Department of Mathematics Lecture Series — No. III
Prima Lectio Spring Term · MMXXVI

Fractal Geometry

A concise overview of the mathematics of roughness, recursion, and self-similar form

An Overview for Students

Prepared from first principles · Eleven sections · One coastline

§ I · Prologue

Why a new geometry was needed

For more than two millennia, geometry meant Euclid: lines, circles, polygons, and the smooth surfaces of the conic sections. Yet anyone who has looked carefully at a coastline, a fern, a mountain ridge, or the branching of a lung knows that nature does not in fact compose itself from these idealized forms. Clouds are not spheres, mountains are not cones, bark is not smooth, and lightning does not travel in straight lines.

Fractal geometry — the mathematics codified by Benoît Mandelbrot in the late twentieth century — is the language in which such phenomena become rigorously describable. It treats roughness not as deviation from order but as a kind of order in its own right: an order built on self-similarity across scales, on non-integer dimensions, and on the patient logic of iteration.

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. — Benoît Mandelbrot, The Fractal Geometry of Nature (1982)

What follows is a survey suitable for one short course — enough to orient you in the field, name its principal objects, sketch its central theorems, and indicate where its applications continue to grow.

§ II · Origins

A short genealogy

Mandelbrot did not invent fractals so much as recognize and unify a scattered set of nineteenth and early-twentieth-century "pathological" objects that mathematicians of the time had largely treated as curiosities — or as warnings against trusting intuition.

1872

Weierstrass constructs a function continuous everywhere yet differentiable nowhere — a curve so rough that classical calculus cannot describe it. Mathematicians call it "monstrous."

1883

Georg Cantor introduces the Cantor set — an uncountable set of points with zero length, the first "dust."

1904

Helge von Koch publishes his snowflake: a curve of infinite length enclosing finite area.

1915

Wacław Sierpiński describes the triangle and carpet bearing his name.

1918

Felix Hausdorff generalizes the notion of dimension to admit non-integer values — the mathematical foundation on which fractal geometry will rest.

1918

Gaston Julia & Pierre Fatou investigate the iteration of complex polynomials, discovering what we now call Julia sets — a half-century before computers can render them.

1967

Mandelbrot publishes How Long Is the Coast of Britain? in Science, exposing the deep relevance of dimension to the natural world.

1975

Mandelbrot coins the word fractal, from the Latin frāctus (broken). The field is named.

1980

The first computer rendering of the Mandelbrot set. A geometry once invisible becomes spectacular.

1988

Michael Barnsley's Fractals Everywhere systematizes the Iterated Function System and proves the Collage Theorem — fractals as data compression.

§ III · Three Pillars

The three properties that define a fractal

No single definition has achieved universal consensus — Mandelbrot himself revised his repeatedly. But three properties, taken together, capture what nearly every working mathematician means by the word.

Self-similarity

A fractal contains, at every scale of magnification, structures that resemble the whole — either exactly (deterministic), approximately, or in a statistical sense (random fractals like coastlines).

Fractional dimension

Its Hausdorff dimension strictly exceeds its topological dimension. A "curve" may have dimension 1.26; a "surface" may fill space with dimension 2.7. This is the precise meaning of roughness.

Recursive construction

A fractal is most naturally described by a rule applied repeatedly — an algorithm, an iterated map, or an L-system — rather than by a closed-form equation in the Euclidean tradition.

A working definition A fractal is a set whose detail does not disappear under magnification, and whose Hausdorff dimension exceeds its topological dimension. Equivalently: a fractal is what you get when you take a simple rule and apply it to itself, forever.
§ IV · Dimension

How can a curve have dimension 1.26?

The decisive conceptual leap in fractal geometry is the recognition that dimension need not be a whole number. To see why, ask a simple question: if you scale a line segment by a factor of 3, how many copies of the original fit inside? Three. If you scale a square by 3, how many copies fit? Nine, that is, 3². If you scale a cube by 3? Twenty-seven, or 3³. In each case the exponent is the dimension.

This suggests a definition: for a self-similar object made of N copies of itself, each scaled by factor r, the similarity dimension is

D = log(N) / log(1/r) Similarity Dimension — for strictly self-similar sets

Apply this to the Koch curve. Each iteration replaces a segment with four segments, each one-third the original length. So N = 4 and r = 1/3, giving D = log 4 / log 3 ≈ 1.2619… The Koch curve is more than a line but less than a plane. It lives in the gap that classical geometry insisted did not exist.

IV.1 Hausdorff and box-counting dimensions

For sets that are not exactly self-similar — most natural fractals — we need finer tools. The Hausdorff dimension measures how the minimum covering of a set by small balls scales with the radius. The box-counting dimension (or Minkowski–Bouligand dimension) is more practical: cover the set with a grid of boxes of side ε, count how many N(ε) contain part of the set, and compute

Dbox = limε→0 log N(ε) / log(1/ε) Box-Counting Dimension — operationally measurable

For well-behaved fractals these dimensions agree. The British coastline, measured this way, has a fractal dimension of roughly 1.25; the Norwegian coastline, far rougher, approaches 1.52. The dimension is the roughness.

Mandelbrot's coastline paradox The length of a coastline depends on the ruler used to measure it. Use a kilometer ruler and you get one number; a meter ruler, a much larger one; a centimeter ruler, larger still. There is no true length — but there is a true dimension, and that dimension is the invariant.
§ V · Bestiary

A small menagerie of fractals

These are the objects every student of the field should be able to recognize, construct, and reason about. Each illustrates a different principle.

V.5 The Mandelbrot set

The most famous object in modern mathematics. Defined with shocking simplicity — iterate zz² + c in the complex plane and ask which values of c remain bounded — its boundary is infinitely intricate, contains miniature copies of itself, and has Hausdorff dimension exactly 2. It is, in a sense, the set of all Julia sets: a single image that catalogs an entire universe of dynamical behaviors.

V.5 The Mandelbrot set · M = { c ∈ ℂ : the orbit of 0 under z ↦ z² + c stays bounded }

V.6 Honorable mentions

Menger Sponge. The three-dimensional analogue of the Sierpiński carpet. Dimension log 20 / log 3 ≈ 2.727. Infinite surface area, zero volume.

Julia Sets. One for every c in the complex plane. Connected iff c lies inside the Mandelbrot set.

Barnsley Fern. A photo-realistic fern produced by an Iterated Function System of just four affine maps — a triumph of fractal compression.

Lorenz Attractor. The strange attractor of a simplified weather model. Dimension ≈ 2.06. The geometric face of chaos.

Apollonian Gasket. Generated by recursively packing circles. Dimension ≈ 1.3057. A surprisingly deep object connecting to number theory.

Lévy C Curve. A two-dimensional space-filling curve constructed from a single right-angle rule applied recursively.

§ VI · Methods

Four ways to make a fractal

VI.1 Geometric replacement (L-systems)

Begin with an initiator (a shape) and a generator (a rule). Replace each piece of the initiator with a scaled copy of the generator. Repeat. This produces Koch curves, dragon curves, plant-like branching structures. Aristid Lindenmayer's L-systems formalize this as a grammar — a powerful framework for modeling biological growth.

VI.2 Iterated Function Systems (IFS)

A finite set of contraction maps {f1, …, fn} on a complete metric space defines a unique compact attractor: the fractal is the fixed point of the operator F(A) = ⋃ fi(A). The Hutchinson–Barnsley theorem guarantees existence and uniqueness; the Chaos Game renders it efficiently. The Barnsley fern is produced this way with four affine transformations.

VI.3 Escape-time algorithms

For each point c in the complex plane, iterate zn+1 = f(zn, c) and color it by how many iterations are needed to "escape" some threshold. Produces the Mandelbrot set, Julia sets, Burning Ship, Newton fractals. The entire visual mythology of fractals derives from this method.

VI.4 Random / stochastic fractals

Inject randomness at each step. The midpoint displacement algorithm produces realistic mountain terrain. Fractional Brownian motion generalizes Brownian motion to any dimension between 1 and 2 and underlies most computer-graphics renderings of natural landscapes, clouds, and noise.

§ VII · Nature

Where fractals are found, not made

Nature is statistically fractal over a wide range of scales — never to infinite depth, of course, but typically across three to six orders of magnitude, which is more than enough to matter. The list is long; here are some of the most studied examples.

Coastlines and river networks. D ≈ 1.1–1.5. Mandelbrot's original case study.

The human vascular system. Branches recursively to fill three-dimensional space without excess volume — a fractal optimization.

Lungs. Roughly 23 levels of bronchial branching produce ~70 m² of surface area inside a chest cavity of a few liters. D ≈ 2.97.

Lightning and electrical discharge. Dielectric breakdown produces classic random fractals (D ≈ 1.7 in 2D).

Galaxy distribution. Up to a transition scale (~70 Mpc), galaxies appear to be distributed fractally, with D ≈ 2.

Cauliflower and Romanesco broccoli. Visibly self-similar at several scales — botany's gift to introductory lectures.

Snowflakes, dendrites, frost. Diffusion-limited aggregation in action.

Stock-price time series. Mandelbrot's later work; cotton prices were his first dataset (1963).

§ VIII · Chaos

Fractals and the geometry of chaos

Fractal geometry is the natural geometric companion to chaos theory. Where chaos describes how deterministic dynamical systems can produce unpredictable behavior, fractals describe the shape of the sets on which that behavior unfolds.

A strange attractor is an attractor of a dynamical system — a set toward which trajectories converge — that has fractal geometry. The Lorenz attractor, discovered in 1963 in a simplified model of atmospheric convection, was the first famous example. Its two-lobed butterfly shape is now an icon of modern science.

The connection runs deep: the boundary of the Mandelbrot set encodes the complete bifurcation behavior of the logistic map xr·x·(1−x), the simplest equation that produces chaos. Walk along the real axis of the Mandelbrot set and you walk through the period-doubling cascade in chronological order.

Chaos is the dynamics; fractals are the geometry. They are the verb and the noun of the same sentence.
§ IX · Applications

Where the field has gone useful

Computer Graphics

Procedural terrain, cloud, vegetation, and texture generation. Every modern film and video game with a synthetic landscape uses fractal methods.

Image Compression

Fractal Image Compression (Barnsley) stores an image as an IFS rather than as pixels. Resolution-independent decompression.

Antenna Design

Fractal antennas (Sierpiński, Koch, Hilbert curves) are multiband and compact. Standard in modern mobile phones.

Medical Diagnostics

Fractal dimension of tumor margins, retinal vasculature, and EEG signals serves as a diagnostic biomarker.

Quantitative Finance

Mandelbrot's "rough" model of price movements (fractional Brownian motion, multifractals) corrects the Gaussian assumptions of classical finance.

Geophysics & Seismology

Fault networks, earthquake size distributions, and porosity of rocks all exhibit fractal scaling.

Network Science

Many real-world networks (the Internet, metabolic pathways) show self-similar structure under appropriate renormalization.

Art & Architecture

From Jackson Pollock's drip paintings (measurable fractal dimension) to the Eiffel Tower's recursive trusses, fractal aesthetics span centuries.

§ X · Frontiers

What remains open

Fractal geometry, despite its half-century of growth, is a young and active field. Among the open problems and lively frontiers:

The MLC Conjecture. Is the Mandelbrot set locally connected? Conjectured by Douady and Hubbard in the 1980s. A positive resolution would complete our understanding of the parameter space of quadratic polynomials. Still open.

Analysis on fractals. What does calculus look like on a Sierpiński triangle? Kigami, Strichartz, and others have built differential operators, heat equations, and spectral theory on self-similar sets — a field still being formalized.

Multifractals. Most natural fractals are not characterized by a single dimension but by a spectrum of them. The multifractal formalism, developed since the 1980s, remains a major area of probabilistic and statistical research.

Random fractals and SLE. Schramm–Loewner Evolution, a Fields-Medal-recognized framework, describes random fractal curves arising at criticality in two-dimensional statistical mechanics. Its connections to fractal geometry are still unfolding.

§ XI · Reading

For further pursuit

Three texts to take with you. Read them in this order.

Mandelbrot, The Fractal Geometry of Nature (1982). Idiosyncratic, polemical, magnificent. The founding document of the field.

Falconer, Fractal Geometry: Mathematical Foundations and Applications (3rd ed., 2014). The standard rigorous introduction. Use as your reference.

Barnsley, Fractals Everywhere (2nd ed., 1993). The IFS and Chaos Game perspective, lucid and constructive.

Peitgen, Jürgens & Saupe, Chaos and Fractals (1992). Encyclopedic, beautifully illustrated; ideal for self-study.

An exercise to begin with Take a sheet of graph paper. Draw a triangle. Find the midpoints of its sides; connect them to form a smaller, upside-down triangle. Erase that smaller triangle's interior. You now have three triangles; repeat the process on each. After five iterations, count the small triangles. You have just constructed the first generations of the Sierpiński triangle. Its limit object has dimension log 3 / log 2. You are doing fractal geometry.

Set in Cormorant Garamond & EB Garamond.

Diagrams generated procedurally in the browser — themselves small fractals.

— Finis —