Introduction to Chaos Theory

I recently took a course on Chaos Theory as part of a summer camp at the University of Chicago. It was taught by Greg Huber (g-huber@uchicago.edu). If you have any difficult questions you might want to ask him. The first thing we did in our chaos theory course was to look at what happens to an initial value, x0, when a function, f(x), is repeatedly applied to it. We tried this with three functions, both with domain and range within [0, 1].

The Shift Map



The formula for the shift map is f(x) =
x*2 for 0 <= x < .5
x*2-1 for .5 <= x < 1
It turns out that this function can be understood by writing x0 as a "binary decimal". For example .1101 is 13/16, 1/2 + 1/4 + 1/16. Each iteration of the function is equivalent to shifting the decimal point right one place, and chopping off any integer part. Therefore, to understand this function, you just have to write x0 as a "binary decimal".

The Tent Map



The formula for the tent map is f(x) =
x*2 for 0 <= x < .5
x*-2+2 for .5 <= x < 1
This function can also be understood fairly simply. First, express x0 as a "binary decimal". Each iteration of the function starts by shifting the decimal point one place to the left. If the number is 0 point something, you are done. However, If the number is one point something turn all of the ones in the number to zeros, and vice-versa. Therefore, the tent map can also be understood by expressing x0 as a binary decimal.

The Logistic Map



The formula for the logistic map is f(x) = r * x * (1 - x), where r is a constant. The height of the map is r/4, so r ranges from 0 to 4. behavior of the logistic map depends greatly on the value of r. If r is between 0 and 1, repeated iteration of the logistic map will eventually give 0. For r between 1 and 3, the logistic map will eventually settle down to fixed point. After three, more interesting things start to happen. For r just greater than 3, the logisitic map will start to bounce back and forth between two numbers. As r gets a little bigger, the logisitic map will go between four numbers. The number of points the logistic map settles down to will keep doubling until r becomes approximately 3.6. Then the logistic map will end in chaos. If you make a graph with r as the x-axis going from 0 to 4, and the value the logistic map settles to as the y-axis, you get what is known as the bifurcation tree. It looks like this:

The Bifurcation Tree



If you look at the bifurcations of the tree, you can see that they happen faster and faster, until at a certain point, they happen infinitely fast. The ratio of the bifurcations of the tree is called Feigenbaum's Delta.

Fractals


Another part of chaos theory deals with fractals. The formal definition of a fractal is fairly complicated and I don't know what it is. However I do know a little bit about them. Fractals are basicly self-similar objects. For example, take a line segment with length 1. Then split it into thirds and get rid of the middle third. Every time you do this, you end up with two copies of the original, only they are one third the size. This fractal is known as the Cantor set. Here is a picture of it:

The Cantor Set



Another example is called the Koch Curve. Start with a line segment of length 1. Then replace the middle third of the segment with two segments of length one third that form the two legs of a equilateral triangle, with the third side being the line segment you just got rid of. If you keep doing this, you get something that looks pretty cool.

The classic example of a fractal is the Mandelbrot set. This is a real cool looking thing that is created a lot differently than most other fractals.

Chaos Links

The Julia Set
This is the source code to a C++ program I wrote. It draws the Julia set, and lets you zoom in on different parts of it.
The Mandelbrot Set
This is the source code to a C program I wrote. It draws the Mandelbrot set, and lets you zoom in on different parts of it.
Fractals and Chaos Theory
A good introduction to chaos theory, including the Bifurcation Tree, and the Mandelbrot Set.
Chaos Theory: A Brief Introduction
Another introduction to chaos theory, with many excerpts from James Gleick's book, Chaos.

Return to my homepage.


David Mellis / stendahl@imsa.edu / Last Modified August 13, 1996