In
mathematics, the 'Hausdorff dimension' (also known as the 'Hausdorff-Besicovitch dimension') is an
extended non-negative
real number associated to any
metric space. It was introduced in 1918 by the
mathematician Felix Hausdorff. Many of the technical developments used to compute the Hausdorff dimension for highly irregular sets were obtained by
Abram Samoilovitch Besicovitch.
Less frequently it is also called the ''capacity dimension'' or ''
fractal dimension'' (the latter is somewhat misleading as there are many other choices of definition).
Informal discussion
Intuitively, the dimension of a set (for example, a
subset of
Euclidean space) is the number of independent parameters needed to describe a point in the set. One mathematical concept which closely models this naive idea is that of
topological dimension of a set. For example a point in the plane is described by two independent parameters (the
Cartesian coordinates of the point), so in this sense, the plane is two-dimensional. As one would expect, topological dimension is always a
natural number.
However, topological dimension behaves in quite unexpected ways on certain highly irregular sets such as
fractals. For example, the
Cantor set has topological dimension zero, but in some sense it behaves as a higher dimensional space. Hausdorff dimension gives another way to define dimension, which takes the metric into account.
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Sierpinski triangle. A space having fractional dimension ln 3 / ln 2, or log
2 3, which is approximately 1.58
To define the Hausdorff dimension for ''X'' as non-negative
real number (that is a number in the half-closed infinite interval [0, ∞), we first consider the number N(''r'') of
balls of radius at most ''r'' required to cover ''X'' completely. Clearly, as ''r'' gets smaller N(''r'') gets larger. Very roughly, if N(''r'') grows in the same way as 1/''r''
''d'' as ''r'' is squeezed down towards zero, then we say ''X'' has dimension ''d''. In fact the rigorous definition of Hausdorff dimension is somewhat roundabout, since it first defines an entire family of covering measures for ''X''. It turns out that Hausdorff dimension refines the concept of topological dimension and also relates it to other properties of the space such as area or volume.
There are various closely related notions of possibly fractional dimension. For example
box-counting dimension, generalizes the idea of counting the squares of
graph paper in which a point of ''X'' can be found, as the size of the squares is made smaller and smaller. (The box-counting dimension is also called the
Minkowski-Bouligand dimension).
These notions (topological dimension, Hausdorff dimension, Minkowski-Bouligand dimension) all give the same value for many shapes. They give different values for some highly irregular curves. Those curves were originally called "
monster curves" because they seemed so bizarre and non-intuitive at the time. But
Benoît Mandelbrot says that most shapes found in nature are best modeled by such irregular curves.
Formal definition
The Hausdorff dimension is one measure of the
dimension of an arbitrary
metric space; this includes complicated spaces such as
fractals.
Suppose (''X'',''d'') is a metric space. As mentioned in the introduction, we are interested in counting the number of balls of some radius necessary to cover a given set. It is possible to try to do this directly for many sets (leading to so-called box counting dimension), but Hausdorff's insight was to approach the problem indirectly using the theory of
measure developed earlier in the century by
Henri Lebesgue and
Constantin Caratheodory. In order to deal with the technical details of this approach, Hausdorff defined an entire family of measures on subsets of ''X'', one for each possible dimension ''s'' ∈
[0, ∞). For example, if ''X''= 'R'³, this construction assigns an ''s''-dimensional measure ''H''
''s'' to all subsets of 'R'³ including the unit segment along the ''x''-axis [0,1] × {0} × {0}, the unit square on the ''x''-''y'' plane [0,1] × [0,1] × {0} and the unit cube [0,1] × [0,1] × [0,1]. For ''s'' = 2, one would expect
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The above example suggests that we can define a set ''A'' to have Hausdorff dimension ''s'' if its ''s''-dimensional Hausdorff measure is positive and finite; in fact we have to modify this slightly. The Hausdorff dimension of ''A'' is the cutoff value ''s'' where below ''s'' the ''s''-dimensional Hausdorff measure is ∞ and above ''s'' it is 0. It is possible for the ''s'' dimensional Hausdorff measure of an ''s'' dimensional set to be 0 or ∞. For instance 'R' has dimension 1 and its 1-dimensional Hausdorff measure is infinite.
To carry this construction of this measure, we use a theory of measure which is appropriate for metric spaces. Define a family of
metric outer measures on ''X'' using the ''Method'' II construction of outer measures due to Munroe and described in the article
outer measure. Let ''C'' be the class of all subsets of ''X''; for each positive
real number ''s'', let ''p''
''s'' be the function ''A'' → diam(''A'')
''s'' on ''C''. The ''Hausdorff outer measure'' of dimension ''s'', denoted ''H''
''s'' is the outer measure corresponding to the function ''p''
''s'' on ''C''.
Thus, for any subset ''E'' of ''X''
:
where the
infimum is taken over sequences {''A''
''i''}
''i'' which cover ''E'' by sets each with diameter ≤ δ. This quantity is non-decreasing as
The ''s''-dimensional ''Hausdorff outer measure'' is defined as
:
We can succinctly (though not in a very useful way) describe the value ''H''
''s''(''E'') as the
infimum of all ''h'' > 0 such that for all δ > 0, ''E'' can be covered by
countably many closed sets of diameter ≤ δ; and the sum of the ''s''-th powers of these diameters is less than or equal to ''h''.
The function ''s'' → ''H''
''s''(''E'') is non-increasing.
In fact, it turns out that for all values of ''s'', except possibly one ''H''
''s''(''E'') is either 0 or ∞. We say ''E'' has positive finite Hausdorff dimension if, and only if, there is a real number 0<''d''< ∞ such that if ''s'' < ''d'' then ''H''
''s''(''E'') = ∞ and if ''s'' > ''d'', then ''H''
''s''(''E'') = 0. If
''H''
''s''(''E'')=0 for all positive ''s'', then ''E'' has Hausdorff dimension 0. Finally, if ''H''
''s''(''E'')=∞ for all positive ''s'', then ''E'' has Hausdorff dimension ∞. In other words,
:
It is clear from the definition that any metric space has been assigned a dimension in the range [0,∞]. It is also easy to check that Hausdorff dimension is a
bi-Lipschitz invariant of metric spaces (see below).
Results
The Hausdorff outer measure ''H''
''s'' is defined for all subsets of ''X''. However, we can in general assert additivity properties, that is
:
for disjoint ''A'', ''B'', only when ''A'' and ''B'' satisfy some additional condition, such as both being
Borel sets (or more generally, that they are both measurable sets). From the perspective of assigning measure and dimension to sets with unusual metric properties such as fractals, however, this is not a restriction.
'Theorem'. ''H''
''s'' is a metric outer measure. Thus all Borel subsets of ''X'' are measurable and ''H''
''s'' is a countably additive measure on the σ-algebra of Borel sets.
Clearly, if (''X'', ''d'') and (''Y'', ''e'') are
isomorphic metric spaces, then the corresponding Hausdorff measure spaces are also isomorphic. It is more useful to note however that Hausdorff measure even behaves well under certain bounded modifications of the underlying metric. Hausdorff measure is a
Lipschitz invariant in the following sense: If ''d'' and ''d''
1 are metrics on ''X'' such that for some ''0< C < ∞'' and all ''x'', ''y'' in ''X'',
:
then the corresponding Hausdorff measures ''H''
s, ''H''
1''s'' satisfy
:
for any Borel set ''E''.
Note that if ''m'' is a positive integer, the ''m'' dimensional Hausdorff measure of 'R'
n is a rescaling of usual ''m''-dimensional Lebesgue measure λ
''m'' which is normalized so that the Lebesgue measure of the ''m''-dimensional unit cube [0,1]
''m'' is 1. In fact, for any Borel set ''E'',
:
'Remark'. Some authors adopt a slightly different definition of Hausdorff measure than the one chosen here, the difference being that it is normalized in such a way that Hausdorff ''m''-dimensional measure in the case of Euclidean space coincides exactly with the Lebesgue measure λ.
See the Federer reference below for additional material on other fractal measures.
Examples
★ The
Euclidean space 'R'
''n'' has Hausdorff dimension ''n''.
★ The circle S
1 has Hausdorff dimension 1.
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Countable sets have Hausdorff dimension 0.
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Fractals often are spaces whose Hausdorff dimension strictly exceeds the
topological dimension. For example, the
Cantor set (a zero-dimensional topological space) is a union of two copies of itself, each copy shrunk by a factor 1/3; this fact can be used to prove that its Hausdorff dimension is
which is approximately
(see
natural logarithm). The
Sierpinski triangle is a union of three copies of itself, each copy shrunk by a factor of 1/2; this yields a Hausdorff dimension of
, which is approximately
.
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Spacefilling curves like the
Peano and the
Sierpiński curve by definition have Hausdorff dimension 2.
★ The trajectory of
Brownian motion in dimension 2 and above has Hausdorff dimension 2
almost surely.
★ The Hausdorff dimension of many coastlines have been measured, partly due to an early paper by
Benoit Mandelbrot entitled ''
How Long Is the Coast of Britain? Statistical Self-Similarity and Fractional Dimension''. The results vary from 1.02 for the coastline of
South Africa to 1.25 for the west coast of
Great Britain.
Hausdorff dimension and topological dimension
Let ''X'' be an arbitrary
separable metric space. There is a notion of
topological dimension for ''X'' which is defined recursively. It is always an integer (or +∞) and is denoted dim
top(''X'').
'Theorem'. Suppose ''X'' is non-empty. Then
:
Moreover
:
where ''Y'' ranges over metric spaces
homeomorphic to ''X''. In other words, ''X'' and ''Y'' have the same underlying set of points and the metric ''d''
''Y'' of ''Y'' is topologically equivalent to ''d''
''X''.
These results were originally established by
Edward Szpilrajn (1907-1976). The treatment in Chapter VIII of the Hurewicz and Wallman reference is particularly recommended.
Self-similar sets
Many sets defined by a self-similarity condition have dimensions which can be determined explicitly. Roughly, a set ''E'' is self-similar if it is the fixed point of a set-valued transformation ψ, that is ψ(''E'') = ''E'', although the exact definition is given below. The following is Theorem 8.3 of the Falconer reference below:
'Theorem'. Suppose
:
are
contractive mappings on 'R'
''n'' with contraction constant ''r''
''j'' < 1. Then there is a unique ''non-empty'' compact set ''A'' such that
:
This follows from
Banach's
contractive mapping fixed point theorem applied to the complete metric space of non-empty compact subsets of 'R'
''n'' with the
Hausdorff distance.
To determine the dimension of the self-similar set ''A'' (in certain cases), we need a technical condition called the ''open set condition'' on the sequence of contractions ψ
''i'' which is stated as follows: There is a relatively compact open set ''V'' such that
:
where the sets in union on the left are pairwise
disjoint.
'Theorem'. Suppose the open set condition holds and each ψ
''i'' is a similitude, that is a composition of an
isometry and a
dilation around some point. Then the unique fixed point of ψ is a set whose Hausdorff dimension is ''s'' where ''s'' is the unique solution of
:
Note that the contraction coefficient of a similitude is the magnitude of the dilation.
We can use this theorem to compute the Hausdorff dimension of the Sierpinski triangle (or sometimes called Sierpinski gasket). Consider three
non-collinear points ''a''
1, ''a''
2, ''a''
3 in the plane 'R'² and let ψ
''i'' be the dilation of ratio 1/2 around ''a''
''i''. The unique non-empty fixed point of the corresponding mapping ψ is a Sierpinski gasket and the dimension ''s'' is the unique solution of
:
Taking natural logarithms of both sides of the above equation, we can solve for ''s'', that is:
:
The Sierpinski gasket is self-similar. In general a set ''E'' which is a fixed point of a mapping
:
is self-similar if and only if the intersections
:
where ''s'' is the Hausdorff dimension of ''E''. This is clear in the case of the Sierpinski gasket (the intersections are just points), but is also true more generally:
'Theorem'. Under the same conditions as the previous theorem, the unique fixed point of ψ is self-similar.
See also
★
List of fractals by Hausdorff dimension, some examples of deterministic fractals, random and natural fractals
Historical references
★ A. S. Besicovitch, ''On Linear Sets of Points of Fractional Dimensions'',
Mathematische Annalen '101' (1929).
★ A. S. Besicovitch and H. D. Ursell, ''Sets of Fractional Dimensions'', Journal of the London Mathematical Society, v12 (1937). Several selections from this volume are reprinted in ''Classics on Fractals'',ed. Gerald A. Edgar, Addison-Wesley (1993) ISBN 0-201-58701-7 See chapters 9,10,11.
★ F. Hausdorff, ''Dimension und äußeres Maß'', Mathematische Annalen '79'(1–2) (March 1919) pp. 157–179.
References
★ M. Maurice Dodson and Simon Kristensen,
''Hausdorff Dimension and Diophantine Approximation'' (June 12, 2003).
★ L. Evans and R. Gariepy, ''Measure Theory and Fine Properties of Functions'', CRC Press, 1992
★ K. J. Falconer, ''The Geometry of Fractal Sets'', Cambridge University Press, 1985
★ H. Federer, ''Geometric Measure Theory'', Springer-Verlag, 1969.
★
W. Hurewicz and H. Wallman, ''Dimension Theory'', Princeton University Press, 1948.
★ Frank Morgan, ''Geometric Measure Theory'', Academic Press, 1988. Good introductory presentation with lots of illustrations.
★
E. Szpilrajn, ''La dimension et la mesure'', Fundamenta Mathematica 28, 1937, pp 81-89.