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. 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. Fractal geometry lies within the mathematical branch of
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. This power is called the
fractal dimension of the geometric object, to distinguish it from the conventional dimension (which is formally called the
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." 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." 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." Still later, Mandelbrot proposed "to use fractal without a pedantic definition, to use fractal dimension as a generic term applicable to all the variants".
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. Fractals are not limited to geometric patterns, but can also describe processes in time. Fractal patterns with various degrees of self-similarity have been rendered or studied in visual, physical, and aural media and found in
law. 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).
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.: 166, 18 
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 32 = 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 rn 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 3D = 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. 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.
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.
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.
Pickover, the mathematics behind fractals began to take shape in the 17th century when the mathematician and philosopher
Gottfried Leibniz pondered
recursiveself-similarity (although he made the mistake of thinking that only the
straight line was self-similar in this sense).
In his writings, Leibniz used the term "fractional exponents", but lamented that "Geometry" did not yet know of them.: 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". 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
nowhere differentiable at the Royal Prussian Academy of Sciences.: 7 
In addition, the quotient difference becomes arbitrarily large as the summation index increases. Not long after that, in 1883,
Georg Cantor, who attended lectures by Weierstrass, published examples of
subsets of the real line known as
Cantor sets, which had unusual properties and are now recognized as fractals.: 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.: 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.: 25  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.
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. 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]
In 1975 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".
Loren Carpenter gave a presentation at the
SIGGRAPH where he introduced his software for generating and rendering fractally generated landscapes.
Definition and characteristics
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"; 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.
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;
Self-similarity, which may include:
Exact self-similarity: identical at all scales, such as the
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.
Qualitative self-similarity: as in a time series
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 (related to the next criterion in this list).
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.
L-systems – use string rewriting; may resemble branching patterns, such as in plants, biological cells (e.g., neurons and immune system cells), blood vessels, pulmonary structure, etc. or
turtle graphics patterns such as
space-filling curves and tilings
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.
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. Phenomena known to have fractal features include:
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.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. These processes are crucial in cell
physiology and different
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. Similarly Matthias Weiss showed that the
endoplasmic reticulum displays fractal features. The current understanding is that fractals are ubiquitous in cell biology, from
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.
Recently, fractal analysis has been used to achieve a 93% success rate in distinguishing real from imitation Pollocks. Cognitive neuroscientists have shown that Pollock's fractals induce the same stress-reduction in observers as computer-generated fractals and Nature's fractals.
Decalcomania, a technique used by artists such as
Max Ernst, can produce fractal-like patterns. It involves pressing paint between two surfaces and pulling them apart.
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.Hokky Situngkir also suggested the similar properties in Indonesian traditional art,
ornaments found in traditional houses.
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."
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.
Aesthetics and Psychological Effects of Fractal Based Design: Highly prevalent in nature, fractal patterns possess self-similar components that repeat at varying size scales. The perceptual experience of human-made environments can be impacted with inclusion of these natural patterns. Previous work has demonstrated consistent trends in preference for and complexity estimates of fractal patterns. However, limited information has been gathered on the impact of other visual judgments. Here we examine the aesthetic and perceptual experience of fractal ‘global-forest’ designs already installed in humanmade spaces and demonstrate how fractal pattern components are associated with positive psychological experiences that can be utilized to promote occupant well-being. These designs are composite fractal patterns consisting of individual fractal ‘tree-seeds’ which combine to create a ‘global fractal forest.’ The local ‘tree-seed’ patterns, global configuration of tree-seed locations, and overall resulting ‘global-forest’ patterns have fractal qualities. These designs span multiple mediums yet are all intended to lower occupant stress without detracting from the function and overall design of the space. In this series of studies, we first establish divergent relationships between various visual attributes, with pattern complexity, preference, and engagement ratings increasing with fractal complexity compared to ratings of refreshment and relaxation which stay the same or decrease with complexity. Subsequently, we determine that the local constituent fractal (‘tree-seed’) patterns contribute to the perception of the overall fractal design, and address how to balance aesthetic and psychological effects (such as individual experiences of perceived engagement and relaxation) in fractal design installations. This set of studies demonstrates that fractal preference is driven by a balance between increased arousal (desire for engagement and complexity) and decreased tension (desire for relaxation or refreshment). Installations of these composite mid-high complexity ‘global-forest’ patterns consisting of ‘tree-seed’ components balance these contrasting needs, and can serve as a practical implementation of biophilic patterns in human-made environments to promote occupant well-being.
A fractal that models the surface of a mountain (animation)
Humans appear to be especially well-adapted to processing fractal patterns with D values between 1.3 and 1.5. When humans view fractal patterns with D values between 1.3 and 1.5, this tends to reduce physiological stress.
^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 R2 are both 2. Note, however, that the topological dimension of the graph of the Hilbert map (a set in R3) is 1.
abcMandelbrot, Benoît B. (2004). Fractals and Chaos. Berlin: Springer. p. 38.
ISBN978-0-387-20158-0. A fractal set is one for which the fractal (Hausdorff-Besicovitch) dimension strictly exceeds the topological dimension
^Segal, S. L. (June 1978). "Riemann's example of a continuous 'nondifferentiable' function continued". The Mathematical Intelligencer. 1 (2): 81–82.
abKarperien, Audrey L.; Jelinek, Herbert F.; Buchan, Alastair M. (2008). "Box-Counting Analysis of Microglia Form in Schizophrenia, Alzheimer's Disease and Affective Disorder". Fractals. 16 (2): 103.
^Edgar, Gerald (2008). Measure, topology, and fractal geometry. New York: Springer-Verlag. p. 1.
^Karperien, Audrey (2004). Defining microglial morphology: Form, Function, and Fractal Dimension. Charles Sturt University.
^Spencer, John; Thomas, Michael S. C.; McClelland, James L. (2009). Toward a unified theory of development : connectionism and dynamic systems theory re-considered. Oxford/New York: Oxford University Press.
^Taylor, Richard P. (2016). "Fractal Fluency: An Intimate Relationship Between the Brain and Processing of Fractal Stimuli". In Di Ieva, Antonio (ed.). The Fractal Geometry of the Brain. Springer Series in Computational Neuroscience. Springer. pp. 485–496.
^Hohlfeld, Robert G.; Cohen, Nathan (1999). "Self-similarity and the geometric requirements for frequency independence in Antennae". Fractals. 7 (1): 79–84.
^Reiner, Richard; Waltereit, Patrick; Benkhelifa, Fouad; Müller, Stefan; Walcher, Herbert; Wagner, Sandrine; Quay, Rüdiger; Schlechtweg, Michael; Ambacher, Oliver; Ambacher, O. (2012). "Fractal structures for low-resistance large area AlGaN/GaN power transistors". 2012 24th International Symposium on Power Semiconductor Devices and ICs. pp. 341–344.
cite book}}: CS1 maint: date and year (
^Smith, Robert F.; Mohr, David N.; Torres, Vicente E.; Offord, Kenneth P.; Melton III, L. Joseph (1989). "Renal insufficiency in community patients with mild asymptomatic microhematuria". Mayo Clinic Proceedings. 64 (4): 409–414.
^Burkle-Elizondo, Gerardo; Valdéz-Cepeda, Ricardo David (2006). "Fractal analysis of Mesoamerican pyramids". Nonlinear Dynamics, Psychology, and Life Sciences. 10 (1): 105–122.
^Brown, Clifford T.; Witschey, Walter R. T.; Liebovitch, Larry S. (2005). "The Broken Past: Fractals in Archaeology". Journal of Archaeological Method and Theory. 12: 37–78.
Jones, Jesse; Fractals for the Macintosh, Waite Group Press, Corte Madera, CA, 1993.
Lauwerier, Hans; Fractals: Endlessly Repeated Geometrical Figures, Translated by Sophia Gill-Hoffstadt, Princeton University Press, Princeton NJ, 1991.
ISBN0-691-02445-6 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.
Lesmoir-Gordon, Nigel; The Colours of Infinity: The Beauty, The Power and the Sense of Fractals. 2004.
ISBN1-904555-05-5 (The book comes with a related DVD of the
Arthur C. Clarke documentary introduction to the fractal concept and the