hartmut; Peitgen, Heinz-Otto; and Saupe, Dietmar;
*Chaos and Fractals: New Frontiers of Science*. New York: Springer-Verlag, 1992. ISBN 0-387-97903-4 - Mandelbrot, Benoit B.;
*The Fractal Geometry of Nature*. New York: W. H. Freeman and Co., 1982. ISBN 0-7167-1186-9 - Peitgen, Heinz-Otto; and Saupe, Dietmar; eds.;
*The Science of Fractal Images*. New York: Springer-Verlag, 1988. ISBN 0-387-96608-0 - Pickover, Clifford A.; ed.;
*Chaos and Fractals: A Computer Graphical Journey – A 10 Year Compilation of Advanced Research*. Elsevier, 1998. ISBN 0-444-50002-2 - Jones, Jesse;
*Fractals for the Macintosh*, Waite Group Press, Corte Madera, CA, 1993. ISBN 1-878739-46-8. - Lauwerier, Hans;
*Fractals: Endlessly Repeated Geometrical Figures*, Translated by Sophia Gill-Hoffstadt, Princeton University Press, Princeton NJ, 1991. ISBN 0-691-08551-X, cloth. ISBN 0-691-02445-6 paperback. "This book has been written for a wide audience..." Includes sample BASIC programs in an appendix. - Sprott, Julien Clinton (2003).
*Chaos and Time-Series Analysis*. Oxford University Press. ISBN 978-0-19-850839-7. - Wahl, Bernt; Van Roy, Peter; Larsen, Michael; and Kampman, Eric;
*Exploring Fractals on the Macintosh*, Addison Wesley, 1995. ISBN 0-201-62630-6 - Lesmoir-Gordon, Nigel;
*The Colours of Infinity: The Beauty, The Power and the Sense of Fractals*. 2004. ISBN 1-904555-05-5 (The book comes with a related DVD of the Arthur C. Clarke documentary introduction to the fractal concept and the Mandelbrot set.) - Liu, Huajie;
*Fractal Art*, Changsha: Hunan Science and Technology Press, 1997, ISBN 9787535722348. - Gouyet, Jean-François;
*Physics and Fractal Structures*(Foreword by B. Mandelbrot); Masson, 1996. ISBN 2-225-85130-1, and New York: Springer-Verlag, 1996. ISBN 978-0-387-94153-0. Out-of-print. Available in PDF version at. "Physics and Fractal Structures" (in French). Jfgouyet.fr. Retrieved October 17, 2010. - Falconer, Kenneth (2013).
*Fractals, A Very Short Introduction*. Oxford University Press.

Wikimedia Commons has media related to Fractal .

Wikibooks has a book on the topic of: ** Fractals **

- Fractals at the Library of Congress Web Archives(archived November 16, 2001)
- Hunting the Hidden Dimension, PBS
*NOVA*, first aired August 24, 2011 - Benoit Mandelbrot: Fractals and the Art of Roughness Archived February 17, 2014, at the Wayback Machine , TED, February 2010
- Technical Library on Fractals for controlling fluid
- Equations of self-similar fractal measure based on the fractional-order calculus（2007）

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