In this unit, I will talk about fixed points and stability. Two important concepts we will use throughout the course. But first, I should mention that iterated functions are an example of a dynamical system and the course is about dynamical systems. So, this is important. So I should say what dynamical systems are. And I'll come back to this again. But, for now: Dynamical system is a system that evolves in forward forward in time according to a well defined and unchanging rule. And that is what we have for iterated functions. So, we have a value, a number, that moves forward changes from iterate to iterate. According to a well defined rule. That is the function. A nice deterministic function. The same input gives the same output each time. And the rule doesn't change as we iterate. We are doing the same thing over and over again. Using the output of one step for the input of the next So, iterated functions are a dynamical system In the study of dynamical systems, We are often not particularly interested in the numbers of a particular orbit or itinerary. Instead we are interested collections of orbits, many orbits all at once. And more generally we would like to understand What sort of behaviors do we see in different types of dynamical systems? So this is the approach we will take in this course and so we will start that in this unit When we look at fixed points and stability Let's start with an example. We will consider the squaring function. F(x) = x^2. We know how to calculate an orbit for this function. We just start with the number, the seed. In this case I choose 1.1. And then we square it to get the next iterate. 1.21. We square that to get 1.46. And so on. We could choose a different seed. And we would get a different orbit. Let's say instead of 1.1, I choose 1.2. I would do the same thing Square again and again. To get that orbit. So here is the orbit for the seed 1.2. Note that both orbits get larger when you square a number larger than 1. The number gets larger. So these numbers will continue to grow Let's try another one. Suppose I choose a seed of 0.9. I'll put 0.9 here. What will happen? Well let's apply the function and see. For this initial condition, the number gets smaller. It's getting closer and closer to zero. If you square a number between 0 and 1, It gets smaller not larger. Let's try one more initial condition. One more seed. I'll try 0.8. And I will square again and again to get the orbit. So again when we square a number between 0 and 1, it gets smaller. Here we can see the number gets close and closer to zero. So, calculating the orbit a particular orbit for a particular seed is not too difficult. It just requires a little bit of calculator work. But it doesn't let us get a sense of the big picture. What does this function do? So we will use some graphical techniques that will help us see this better and understand the function all at once. First, let me plot the time series plots for these four orbits. 1.1 and 1.2 they get bigger. 0.9 and 0.8 they get smaller. So here is the time series plot for that. You can see I have four different initial conditions. A square, a diamond --sorry -- a sqaure, a triangle, a circle, and a diamond. The square that is 1.2. We can see that growing quite fast. It goes off the graph. The triangles are 1.1 Those grow. The circles are 0.9 and those are getting close to zero. And then 0.8 also gets close to zero. So this lets us see the numbers larger than 1 will get larger and larger And numbers between 0 and 1 we suspect will get closer and closer to zero.