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Fractales  
Bartolo  Luque
Gabor
Csordas y  
Gabor Papp
3
El  efecto  Droste
Tal vez la forma más elemental y pri-­
mitiva de recursividad sea el efecto
Droste: una imagen que contiene una
réplica en miniatura de sí misma.
El nombre proviene de una popular
marca de chocolates de los Países
Bajos que, a principios del siglo xx,
empleó este efecto en una de sus
imágenes publicitarias. En ella
aparecía una enfermera que portaba,
justamente, una caja de cacao
Droste decorada con una réplica en
miniatura de la imagen original. Así
pues, en la caja aparecía otra vez la
enfermera, la cual llevaba otra caja, y
así sucesivamente.
Diseño  publicitario
Visage of War, Salvador Dali (1940)
Geometrical  Self-­Similarity
Geometrical  Self-­Similarity
The  magnified  piece  of  an  object  is  
an  exact  copy  of  the  whole  object.
SierpinskiTriangle.exe
zoom  in
and  rescale  
Geometrical  Self-­Similarity
zoom  in
and  rescale  
Geometrical  Self-­Similarity
Cosas  raras:  el  perímetro
Koch  snowflake
n
nN 43)( ⋅=
n
nL )3/1()( =
n
nLnNnP )3/4(3)()()( ⋅==
3)0(
1)0(
==
==
nN
nL
∞→n ∞
KochCurve.exe
14
"I coined fractal from the Latin adjective
fractus. The corresponding Latin verb
frangere means "to break": to create
irregular fragments. It is therefore
sensible - and how appropriatefor our
needs! - that, in addition to "fragmented"
(as in fraction or refraction), fractus
should also mean "irregular", both
meanings being preserved in fragment."
(The Fractal Geometry of Nature)
La palabra latina fractus significa quebrado. En palabras
de Benoit Mandelbrot:
Benoit Mandelbrot (1924-2010)
The  Cantor  Set  is  the  dust  of  
points  obtained  as  the  limit  
of  this  succession  of  
segments
This  is  already  the  limit  
of  
succession  of  iterations
Más cosas raras: Curva de Peano
¿Tiene  entonces  la  curva  dimensión  1  o  dimensión  2?
¿Tiene  sentido  esta  pregunta?
Objects  in  
mirror  are  
closer  than  
they  appear.
Monsters  in
Sci-­Fi
King  Kong  (1933) Them  (1954) Godzilla  (1954)
Record:  120  m
Tarantula  (1955)
The deadly
mantis
(1957)
20
?
Ley	
  cuadrado	
  cúbica
Cuando  un  objeto  crece  sin  
cambiar  de  forma,  su  
superficie  crece  como  el  
cuadrado  de  alguna  longitud  
característica  
(por  ejemplo,  su  altura)  
mientras  que  el  volumen  
crece  como  el  cubo  de  dicha  
cantidad.
Galileo  (1564-­1642)
¿Qué  se  podemos  deducir  de  la  ley?
3
2
~)(
~)(
rrV
rrS
3
2
8~)2(
4~)2(
rrV
rrS
⋅⋅
⋅⋅
19571958
250  Hz
150  Hz
ρ
ρ
µ S
L
SL
==
211 −
∝∝ L
SL
ν
µ
ν
T
L2
1
=
Allometry  is  the  study  of  
the  relationship  between  
size  and  shape.
2−
∝ Lν
2−
∝ Lν
Dimension
Topological	
  Dimension
• Points	
  (or	
  disconnected	
  collections	
  of	
  them)	
  have	
  topological	
  
dimension	
  0.
• Lines	
  and	
  curves	
  have	
  topological	
  dimension	
  1.
• 2-­‐D	
  things	
  (think	
  filled	
  in	
  square)	
  have	
  topological	
  dimension	
  2.
• 3-­‐D	
  things	
  (a	
  solid	
  cube)	
  have	
  topological	
  dimension	
  3.
intuitive:  length,  area,  volume
rescale  by
a  factor  b
length  s
Fractal  vs.  integer  dimension
b ·s
b
2·A
area  A
intuitive:  length,  area,  volume
rescale  by
a  factor  b
length  s
b
2·A
area  A
Fractal  vs.  integer  dimension
b
1·s
D
Dimensions	
  of	
  objects
• Consider	
  objects	
  in	
  1,	
  2	
  and	
  3	
  dimensions:
D  =  1 D  =  2 D  =  3
• Reduce	
  length	
  of	
  ruler	
  by	
  factor,	
  r
r  =  1/2
N  =  2
N  =  4
N  =  8
• Quantity	
  increases	
  by	
  N	
  =	
  (1/r)D
r  =  1/2
r  =1/3
N  =  2
N  =  3
N  =  4
N  =  9
N  =  8
N  =  27
( )
( )r
N
D
/1log
log
=
( )
( )
( )
( )
1
3log
3log
2log
2log
===D
( )
( )
( )
2
3log
9log
2log
)4log(
===D
( )
( )
( )
3
3log
27log
2log
)8log(
===D
1                            1  
r N
Sierpinsky  revisited
1                             1  
r N
1/2 3
Sierpinsky  revisited
1                                    1  
r N
1/2 3
1/4 9
Sierpinsky  revisited
1                          1  
r N
1/2 3
1/4 9
1/8 27
k
0
1
2
3
r  =  2-­k
N    =  3k
Sierpinsky  revisited
N  = (1/r)D  
( )
( )r
N
D
/1log
log
=
( )
( )
( )
( )2log
3log
2log
3log
== k
k
D
Fractal  vs.  integer  dimension
585.1
)2log(
)3log(
D ≈=
“more  than  a  line  – less  than  an  area”
What’s  special  about  fractals  is  that  the  
“dimension”  is  not  necessarily  a  whole  number
“Clouds are not spheres,
mountains are not cones,
coastlines are not circles, and
bark is not smooth, nor does
lightning travel in a straight
line.”
Benoit  B.  Mandelbrot
Geometric scale invariance and fractal geometry
«Un  fractal  es  un  objeto  
matemático  cuya  
dimensión  de  Hausdorff es  
siempre  mayor  a  su  
dimensión  topológica».
Koch  island:  
scale  by
factor  b=3
length  s
length  4  s
2619.1
)3log(
)4log(
D ≈=
Fractal  vs.  integer  dimension
N(ε) =  2k where  k  is  the  iteration  
And  ε =(1/3)k
D=ln(2)/ln(3)  =  0.6309…
N(ε) =  8k where  k  is  the  iteration  
And  ε =(1/3)k
D=ln(8)/ln(3)  =  1.8927…
The  Cantor  Set  is  the  dust  of  points  
obtained  as  the  limit  of  this  succession  
of  segments
This  is  already  the  limit  of  
succession  of  iterations
N	
  =	
  (1/r)D
Self-­similarity  in  nature
Romanesco	
  –
a	
  cross	
  between	
  broccoli	
  
and	
  cauliflower
Self-­similarity  in  nature
Self-­similarity  in  nature
Fractal  concepts  characterize  
those  objects  in  which  
properly  scaled portions  are  
identical  to  the  original  
object.  Can  be  identical  in  
deterministic  or  statistical  
sense.
Self-­Similarity:  
Geometrical  and  Statistical
La  gran  ola  de  Kanagawa
Scale  Laws...  Power  Laws
α−
⋅= rBrQ )(
......... 2−
∝ Lν
Q  (r) Log  Q  (r)
r Log  r
BrrQ loglog)(log +−= α
How	
  long	
  is	
  the	
  coast	
  of	
  Britain?
Suppose	
  the	
  coast	
  of	
  Britain	
  is	
  measured	
  using	
  a	
  200	
  km	
  ruler,	
  specifying	
  that	
  
both	
  ends	
  of	
  the	
  ruler	
  must	
  touch	
  the	
  coast.	
  Now	
  cut	
  the	
  ruler	
  in	
  half	
  and	
  
repeat	
  the	
  measurement,	
  then	
  repeat	
  again:	
  
B.  B.  Mandelbrot,  Science’1967
Scale-dependent length.
Compass o ruler method:
How  Long  is  the  Coastline  of  Britain?
r  =  Length  of  Line  Segments  in  Km
Q(r)  =  N(r)  r  = Total  Length  in  Km
r r
How  Long  is  the  Coastline  of  Britain?
Richardson  1961  The  problem  of  contiguity:  An  Appendix  to  Statistics  
of  Deadly  Quarrels  General  Systems  Yearbook    6:139-­187
Log10(Total  Length  in  Km)
CIRCLE
SOUTH  AFRICAN    COAST
4.0
3.5
3.0
1.0 1.5 2.0 2.5 3.0 3.5
Log10 (Length  of  Line  Segments  in  Km)
Scaling
The  value  measured for  a  property,  
such  as  length,  surface,  or  volume,    
depends  on  the  resolution at  which  it  
is  measured.  
How  depends  is  called  the  
scaling  relationship.
How  Long  is  the  Coastline  of  Britain?
Richardson  1961  The  problem  of  contiguity:  An  Appendix  to  Statistics  
of  Deadly  Quarrels  General  Systems  Yearbook    6:139-­187
Log10(Total  Length  in  Km)
CIRCLE
SOUTH  AFRICAN    COAST
4.0
3.5
3.0
1.0 1.5 2.0 2.5 3.0 3.5
Log10 (Length  of  Line  Segments  in  Km)
25.0
)( −
∝ rrL
Statistical  Self-­Similarity
In  real  world  are  usually  not  exact  smaller  copies  of  the  
whole  object.  The  value  of  statistical  property  Q(r)  
measured  at  resolution  r,  is  proportional  to  the  value  Q(ar)  
measured  at  resolution  ar.
Q(ar)  =  kQ(r)
pdf  [Q(ar)]  =  pdf  [kQ(r)]
d
)()()(
;)(
25.025.025.025.0
25.0
rLarAaraAraL
rArL
⋅=⋅⋅=⋅⋅=⋅
⋅=
−−−−
−
Self-­Similarity Implies  a  Scaling  Relationship
Q  (r)  =  B  rb
Q  (ar)  =  k  Q(r) Q  (r)  =  B  rb
Self-­Similarity  can  be  satisfied  by  the  power  
law  scaling,  the  simplest  and  most  common  
form  of  the  scaling  relationship:
Proof:  using  the  scaling  relationship  to  evaluate  Q(r)  and  Q(ar)
Q  (r)  =  B  rb  
Q  (ar)  =  B  ab rb
if        k  =  ab then        Q  (ar)  =  k  Q  (r)
Power  Law
measurement
r Log  r
Logarithmof  
the  measuremnt
Resolution  used  to  make  
the  measurement
Logarithm  of  the  resolution  
used  to  make  the  
measurement
Such power law scaling relationships are	
  characteristic of	
  fractals. Power law
relationships are	
  found so	
  often because so	
  many things in	
  nature are	
  fractal.
Scale Laws and  Power Laws
α−
⋅= rBrQ )( BrrQ loglog)(log +−= α
Mass (Perimeter)3
Double  the  size   Octuple  Mass
Dimension  =  3
Solid  Spheres
"Euclidean  Object"
3
3
23
4
3
4
~
2
⎟
⎠
⎞
⎜
⎝
⎛
==
=
π
ππρ
π
P
RVM
RP
Crumbled  Paper  Balls
"Non-­Euclidean  Objects"
M.A.F. Gomes,  “Fractal  geometry  in  crumpled  paper  balls”
Am.J.Phys.  55,  649-­650  (1987).
R.H.Ko and  C.P.Bean,  “A  simple  experiment  that  
demonstrates  fractal  behavior”,  Phys.  Teach. 29,  78  (1991).
Crumbled  Paper  Balls
"Non-­Euclidean  Objects"
Mass (Perimeter)Dimension
log(Mass)   Dimension log(Perimeter)
L.H.F.  Silva  and  M.T.  Yamashita,  “The  dimension  of  the  pore  space  in  sponges,”  
European  Journalof  Physics  30:  135-­137,  2009  .
Por  cierto,  los  geólogos  suelen  utilizar  
este  tipo  de  idea  para  caracterizar  la  
porosidad  de  rocas  y  su  permeabilidad  
(Alexis  Mojica,  Leomar Acosta,  “La  
porosidad  de  las  rocas  y  su  naturaleza  
fractal,”  Invet.  pens.  crit.  4:  88-­93,  2006  ).
Se  recortan  muchos  cubitos  de  esponja  
de  lado  progresivamente  mayor,  por  
ejemplo, desde  1  cm  de  lado,  2  cm,  3  
cm,  hasta  donde  podamos.  Pesamos  las  
esponjas  con  una  balanza,  luego  las  
sumergimos  en  agua  y  las  volvemos  a  
pesar.  La  diferencia  de  masa  entre  la  
esponja  seca  y  la  mojada.  Dibujando  
esta  diferencia  en  función  del  lado  en  
escala  doblemente  logarítmica  se  
observará  que  la  dimensión  fractal  de  la  
esponja  es  D  =  2.95,  menor  que  3,  
resultado  de  la  existencia  de  los  poros.
Object   Set
Property   Distribution
Mean  size  o  characteristic  size
66
What  is  the  normal  
length  of  a  penis?  
67
While  results  vary  across  
studies,  the  consensus  is  that  
the  mean  human  penis  is  
approximately  12.9  – 15  cm in  
length  with  a  95%  confidence  
interval  of  (10.7  cm,  19.1  cm).
Mean
Non  -­ Fractal
More  Data
69
Fractal?
Self-similarity in geology
From:  D.  Sornette,  Critical  Phenomena  in  Natural  Sciences  (2000)
Self-similarity in geology
From:  D.  Sornette,  Critical  Phenomena  in  Natural  Sciences  (2000)
Cloud perimeters over 5
decades yield D ≈ 1.35
(Lovejoy, 1982)
Power  laws,  Pareto  distributions  and  Zipf’s  law
M.  E.  J.  Newman
WWW Nodes: WWW pages
Links: URL links
P(k)  ~  k-­ 2.1
Scale-­Free  Networks
77
?
The  Average  Depends  on  the  
Amount  of  Data  Analyzed
each  piece
The  Average  Depends  on  the  
Amount  of  Data  Analyzed
or
average  
size
number  of  pieces  
included
average  
size
number  of  pieces  
included
Contributions  to  the  mean  dominated  
by  the  number  of  smallest  sizes.  
Contributions  to  the  mean  dominated  
by  the  number  of  biggest  sizes.  
0→µ
∞→µ
Non-­Fractal
Log  avg
density  within  
radius  r
Log  radius  r
Fractal
Log  avg
density  
within  
radius  r
Log  radius  r
.5
-­1.0
-­2.0
-­1.5
.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.00
-­2.5
0
Meakin  1986  In  On  Growth  and  Form:  Fractal  and  Non-­Fractal  Patterns  in  
Physics  Ed.  Stanley  &  Ostrowsky,  Martinus  Nijoff  Pub.,  pp.  111-­135
When  the  moments,  such  as  the  mean  and  variance,  
don’t  exist,  what  should  I  measure?  The  exponent...
Fractals	
  in	
  Nature
Electrical
Discharge from
Tesla Coil
Fractals	
  in	
  Nature
Lichtenberg Figure
Created by exposing plastic rod to electron beam & injecting charge
into material. Discharged by touching earth connector to left hand end
Viscous  fingeringElectrodeposition
Diffusion-limited aggregation (DLA)
T.A.  Witten,  L.M.  Sander  1981  
Statistical scale invariance of DLA
P.  Meakin,  Fractals,  scaling  and    growth  far  from  equilibrium
Mass-­length  relation  
M1 R1
D           M2 R2
D  
Fractal
Log  avg
density  
within  
radius  r
Log  radius  r
.5
-­1.0
-­2.0
-­1.5
.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.00
-­2.5
0
Meakin  1986  In  On  Growth  and  Form:  Fractal  and  Non-­Fractal  Patterns  in  
Physics  Ed.  Stanley  &  Ostrowsky,  Martinus  Nijoff  Pub.,  pp.  111-­135
When  the  moments,  such  as  the  mean  and  variance,  
don’t  exist,  what  should  I  measure?  The  exponent...
Box-­counting
∙ Cover  the  object  by  
boxes  of  size    ∊
<    ∊ >
∙  count  non-­empty  boxes
∙  repeat  for  many    ∊
Measuring  fractal  dimension
∙ cover  the  object  by  
boxes  of  size    ∊
<∊>
∙  count  non-­empty  boxes
∙  repeat  for  many    ∊
box-­counting:  resolution-­dependent  measurement  
Measuring  fractal  dimension
∙ cover  the  object  by  
boxes  of  size    ∊
∙  count  non-­empty  boxes
∙  repeat  for  many    ∊
box-­counting:  resolution-­dependent  measurement  
∙  consider  the  number  
n  of  non-­empty  boxes
as  a  function  of  ∊
(in  the  limit  ∊→0)
Fractals and  Chaos.
Larry  S.  Liebovitch.
Fractals,  Chaos,  
Power  Laws.
Manfred  Schroeder  

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Fractales bartolo luque - curso de introduccion sistemas complejos

  • 2.
  • 3. 3 El  efecto  Droste Tal vez la forma más elemental y pri-­ mitiva de recursividad sea el efecto Droste: una imagen que contiene una réplica en miniatura de sí misma. El nombre proviene de una popular marca de chocolates de los Países Bajos que, a principios del siglo xx, empleó este efecto en una de sus imágenes publicitarias. En ella aparecía una enfermera que portaba, justamente, una caja de cacao Droste decorada con una réplica en miniatura de la imagen original. Así pues, en la caja aparecía otra vez la enfermera, la cual llevaba otra caja, y así sucesivamente.
  • 5.
  • 6.
  • 7. Visage of War, Salvador Dali (1940)
  • 8.
  • 10. Geometrical  Self-­Similarity The  magnified  piece  of  an  object  is   an  exact  copy  of  the  whole  object. SierpinskiTriangle.exe
  • 11. zoom  in and  rescale   Geometrical  Self-­Similarity
  • 12. zoom  in and  rescale   Geometrical  Self-­Similarity
  • 13. Cosas  raras:  el  perímetro Koch  snowflake n nN 43)( ⋅= n nL )3/1()( = n nLnNnP )3/4(3)()()( ⋅== 3)0( 1)0( == == nN nL ∞→n ∞ KochCurve.exe
  • 14. 14 "I coined fractal from the Latin adjective fractus. The corresponding Latin verb frangere means "to break": to create irregular fragments. It is therefore sensible - and how appropriatefor our needs! - that, in addition to "fragmented" (as in fraction or refraction), fractus should also mean "irregular", both meanings being preserved in fragment." (The Fractal Geometry of Nature) La palabra latina fractus significa quebrado. En palabras de Benoit Mandelbrot: Benoit Mandelbrot (1924-2010)
  • 15. The  Cantor  Set  is  the  dust  of   points  obtained  as  the  limit   of  this  succession  of   segments This  is  already  the  limit   of   succession  of  iterations
  • 16.
  • 17. Más cosas raras: Curva de Peano ¿Tiene  entonces  la  curva  dimensión  1  o  dimensión  2? ¿Tiene  sentido  esta  pregunta?
  • 18. Objects  in   mirror  are   closer  than   they  appear. Monsters  in Sci-­Fi
  • 19. King  Kong  (1933) Them  (1954) Godzilla  (1954) Record:  120  m Tarantula  (1955) The deadly mantis (1957)
  • 20. 20 ?
  • 21. Ley  cuadrado  cúbica Cuando  un  objeto  crece  sin   cambiar  de  forma,  su   superficie  crece  como  el   cuadrado  de  alguna  longitud   característica   (por  ejemplo,  su  altura)   mientras  que  el  volumen   crece  como  el  cubo  de  dicha   cantidad. Galileo  (1564-­1642) ¿Qué  se  podemos  deducir  de  la  ley?
  • 25. ρ ρ µ S L SL == 211 − ∝∝ L SL ν µ ν T L2 1 = Allometry  is  the  study  of   the  relationship  between   size  and  shape.
  • 26.
  • 27.
  • 30. Dimension Topological  Dimension • Points  (or  disconnected  collections  of  them)  have  topological   dimension  0. • Lines  and  curves  have  topological  dimension  1. • 2-­‐D  things  (think  filled  in  square)  have  topological  dimension  2. • 3-­‐D  things  (a  solid  cube)  have  topological  dimension  3.
  • 31. intuitive:  length,  area,  volume rescale  by a  factor  b length  s Fractal  vs.  integer  dimension b ·s b 2·A area  A
  • 32. intuitive:  length,  area,  volume rescale  by a  factor  b length  s b 2·A area  A Fractal  vs.  integer  dimension b 1·s D
  • 33. Dimensions  of  objects • Consider  objects  in  1,  2  and  3  dimensions: D  =  1 D  =  2 D  =  3 • Reduce  length  of  ruler  by  factor,  r r  =  1/2 N  =  2 N  =  4 N  =  8
  • 34. • Quantity  increases  by  N  =  (1/r)D r  =  1/2 r  =1/3 N  =  2 N  =  3 N  =  4 N  =  9 N  =  8 N  =  27 ( ) ( )r N D /1log log = ( ) ( ) ( ) ( ) 1 3log 3log 2log 2log ===D ( ) ( ) ( ) 2 3log 9log 2log )4log( ===D ( ) ( ) ( ) 3 3log 27log 2log )8log( ===D
  • 35. 1                            1   r N Sierpinsky  revisited
  • 36. 1                             1   r N 1/2 3 Sierpinsky  revisited
  • 37. 1                                    1   r N 1/2 3 1/4 9 Sierpinsky  revisited
  • 38. 1                          1   r N 1/2 3 1/4 9 1/8 27 k 0 1 2 3 r  =  2-­k N    =  3k Sierpinsky  revisited N  = (1/r)D   ( ) ( )r N D /1log log = ( ) ( ) ( ) ( )2log 3log 2log 3log == k k D
  • 39. Fractal  vs.  integer  dimension 585.1 )2log( )3log( D ≈= “more  than  a  line  – less  than  an  area” What’s  special  about  fractals  is  that  the   “dimension”  is  not  necessarily  a  whole  number
  • 40. “Clouds are not spheres, mountains are not cones, coastlines are not circles, and bark is not smooth, nor does lightning travel in a straight line.” Benoit  B.  Mandelbrot Geometric scale invariance and fractal geometry «Un  fractal  es  un  objeto   matemático  cuya   dimensión  de  Hausdorff es   siempre  mayor  a  su   dimensión  topológica».
  • 41. Koch  island:   scale  by factor  b=3 length  s length  4  s 2619.1 )3log( )4log( D ≈= Fractal  vs.  integer  dimension
  • 42. N(ε) =  2k where  k  is  the  iteration   And  ε =(1/3)k D=ln(2)/ln(3)  =  0.6309… N(ε) =  8k where  k  is  the  iteration   And  ε =(1/3)k D=ln(8)/ln(3)  =  1.8927… The  Cantor  Set  is  the  dust  of  points   obtained  as  the  limit  of  this  succession   of  segments This  is  already  the  limit  of   succession  of  iterations N  =  (1/r)D
  • 44. Romanesco  – a  cross  between  broccoli   and  cauliflower Self-­similarity  in  nature
  • 46. Fractal  concepts  characterize   those  objects  in  which   properly  scaled portions  are   identical  to  the  original   object.  Can  be  identical  in   deterministic  or  statistical   sense. Self-­Similarity:   Geometrical  and  Statistical
  • 47.
  • 48. La  gran  ola  de  Kanagawa
  • 49. Scale  Laws...  Power  Laws α− ⋅= rBrQ )( ......... 2− ∝ Lν Q  (r) Log  Q  (r) r Log  r BrrQ loglog)(log +−= α
  • 50. How  long  is  the  coast  of  Britain? Suppose  the  coast  of  Britain  is  measured  using  a  200  km  ruler,  specifying  that   both  ends  of  the  ruler  must  touch  the  coast.  Now  cut  the  ruler  in  half  and   repeat  the  measurement,  then  repeat  again:   B.  B.  Mandelbrot,  Science’1967 Scale-dependent length.
  • 51. Compass o ruler method: How  Long  is  the  Coastline  of  Britain? r  =  Length  of  Line  Segments  in  Km Q(r)  =  N(r)  r  = Total  Length  in  Km r r
  • 52. How  Long  is  the  Coastline  of  Britain? Richardson  1961  The  problem  of  contiguity:  An  Appendix  to  Statistics   of  Deadly  Quarrels  General  Systems  Yearbook    6:139-­187 Log10(Total  Length  in  Km) CIRCLE SOUTH  AFRICAN    COAST 4.0 3.5 3.0 1.0 1.5 2.0 2.5 3.0 3.5 Log10 (Length  of  Line  Segments  in  Km)
  • 53. Scaling The  value  measured for  a  property,   such  as  length,  surface,  or  volume,     depends  on  the  resolution at  which  it   is  measured.   How  depends  is  called  the   scaling  relationship.
  • 54. How  Long  is  the  Coastline  of  Britain? Richardson  1961  The  problem  of  contiguity:  An  Appendix  to  Statistics   of  Deadly  Quarrels  General  Systems  Yearbook    6:139-­187 Log10(Total  Length  in  Km) CIRCLE SOUTH  AFRICAN    COAST 4.0 3.5 3.0 1.0 1.5 2.0 2.5 3.0 3.5 Log10 (Length  of  Line  Segments  in  Km) 25.0 )( − ∝ rrL
  • 55. Statistical  Self-­Similarity In  real  world  are  usually  not  exact  smaller  copies  of  the   whole  object.  The  value  of  statistical  property  Q(r)   measured  at  resolution  r,  is  proportional  to  the  value  Q(ar)   measured  at  resolution  ar. Q(ar)  =  kQ(r) pdf  [Q(ar)]  =  pdf  [kQ(r)] d )()()( ;)( 25.025.025.025.0 25.0 rLarAaraAraL rArL ⋅=⋅⋅=⋅⋅=⋅ ⋅= −−−− −
  • 56. Self-­Similarity Implies  a  Scaling  Relationship Q  (r)  =  B  rb Q  (ar)  =  k  Q(r) Q  (r)  =  B  rb Self-­Similarity  can  be  satisfied  by  the  power   law  scaling,  the  simplest  and  most  common   form  of  the  scaling  relationship: Proof:  using  the  scaling  relationship  to  evaluate  Q(r)  and  Q(ar) Q  (r)  =  B  rb   Q  (ar)  =  B  ab rb if        k  =  ab then        Q  (ar)  =  k  Q  (r)
  • 57. Power  Law measurement r Log  r Logarithmof   the  measuremnt Resolution  used  to  make   the  measurement Logarithm  of  the  resolution   used  to  make  the   measurement Such power law scaling relationships are  characteristic of  fractals. Power law relationships are  found so  often because so  many things in  nature are  fractal. Scale Laws and  Power Laws α− ⋅= rBrQ )( BrrQ loglog)(log +−= α
  • 58. Mass (Perimeter)3 Double  the  size   Octuple  Mass Dimension  =  3 Solid  Spheres "Euclidean  Object" 3 3 23 4 3 4 ~ 2 ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ == = π ππρ π P RVM RP
  • 59. Crumbled  Paper  Balls "Non-­Euclidean  Objects" M.A.F. Gomes,  “Fractal  geometry  in  crumpled  paper  balls” Am.J.Phys.  55,  649-­650  (1987). R.H.Ko and  C.P.Bean,  “A  simple  experiment  that   demonstrates  fractal  behavior”,  Phys.  Teach. 29,  78  (1991).
  • 60. Crumbled  Paper  Balls "Non-­Euclidean  Objects" Mass (Perimeter)Dimension log(Mass)   Dimension log(Perimeter)
  • 61.
  • 62.
  • 63.
  • 64. L.H.F.  Silva  and  M.T.  Yamashita,  “The  dimension  of  the  pore  space  in  sponges,”   European  Journalof  Physics  30:  135-­137,  2009  . Por  cierto,  los  geólogos  suelen  utilizar   este  tipo  de  idea  para  caracterizar  la   porosidad  de  rocas  y  su  permeabilidad   (Alexis  Mojica,  Leomar Acosta,  “La   porosidad  de  las  rocas  y  su  naturaleza   fractal,”  Invet.  pens.  crit.  4:  88-­93,  2006  ). Se  recortan  muchos  cubitos  de  esponja   de  lado  progresivamente  mayor,  por   ejemplo, desde  1  cm  de  lado,  2  cm,  3   cm,  hasta  donde  podamos.  Pesamos  las   esponjas  con  una  balanza,  luego  las   sumergimos  en  agua  y  las  volvemos  a   pesar.  La  diferencia  de  masa  entre  la   esponja  seca  y  la  mojada.  Dibujando   esta  diferencia  en  función  del  lado  en   escala  doblemente  logarítmica  se   observará  que  la  dimensión  fractal  de  la   esponja  es  D  =  2.95,  menor  que  3,   resultado  de  la  existencia  de  los  poros.
  • 65. Object   Set Property   Distribution Mean  size  o  characteristic  size
  • 66. 66 What  is  the  normal   length  of  a  penis?  
  • 67. 67 While  results  vary  across   studies,  the  consensus  is  that   the  mean  human  penis  is   approximately  12.9  – 15  cm in   length  with  a  95%  confidence   interval  of  (10.7  cm,  19.1  cm).
  • 70.
  • 71. Self-similarity in geology From:  D.  Sornette,  Critical  Phenomena  in  Natural  Sciences  (2000)
  • 72. Self-similarity in geology From:  D.  Sornette,  Critical  Phenomena  in  Natural  Sciences  (2000)
  • 73. Cloud perimeters over 5 decades yield D ≈ 1.35 (Lovejoy, 1982)
  • 74.
  • 75. Power  laws,  Pareto  distributions  and  Zipf’s  law M.  E.  J.  Newman
  • 76. WWW Nodes: WWW pages Links: URL links P(k)  ~  k-­ 2.1 Scale-­Free  Networks
  • 77. 77 ?
  • 78. The  Average  Depends  on  the   Amount  of  Data  Analyzed each  piece
  • 79. The  Average  Depends  on  the   Amount  of  Data  Analyzed or average   size number  of  pieces   included average   size number  of  pieces   included Contributions  to  the  mean  dominated   by  the  number  of  smallest  sizes.   Contributions  to  the  mean  dominated   by  the  number  of  biggest  sizes.   0→µ ∞→µ
  • 80. Non-­Fractal Log  avg density  within   radius  r Log  radius  r
  • 81. Fractal Log  avg density   within   radius  r Log  radius  r .5 -­1.0 -­2.0 -­1.5 .5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.00 -­2.5 0 Meakin  1986  In  On  Growth  and  Form:  Fractal  and  Non-­Fractal  Patterns  in   Physics  Ed.  Stanley  &  Ostrowsky,  Martinus  Nijoff  Pub.,  pp.  111-­135 When  the  moments,  such  as  the  mean  and  variance,   don’t  exist,  what  should  I  measure?  The  exponent...
  • 83. Fractals  in  Nature Lichtenberg Figure Created by exposing plastic rod to electron beam & injecting charge into material. Discharged by touching earth connector to left hand end
  • 85. Diffusion-limited aggregation (DLA) T.A.  Witten,  L.M.  Sander  1981  
  • 86. Statistical scale invariance of DLA P.  Meakin,  Fractals,  scaling  and    growth  far  from  equilibrium
  • 87. Mass-­length  relation   M1 R1 D           M2 R2 D  
  • 88. Fractal Log  avg density   within   radius  r Log  radius  r .5 -­1.0 -­2.0 -­1.5 .5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.00 -­2.5 0 Meakin  1986  In  On  Growth  and  Form:  Fractal  and  Non-­Fractal  Patterns  in   Physics  Ed.  Stanley  &  Ostrowsky,  Martinus  Nijoff  Pub.,  pp.  111-­135 When  the  moments,  such  as  the  mean  and  variance,   don’t  exist,  what  should  I  measure?  The  exponent...
  • 89. Box-­counting ∙ Cover  the  object  by   boxes  of  size    ∊ <    ∊ > ∙  count  non-­empty  boxes ∙  repeat  for  many    ∊
  • 90. Measuring  fractal  dimension ∙ cover  the  object  by   boxes  of  size    ∊ <∊> ∙  count  non-­empty  boxes ∙  repeat  for  many    ∊ box-­counting:  resolution-­dependent  measurement  
  • 91. Measuring  fractal  dimension ∙ cover  the  object  by   boxes  of  size    ∊ ∙  count  non-­empty  boxes ∙  repeat  for  many    ∊ box-­counting:  resolution-­dependent  measurement   ∙  consider  the  number   n  of  non-­empty  boxes as  a  function  of  ∊ (in  the  limit  ∊→0)
  • 92.
  • 93. Fractals and  Chaos. Larry  S.  Liebovitch. Fractals,  Chaos,   Power  Laws. Manfred  Schroeder