List of fractals by Hausdorff dimension

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According to Benoit Mandelbrot, "A fractal is by definition a set for which the Hausdorff-Besicovitch dimension strictly exceeds the topological dimension." [1] Presented here is a list of fractals, ordered by increasing Hausdorff dimension, to illustrate what it means for a fractal to have a low or a high dimension.

Contents

Deterministic fractals

Hausdorff dimension
(exact value)
Hausdorff dimension
(approx.)
NameIllustrationRemarks
Calculated0.538 Feigenbaum attractor Feigenbaum attractor.png The Feigenbaum attractor (see between arrows) is the set of points generated by successive iterations of the logistic function for the critical parameter value , where the period doubling is infinite. This dimension is the same for any differentiable and unimodal function. [2]
0.6309 Cantor set Cantor set in seven iterations.svg Built by removing the central third at each iteration. Nowhere dense and not a countable set.
0<D<11D generalized symmetric Cantor set Generalized cantor set.png Built by removing the central interval of length from each remaining interval of length at the nth iteration. produces the usual middle-third Cantor set. Varying between 0 and 1 yields any fractal dimension . [3]
0.6942(1/4, 1/2) asymmetric Cantor set AsymmCantor.png Built by removing the second quarter at each iteration. [4]

(golden ratio).

0.69897 Real numbers whose base 10 digits are even Even digits.png Similar to the Cantor set. [5]
0.88137Spectrum of Fibonacci HamiltonianThe study of the spectrum of the Fibonacci Hamiltonian proves upper and lower bounds for its fractal dimension in the large coupling regime. These bounds show that the spectrum converges to an explicit constant. [6] [ page needed ]
1 Smith–Volterra–Cantor set Smith-Volterra-Cantor set.svg Built by removing the central interval of length from each remaining interval at the nth iteration. Nowhere dense but has a Lebesgue measure of 1/2.
1 Takagi or Blancmange curve Takagi curve.png Defined on the unit interval by , where is the triangle wave function. Not a fractal under Mandelbrot's definition, because its topological dimension is also . [7] Special case of the Takahi-Landsberg curve: with . The Hausdorff dimension equals for in . (Hunt cited by Mandelbrot [8] ).
Calculated1.0812 Julia set z² + 1/4 Julia z2+0,25.png Julia set of f(z) = z2 + 1/4. [9]
Solution s of 1.0933Boundary of the Rauzy fractal Rauzy fractal.png Fractal representation introduced by G.Rauzy of the dynamics associated to the Tribonacci morphism: , and . [10] [ page needed ] [11] is one of the conjugated roots of .
1.12915contour of the Gosper island Gosper Island 4.svg Term used by Mandelbrot (1977). [12] The Gosper island is the limit of the Gosper curve.
Measured (box counting)1.2Dendrite Julia set Dendrite julia.png Julia set of f(z) = z2 + i.
1.2083 Fibonacci word fractal 60° Fibo 60deg F18.png Build from the Fibonacci word. See also the standard Fibonacci word fractal.

(golden ratio).

1.2108Boundary of the tame twindragon TameTwindragontile.png One of the six 2-rep-tiles in the plane (can be tiled by two copies of itself, of equal size). [13] [14]
1.26 Hénon map Henon.jpg The canonical Hénon map (with parameters a = 1.4 and b = 0.3) has Hausdorff dimension 1.261 ± 0.003. Different parameters yield different dimension values.
1.2619 Triflake Triflake.png Three anti-snowflakes arranged in a way that a koch-snowflake forms in between the anti-snowflakes.
1.2619 Koch curve Koch curve.svg 3 Koch curves form the Koch snowflake or the anti-snowflake.
1.2619boundary of Terdragon curve Terdragon boundary.png L-system: same as dragon curve with angle = 30°. The Fudgeflake is based on 3 initial segments placed in a triangle.
1.26192D Cantor dust Carre cantor.gif Cantor set in 2 dimensions.
1.26192D L-system branch Onetwosix.png L-Systems branching pattern having 4 new pieces scaled by 1/3. Generating the pattern using statistical instead of exact self-similarity yields the same fractal dimension.
Calculated1.2683 Julia set z2  1 Julia z2-1.png Julia set of f(z) = z2 - 1. [9]
1.3057 Apollonian gasket Apollonian gasket.svg Starting with 3 tangent circles, repeatedly packing new circles into the complementary interstices. Also the limit set generated by reflections in 4 mutually tangent circles. See [9]
1.3285 circles inversion fractal Cicle inversion.svg The limit set generated by iterated inversions with respect to 5 mutually tangent circles (in red). Also an Apollonian packing. See [15]
1.36521 [16] Quadratic von Koch island using the type 1 curve as generator Karperienflakeani2.gif Also known as the Minkowski Sausage
Calculated1.3934 Douady rabbit Douady rabbit.png Julia set of f(z) = -0.123 + 0.745i [9]
1.4649 Vicsek fractal Box fractal.svg Built by exchanging iteratively each square by a cross of 5 squares.
1.4649 Quadratic von Koch curve (type 1) Quadratic Koch 2.svg One can recognize the pattern of the Vicsek fractal (above).
1.4961Quadric cross Quadriccross.gif
The quadric cross is made by scaling the 3-segment generator unit by 5 then adding 3 full scaled units, one to each original segment, plus a third of a scaled unit (blue) to increase the length of the pedestal of the starting 3-segment unit (purple). Q Cross Fractal Generator.jpg
The quadric cross is made by scaling the 3-segment generator unit by 5 then adding 3 full scaled units, one to each original segment, plus a third of a scaled unit (blue) to increase the length of the pedestal of the starting 3-segment unit (purple).
Built by replacing each end segment with a cross segment scaled by a factor of 51/2, consisting of 3 1/3 new segments, as illustrated in the inset.

Images generated with Fractal Generator for ImageJ.

1.5000a Weierstrass function: Weierstrass functionAMD.png The Hausdorff dimension of the graph of the Weierstrass function defined by with and is . [17] [18]
1.5000 Quadratic von Koch curve (type 2) Quadratic Koch.svg Also called "Minkowski sausage".
1.5236Boundary of the Dragon curve Boundary dragon curve.png cf. Chang & Zhang. [19] [14]
1.5236Boundary of the twindragon curve Twindragontile.png Can be built with two dragon curves. One of the six 2-rep-tiles in the plane (can be tiled by two copies of itself, of equal size). [13]
1.58503-branches tree Arbre 3 branches.png Arbre 3 branches2.png Each branch carries 3 branches (here 90° and 60°). The fractal dimension of the entire tree is the fractal dimension of the terminal branches. NB: the 2-branches tree has a fractal dimension of only 1.
1.5850 Sierpinski triangle Sierpinski8.svg Also the limiting shape of Pascal's triangle modulo 2.
1.5850 Sierpiński arrowhead curve PfeilspitzenFraktal.PNG Same limit as the triangle (above) but built with a one-dimensional curve.
1.5850Boundary of the T-square fractal T-Square fractal (evolution).png The dimension of the fractal itself (not the boundary) is
1.61803a golden dragon Phi glito.png Built from two similarities of ratios and , with . Its dimension equals because .

(golden ratio).

1.6309 Pascal triangle modulo 3 Pascal triangle modulo 3.png For a triangle modulo k, if k is prime, the fractal dimension is (cf. Stephen Wolfram [20] ).
1.6309 Sierpinski Hexagon Sierpinski hexagon 4th Iteration.svg Built in the manner of the Sierpinski carpet, on an hexagonal grid, with 6 similitudes of ratio 1/3. The Koch snowflake is present at all scales.
1.6379 Fibonacci word fractal Fibonacci fractal F23 steps.png Fractal based on the Fibonacci word (or Rabbit sequence) Sloane A005614. Illustration : Fractal curve after 23 steps (F23 = 28657 segments). [21]

(golden ratio).

Solution of 1.6402Attractor of IFS with 3 similarities of ratios 1/3, 1/2 and 2/3 IFS3sim3ratios.png Generalization : Providing the open set condition holds, the attractor of an iterated function system consisting of similarities of ratios , has Hausdorff dimension , solution of the equation coinciding with the iteration function of the Euclidean contraction factor: . [5]
1.666732-segment quadric fractal (1/8 scaling rule) 8 scale fractal.png see also: File:32 Segment One Eighth Scale Quadric Fractal.jpg
Generator for 32 segment 1/8 scale quadric fractal. 32SegmentSmall.jpg
Generator for 32 segment 1/8 scale quadric fractal.
Built by scaling the 32 segment generator (see inset) by 1/8 for each iteration, and replacing each segment of the previous structure with a scaled copy of the entire generator. The structure shown is made of 4 generator units and is iterated 3 times. The fractal dimension for the theoretical structure is log 32/log 8 = 1.6667. Images generated with Fractal Generator for ImageJ.
1.6826 Pascal triangle modulo 5 Pascal triangle modulo 5.png For a triangle modulo k, if k is prime, the fractal dimension is (cf. Stephen Wolfram [20] ).
Measured (box-counting)1.7 Ikeda map attractor Ikeda map a=1 b=0.9 k=0.4 p=6.jpg For parameters a=1, b=0.9, k=0.4 and p=6 in the Ikeda map . It derives from a model of the plane-wave interactivity field in an optical ring laser. Different parameters yield different values. [22]
1.699050 segment quadric fractal (1/10 scaling rule) 50seg.tif Built by scaling the 50 segment generator (see inset) by 1/10 for each iteration, and replacing each segment of the previous structure with a scaled copy of the entire generator. The structure shown is made of 4 generator units and is iterated 3 times. The fractal dimension for the theoretical structure is log 50/log 10 = 1.6990. Images generated with Fractal Generator for ImageJ [23] .
Generator for 50 Segment Fractal. 50SegmentSmall.jpg
Generator for 50 Segment Fractal.
1.7227 Pinwheel fractal Pinwheel fractal.png Built with Conway's Pinwheel tile.
1.7712 Sphinx fractal Sphinx rep-tile fractal.gif Built with the Sphinx hexiamond tiling, removing two of the nine sub-sphinxes. [24]
1.7712 Hexaflake HexaFlake 5th Iteration Center.svg Built by exchanging iteratively each hexagon by a flake of 7 hexagons. Its boundary is the von Koch flake and contains an infinity of Koch snowflakes (black or white).
1.7712Fractal H-I de Rivera Fractal H-I de Rivera.jpg Starting from a unit square dividing its dimensions into three equal parts to form nine self-similar squares with the first square, two middle squares (the one that is above and the one below the central square) are removed in each of the seven squares not eliminated the process is repeated, so it continues indefinitely.
1.7848 Von Koch curve 85° Koch Curve 85degrees.png Generalizing the von Koch curve with an angle a chosen between 0 and 90°. The fractal dimension is then .
1.8272A self-affine fractal set Self-affine set.png Build iteratively from a array on a square, with . Its Hausdorff dimension equals [5] with and is the number of elements in the th column. The box-counting dimension yields a different formula, therefore, a different value. Unlike self-similar sets, the Hausdorff dimension of self-affine sets depends on the position of the iterated elements and there is no formula, so far, for the general case.
1.8617 Pentaflake Pentaflake-C 3rd Iteration Blue.svg Built by exchanging iteratively each pentagon by a flake of 6 pentagons.

(golden ratio).

solution of 1.8687Monkeys tree Monkeytree.svg This curve appeared in Benoit Mandelbrot's "Fractal geometry of Nature" (1983). It is based on 6 similarities of ratio and 5 similarities of ratio . [25]
1.8928 Sierpinski carpet Sierpinski carpet 6.png Each face of the Menger sponge is a Sierpinski carpet, as is the bottom surface of the 3D quadratic Koch surface (type 1).
1.89283D Cantor dust Cantor3D3.png Cantor set in 3 dimensions.
1.8928Cartesian product of the von Koch curve and the Cantor set Koch Cantor cartesian product.png Generalization : Let F×G be the cartesian product of two fractals sets F and G. Then . [5] See also the 2D Cantor dust and the Cantor cube.
where 1.9340Boundary of the Lévy C curve LevyFractal.png Estimated by Duvall and Keesling (1999). The curve itself has a fractal dimension of 2.
2 Penrose tiling Pen0305c.gif See Ramachandrarao, Sinha & Sanyal. [26]
2Boundary of the Mandelbrot set Boundary mandelbrot set.png The boundary and the set itself have the same Hausdorff dimension. [27]
2 Julia set Juliadim2.png For determined values of c (including c belonging to the boundary of the Mandelbrot set), the Julia set has a dimension of 2. [27]
2 Sierpiński curve Sierpinski-Curve-3.png Every space-filling curve filling the plane has a Hausdorff dimension of 2.
2 Hilbert curve Hilbert curve 3.svg
2 Peano curve Peano curve.png And a family of curves built in a similar way, such as the Wunderlich curves.
2 Moore curve Moore-curve-stages-1-through-4.svg Can be extended in 3 dimensions.
2 Lebesgue curve or z-order curve Z-order curve.png Unlike the previous ones this space-filling curve is differentiable almost everywhere. Another type can be defined in 2D. Like the Hilbert Curve it can be extended in 3D. [28]
2 Dragon curve Courbe du dragon.png And its boundary has a fractal dimension of 1.5236270862. [29]
2 Terdragon curve Terdragon curve.png L-system: F  F + F  F, angle = 120°.
2 Gosper curve Gosper curve 3.svg Its boundary is the Gosper island.
Solution of 2Curve filling the Koch snowflake Mandeltree.svg Proposed by Mandelbrot in 1982, [30] it fills the Koch snowflake. It is based on 7 similarities of ratio 1/3 and 6 similarities of ratio .
2 Sierpiński tetrahedron Tetraedre Sierpinski.png Each tetrahedron is replaced by 4 tetrahedra.
2 H-fractal H fractal2.png Also the Mandelbrot tree which has a similar pattern.
2 Pythagoras tree (fractal) PythagorasTree.png Every square generates two squares with a reduction ratio of .
2 2D Greek cross fractal Greek cross fractal stage 4.svg Each segment is replaced by a cross formed by 4 segments.
Measured2.01 ±0.01 Rössler attractor Roessler attractor.png The fractal dimension of the Rössler attractor is slightly above 2. For a=0.1, b=0.1 and c=14 it has been estimated between 2.01 and 2.02. [31]
Measured2.06 ±0.01 Lorenz attractor Lorenz attractor.png For parameters ,=16 and . See McGuinness (1983) [32]
2<D<2.3Pyramid surface Pyramid surface fractal.png Each triangle is replaced by 6 triangles, of which 4 identical triangles form a diamond based pyramid and the remaining two remain flat with lengths and relative to the pyramid triangles. The dimension is a parameter, self-intersection occurs for values greater than 2.3. [33]
2.3219Fractal pyramid Fractal pyramid.jpg Each square pyramid is replaced by 5 half-size square pyramids. (Different from the Sierpinski tetrahedron, which replaces each triangular pyramid with 4 half-size triangular pyramids).
2.3296 Dodecahedron fractal Dodecaedron fractal.jpg Each dodecahedron is replaced by 20 dodecahedra.

(golden ratio).

2.3347 3D quadratic Koch surface (type 1) Koch quadratic 3d fractal.svg Extension in 3D of the quadratic Koch curve (type 1). The illustration shows the first (blue block), second (plus green blocks), third (plus yellow blocks) and fourth (plus clear blocks) iterations.
2.4739 Apollonian sphere packing Apollonian spheres2.png The interstice left by the Apollonian spheres. Apollonian gasket in 3D. Dimension calculated by M. Borkovec, W. De Paris, and R. Peikert. [34]
2.50 3D quadratic Koch surface (type 2) Quadratic Koch 3D (type2 stage2).png Extension in 3D of the quadratic Koch curve (type 2). The illustration shows the second iteration.
2.529 Jerusalem cube Jerusalem Cube.jpg The iteration n is built with 8 cubes of iteration n-1 (at the corners) and 12 cubes of iteration n-2 (linking the corners). The contraction ratio is .
2.5819 Icosahedron fractal Icosaedron fractal.jpg Each icosahedron is replaced by 12 icosahedra.

(golden ratio).

2.5849 3D Greek cross fractal Greek cross 3D 1 through 4.png Each segment is replaced by a cross formed by 6 segments.
2.5849 Octahedron fractal Octaedron fractal.jpg Each octahedron is replaced by 6 octahedra.
2.5849 von Koch surface Koch surface 3.png Each equilateral triangular face is cut into 4 equal triangles.

Using the central triangle as the base, form a tetrahedron. Replace the triangular base with the tetrahedral "tent".

2.7095 Von Koch in 3D Koch Curve in Three Dimensions ("Delta" fractal).jpg Start with a 6-sided polyhedron whose faces are isosceles triangles with sides of ratio 2:2:3 . Replace each polyhedron with 3 copies of itself, 2/3 smaller. [35]
2.7268 Menger sponge Menger.png And its surface has a fractal dimension of , which is the same as that by volume.
3 3D Hilbert curve Hilbert3d-step3.png A Hilbert curve extended to 3 dimensions.
3 3D Lebesgue curve Lebesgue-3d-step3.png A Lebesgue curve extended to 3 dimensions.
3 3D Moore curve Moore3d-step3.png A Moore curve extended to 3 dimensions.
33D H-fractal 3D H-fractal.png A H-fractal extended to 3 dimensions. [36]
(conjectured)3 (to be confirmed) Mandelbulb Mandelbulb 1,024GP Overview 20211110 002 ALT.png Extension of the Mandelbrot set (power 9) in 3 dimensions [37] [ unreliable source? ]

Random and natural fractals

Hausdorff dimension
(exact value)
Hausdorff dimension
(approx.)
NameIllustrationRemarks
1/20.5Zeros of a Wiener process Wiener process set of zeros.gif The zeros of a Wiener process (Brownian motion) are a nowhere dense set of Lebesgue measure 0 with a fractal structure. [5] [38]
Solution of where and 0.7499a random Cantor set with 50% - 30% Random Cantor set.png Generalization: at each iteration, the length of the left interval is defined with a random variable , a variable percentage of the length of the original interval. Same for the right interval, with a random variable . Its Hausdorff Dimension satisfies: (where is the expected value of ). [5]
Solution of 1.144... von Koch curve with random interval Random interval koch.png The length of the middle interval is a random variable with uniform distribution on the interval (0,1/3). [5]
Measured1.22±0.02Coastline of Ireland Ireland (MODIS).jpg Values for the fractal dimension of the entire coast of Ireland were determined by McCartney, Abernethy and Gault [39] at the University of Ulster and Theoretical Physics students at Trinity College, Dublin, under the supervision of S. Hutzler. [40]

Note that there are marked differences between Ireland's ragged west coast (fractal dimension of about 1.26) and the much smoother east coast (fractal dimension 1.10) [40]

Measured1.25 Coastline of Great Britain Britain-fractal-coastline-combined.jpg Fractal dimension of the west coast of Great Britain, as measured by Lewis Fry Richardson and cited by Benoît Mandelbrot. [41]
1.2619 von Koch curve with random orientation Random orientation koch.png One introduces here an element of randomness which does not affect the dimension, by choosing, at each iteration, to place the equilateral triangle above or below the curve. [5]
1.333Boundary of Brownian motion Front mouvt brownien.png (cf. Mandelbrot, Lawler, Schramm, Werner). [42]
1.333 Polymer in 2DSimilar to the Brownian motion in 2D with non-self-intersection. [43]
1.333 Percolation front in 2D, Corrosion front in 2D Front de percolation.png Fractal dimension of the percolation-by-invasion front (accessible perimeter), at the percolation threshold (59.3%). It's also the fractal dimension of a stopped corrosion front. [43]
1.40 Clusters of clusters 2D When limited by diffusion, clusters combine progressively to a unique cluster of dimension 1.4. [43]
1.5Graph of a regular Brownian function (Wiener process) Wiener process zoom.png Graph of a function such that, for any two positive reals and , the difference of their images has the centered gaussian distribution with variance . Generalization: the fractional Brownian motion of index follows the same definition but with a variance , in that case its Hausdorff dimension . [5]
Measured1.52 Coastline of Norway Norway municipalities 2020 blank.svg See J. Feder. [44]
Measured1.55 Self-avoiding walk Polymer 2D.png Random walk in a square lattice that avoids visiting the same place twice, with a "go-back" routine for avoiding dead ends.
1.66Polymer in 3DSimilar to the Brownian motion in a cubic lattice, but without self-intersection. [43]
1.70 2D DLA Cluster Aggregation limitee par diffusion.png In 2 dimensions, clusters formed by diffusion-limited aggregation, have a fractal dimension of around 1.70. [43]
1.7381Fractal percolation with 75% probability Fractal percolation 75.png The fractal percolation model is constructed by the progressive replacement of each square by a grid in which is placed a random collection of sub-squares, each sub-square being retained with probability p. The "almost sure" Hausdorff dimension equals . [5]
7/41.752D percolation cluster hull PercolationHull.png The hull or boundary of a percolation cluster. Can also be generated by a hull-generating walk, [45] or by Schramm-Loewner Evolution.
1.8958 2D percolation cluster Amas de percolation.png In a square lattice, under the site percolation threshold (59.3%) the percolation-by-invasion cluster has a fractal dimension of 91/48. [43] [46] Beyond that threshold, the cluster is infinite and 91/48 becomes the fractal dimension of the "clearings".
2 Brownian motion Mouvt brownien2.png Or random walk. The Hausdorff dimensions equals 2 in 2D, in 3D and in all greater dimensions (K.Falconer "The geometry of fractal sets").
MeasuredAround 2Distribution of galaxy clusters Abell 1835 Hubble.jpg From the 2005 results of the Sloan Digital Sky Survey. [47]
2.5Balls of crumpled paper Paperball.png When crumpling sheets of different sizes but made of the same type of paper and with the same aspect ratio (for example, different sizes in the ISO 216 A series), then the diameter of the balls so obtained elevated to a non-integer exponent between 2 and 3 will be approximately proportional to the area of the sheets from which the balls have been made. [48] Creases will form at all size scales (see Universality (dynamical systems)).
2.50 3D DLA Cluster 3D DLA.jpg In 3 dimensions, clusters formed by diffusion-limited aggregation, have a fractal dimension of around 2.50. [43]
2.50 Lichtenberg figure PlanePair2.jpg Their appearance and growth appear to be related to the process of diffusion-limited aggregation or DLA. [43]
2.5regular Brownian surface Brownian surface.png A function , gives the height of a point such that, for two given positive increments and , then has a centered Gaussian distribution with variance = . Generalization: the fractional Brownian surface of index follows the same definition but with a variance , in that case its Hausdorff dimension . [5]
Measured2.523D percolation cluster 3Dpercolation.png In a cubic lattice, at the site percolation threshold (31.1%), the 3D percolation-by-invasion cluster has a fractal dimension of around 2.52. [46] Beyond that threshold, the cluster is infinite.
Measured and calculated~2.7The surface of Broccoli Broccoli DSC00862.png San-Hoon Kim used a direct scanning method and a cross section analysis of a broccoli to conclude that the fractal dimension of it is ~2.7. [49]
Measured~2.8Surface of human brain Cerebellum NIH.png Measured with segmented three-dimensional high-resolution magnetic resonance images [50]
Measured and calculated~2.8 Cauliflower Blumenkohl-1.jpg San-Hoon Kim used a direct scanning method and a mathematical analysis of the cross section of a cauliflower to conclude that the fractal dimension of it is ~2.8. [49]
2.97Lung surface Thorax Lung 3d (2).jpg The alveoli of a lung form a fractal surface close to 3. [43]
Calculated Multiplicative cascade 3fractals2.jpg This is an example of a multifractal distribution. However, by choosing its parameters in a particular way we can force the distribution to become a monofractal. [51]

See also

Notes and references

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  2. Aurell, Erik (May 1987). "On the metric properties of the Feigenbaum attractor". Journal of Statistical Physics. 47 (3–4): 439–458. Bibcode:1987JSP....47..439A. doi:10.1007/BF01007519. S2CID   122213380.
  3. Cherny, A. Yu; Anitas, E.M.; Kuklin, A.I.; Balasoiu, M.; Osipov, V.A. (2010). "The scattering from generalized Cantor fractals". J. Appl. Crystallogr. 43 (4): 790–7. arXiv: 0911.2497 . doi:10.1107/S0021889810014184. S2CID   94779870.
  4. Tsang, K. Y. (1986). "Dimensionality of Strange Attractors Determined Analytically". Phys. Rev. Lett. 57 (12): 1390–1393. Bibcode:1986PhRvL..57.1390T. doi:10.1103/PhysRevLett.57.1390. PMID   10033437.
  5. 1 2 3 4 5 6 7 8 9 10 11 Falconer, Kenneth (1990–2003). Fractal Geometry: Mathematical Foundations and Applications. John Wiley & Sons, Ltd. xxv. ISBN   978-0-470-84862-3.
  6. Damanik, D.; Embree, M.; Gorodetski, A.; Tcheremchantse, S. (2008). "The Fractal Dimension of the Spectrum of the Fibonacci Hamiltonian". Commun. Math. Phys. 280 (2): 499–516. arXiv: 0705.0338 . Bibcode:2008CMaPh.280..499D. doi:10.1007/s00220-008-0451-3. S2CID   12245755.
  7. Vaz, Cristina (2019). Noções Elementares Sobre Dimensão. ISBN   9788565054867.
  8. Mandelbrot, Benoit (2002). Gaussian self-affinity and Fractals. Springer. ISBN   978-0-387-98993-8.
  9. 1 2 3 4 McMullen, Curtis T. (3 October 1997). "Hausdorff dimension and conformal dynamics III: Computation of dimension", Abel.Math.Harvard.edu. Accessed: 27 October 2018.
  10. Messaoudi, Ali. Frontième de numération complexe", matwbn.icm.edu.pl. (in French) Accessed: 27 October 2018.
  11. Lothaire, M. (2005), Applied combinatorics on words, Encyclopedia of Mathematics and its Applications, vol. 105, Cambridge University Press, p.  525, ISBN   978-0-521-84802-2, MR   2165687, Zbl   1133.68067
  12. Weisstein, Eric W. "Gosper Island". MathWorld . Retrieved 27 October 2018.
  13. 1 2 Ngai, Sirvent, Veerman, and Wang (October 2000). "On 2-Reptiles in the Plane 1999", Geometriae Dedicata, Volume 82. Accessed: 29 October 2018.
  14. 1 2 Duda, Jarek (March 2011). "The Boundary of Periodic Iterated Function Systems", Wolfram.com.
  15. Chang, Angel and Zhang, Tianrong. "On the Fractal Structure of the Boundary of Dragon Curve". Archived from the original on 14 June 2011. Retrieved 9 February 2019.{{cite web}}: CS1 maint: bot: original URL status unknown (link) pdf
  16. Mandelbrot, B. B. (1983). The Fractal Geometry of Nature, p.48. New York: W. H. Freeman. ISBN   9780716711865. Cited in: Weisstein, Eric W. "Minkowski Sausage". MathWorld . Retrieved 22 September 2019.
  17. Shen, Weixiao (2018). "Hausdorff dimension of the graphs of the classical Weierstrass functions". Mathematische Zeitschrift. 289 (1–2): 223–266. arXiv: 1505.03986 . doi:10.1007/s00209-017-1949-1. ISSN   0025-5874. S2CID   118844077.
  18. N. Zhang. The Hausdorff dimension of the graphs of fractal functions. (In Chinese). Master Thesis. Zhejiang University, 2018.
  19. Fractal dimension of the boundary of the dragon fractal
  20. 1 2 "Fractal dimension of the Pascal triangle modulo k". Archived from the original on 15 October 2012. Retrieved 2 October 2006.
  21. The Fibonacci word fractal
  22. Theiler, James (1990). "Estimating fractal dimension" (PDF). J. Opt. Soc. Am. A. 7 (6): 1055–73. Bibcode:1990JOSAA...7.1055T. doi:10.1364/JOSAA.7.001055.
  23. Fractal Generator for ImageJ Archived 20 March 2012 at the Wayback Machine .
  24. W. Trump, G. Huber, C. Knecht, R. Ziff, to be published
  25. Monkeys tree fractal curve Archived 21 September 2002 at archive.today
  26. Fractal dimension of a Penrose tiling
  27. 1 2 Shishikura, Mitsuhiro (1991). "The Hausdorff dimension of the boundary of the Mandelbrot set and Julia sets". arXiv: math/9201282 .
  28. Lebesgue curve variants
  29. Duda, Jarek (2008). "Complex base numeral systems". arXiv: 0712.1309v3 [math.DS].
  30. Seuil (1982). Penser les mathématiques. Seuil. ISBN   2-02-006061-2.
  31. Fractals and the Rössler attractor
  32. McGuinness, M.J. (1983). "The fractal dimension of the Lorenz attractor". Physics Letters. 99A (1): 5–9. Bibcode:1983PhLA...99....5M. doi:10.1016/0375-9601(83)90052-X.
  33. Lowe, Thomas (24 October 2016). "Three Variable Dimension Surfaces". ResearchGate.
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Further reading

Related Research Articles

<span class="mw-page-title-main">Fractal</span> Infinitely detailed mathematical structure

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. 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 measure theory.

<span class="mw-page-title-main">Hausdorff dimension</span> Invariant measure of fractal dimension

In mathematics, Hausdorff dimension is a measure of roughness, or more specifically, fractal dimension, that was 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.

<span class="mw-page-title-main">Self-similarity</span> Whole of an object being mathematically similar to part of itself

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.

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 is also a measure of the space-filling capacity of a pattern, and it tells how a fractal scales differently, in a fractal (non-integer) dimension.

<span class="mw-page-title-main">Self-organized criticality</span> Concept in physics

Self-organized criticality (SOC) is a property of dynamical systems that have a critical point as an attractor. Their macroscopic behavior thus displays the spatial or temporal scale-invariance characteristic of the critical point of a phase transition, but without the need to tune control parameters to a precise value, because the system, effectively, tunes itself as it evolves towards criticality.

<span class="mw-page-title-main">Topological order</span> Type of order at absolute zero

In physics, topological order is a kind of order in the zero-temperature phase of matter. Macroscopically, topological order is defined and described by robust ground state degeneracy and quantized non-Abelian geometric phases of degenerate ground states. Microscopically, topological orders correspond to patterns of long-range quantum entanglement. States with different topological orders cannot change into each other without a phase transition.

A two-dimensional electron gas (2DEG) is a scientific model in solid-state physics. It is an electron gas that is free to move in two dimensions, but tightly confined in the third. This tight confinement leads to quantized energy levels for motion in the third direction, which can then be ignored for most problems. Thus the electrons appear to be a 2D sheet embedded in a 3D world. The analogous construct of holes is called a two-dimensional hole gas (2DHG), and such systems have many useful and interesting properties.

<span class="mw-page-title-main">Coastline paradox</span> Counterintuitive observation that the coastline of a landmass does not have a well-defined 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.

<span class="mw-page-title-main">Schramm–Loewner evolution</span>

In probability theory, the Schramm–Loewner evolution with parameter κ, also known as stochastic Loewner evolution (SLEκ), is a family of random planar curves that have been proven to be the scaling limit of a variety of two-dimensional lattice models in statistical mechanics. Given a parameter κ and a domain in the complex plane U, it gives a family of random curves in U, with κ controlling how much the curve turns. There are two main variants of SLE, chordal SLE which gives a family of random curves from two fixed boundary points, and radial SLE, which gives a family of random curves from a fixed boundary point to a fixed interior point. These curves are defined to satisfy conformal invariance and a domain Markov property.

The Hurst exponent is used as a measure of long-term memory of time series. It relates to the autocorrelations of the time series, and the rate at which these decrease as the lag between pairs of values increases. Studies involving the Hurst exponent were originally developed in hydrology for the practical matter of determining optimum dam sizing for the Nile river's volatile rain and drought conditions that had been observed over a long period of time. The name "Hurst exponent", or "Hurst coefficient", derives from Harold Edwin Hurst (1880–1978), who was the lead researcher in these studies; the use of the standard notation H for the coefficient also relates to his name.

<span class="mw-page-title-main">Percolation threshold</span> Threshold of percolation theory models

The percolation threshold is a mathematical concept in percolation theory that describes the formation of long-range connectivity in random systems. Below the threshold a giant connected component does not exist; while above it, there exists a giant component of the order of system size. In engineering and coffee making, percolation represents the flow of fluids through porous media, but in the mathematics and physics worlds it generally refers to simplified lattice models of random systems or networks (graphs), and the nature of the connectivity in them. The percolation threshold is the critical value of the occupation probability p, or more generally a critical surface for a group of parameters p1, p2, ..., such that infinite connectivity (percolation) first occurs.

The Fermi–Ulam model (FUM) is a dynamical system that was introduced by Polish mathematician Stanislaw Ulam in 1961.

Daniel Amihud Lidar is the holder of the Viterbi Professorship of Engineering at the University of Southern California, where he is a professor of electrical engineering, chemistry, physics and astronomy. He is the director and co-founder of the USC Center for Quantum Information Science & Technology (CQIST) as well as scientific director of the USC-Lockheed Martin Quantum Computing Center, notable for his research on control of quantum systems and quantum information processing.

In the context of the physical and mathematical theory of percolation, a percolation transition is characterized by a set of universal critical exponents, which describe the fractal properties of the percolating medium at large scales and sufficiently close to the transition. The exponents are universal in the sense that they only depend on the type of percolation model and on the space dimension. They are expected to not depend on microscopic details such as the lattice structure, or whether site or bond percolation is considered. This article deals with the critical exponents of random percolation.

<span class="mw-page-title-main">Light front holography</span> Technique used to determine mass of hadrons

In strong interaction physics, light front holography or light front holographic QCD is an approximate version of the theory of quantum chromodynamics (QCD) which results from mapping the gauge theory of QCD to a higher-dimensional anti-de Sitter space (AdS) inspired by the AdS/CFT correspondence proposed for string theory. This procedure makes it possible to find analytic solutions in situations where strong coupling occurs, improving predictions of the masses of hadrons and their internal structure revealed by high-energy accelerator experiments. The most widely used approach to finding approximate solutions to the QCD equations, lattice QCD, has had many successful applications; however, it is a numerical approach formulated in Euclidean space rather than physical Minkowski space-time.

In condensed matter physics, an AKLT model, also known as an Affleck-Kennedy-Lieb-Tasaki model is an extension of the one-dimensional quantum Heisenberg spin model. The proposal and exact solution of this model by Ian Affleck, Elliott H. Lieb, Tom Kennedy and Hal Tasaki provided crucial insight into the physics of the spin-1 Heisenberg chain. It has also served as a useful example for such concepts as valence bond solid order, symmetry-protected topological order and matrix product state wavefunctions.

<span class="mw-page-title-main">Random sequential adsorption</span>

Random sequential adsorption (RSA) refers to a process where particles are randomly introduced in a system, and if they do not overlap any previously adsorbed particle, they adsorb and remain fixed for the rest of the process. RSA can be carried out in computer simulation, in a mathematical analysis, or in experiments. It was first studied by one-dimensional models: the attachment of pendant groups in a polymer chain by Paul Flory, and the car-parking problem by Alfréd Rényi. Other early works include those of Benjamin Widom. In two and higher dimensions many systems have been studied by computer simulation, including in 2d, disks, randomly oriented squares and rectangles, aligned squares and rectangles, various other shapes, etc.

<span class="mw-page-title-main">Amnon Aharony</span> Physicist at Ben Gurion University in Israel

Amnon Aharony is an Israeli Professor (Emeritus) of Physics in the School of Physics and Astronomy at Tel Aviv University, Israel and in the Physics Department of Ben Gurion University of the Negev, Israel. After years of research on statistical physics, his current research focuses on condensed matter theory, especially in mesoscopic physics and spintronics. He is a member of the Israel Academy of Sciences and Humanities, a Foreign Honorary Member of the American Academy of Arts and Sciences and of several other academies. He also received several prizes, including the Rothschild Prize in Physical Sciences, and the Gunnar Randers Research Prize, awarded every other year by the King of Norway.

Bernard Sapoval was a French physicist. He was known for his work in semi-conductors, and fractals.

The spectral dimension is a real-valued quantity that characterizes a spacetime geometry and topology. It characterizes a spread into space over time, e.g. a ink drop diffusing in a water glass or the evolution of a pandemic in a population. Its definition is as follow: if a phenomenon spreads as , with the time, then the spectral dimension is . The spectral dimension depends on the topology of the space, e.g., the distribution of neighbors in a population, and the diffusion rate.