UCT MAM1000 lecture notes part 42 – 3D geometry and vectors part v

The vector, or cross product

When we took two vectors previously and found a way to multiply them together using the dot product, we ended up with a scalar. However, there is also a way that we can take two vectors and multiply them together to give a vector, but a vector with very specific properties with respect to the first two. What we will define here will be in three dimensions, and, unlike the dot product, does not generalise easily to other dimensions, (other than 7) though it can in fact be extended.

We are going to define the cross product such that it gives a vector which is perpendicular to the two vectors being crossed. This might sound a bit arbitrary but it shows up in a huge number of different situations in physics in particular and can help us to understand the geometric relation between vectors very simply.…

Something for the weekend: Pascal’s Triangle at TED

Pascal’s triangle is even deeper than you thought…

How clear is this post?
By | September 18th, 2015|English, Level: intermediate|0 Comments

Chaos from differential equations

In all of this talk about differential equations, we haven’t spoken all that much about the uses of them, apart from a little about population dynamics, nor indeed about their amazing properties. Part of the reason for this is that in general (though of course not exclusively), the most interesting differential equations are a single step beyond what we have been looking at. They are differential equations in more than one variable. For instance, rather than just having a y be a function of x or t, they have y a function of both x and t. It turns out that this little change makes all the difference in the world. All of a sudden we can see how things change in both space and time. We can look at real dynamics of systems which are not local to a single place.

This is a topic for another time, and comes under the term partial differential equation.…

By | September 15th, 2015|English, Level: intermediate|0 Comments

UCT MAM1000 lecture notes part 37 – differential equations part vi – second order differential equations

Second Order differential equations

We are only going to look at a particular subset of all possible second order differential equations (that is, equations which contain at most second derivatives) but these particular equations are absolutely ubiquitous across every field of science. The particular subset we are going to look at are linear, homogenous second order differential equations with constant coefficients. These can be written in general as:

 

\frac{d^2y}{dx^2}+b\frac{dy}{dx}+c y=0

 

It is linear because it contains at most (and in this case at least) a single power of y in each term. It is homogenous because there is no term which has no powers of y (ie. the right hand side is not a constant), and the coefficients b and c are any real numbers (though you can extend this to having complex numbers very easily). We will see that depending on the relationship between these numbers (b and c) we can have very different behaviour of the equation.…

UCT MAM1000 lecture notes part 36 – differential equations part v – first order differential equations

First order linear differential equations

We are now going to deal with another subset of first order differential equations which in some ways are easier than the previous and in other ways more complicated. These are linear first order differential equations. The general form of a first order linear differential equation is:

 

\frac{dy}{dx}+P(x)y=Q(x)

 

where P(x) and Q(x) are any functions of x.

 

Very importantly, I’m leaving off the fact that y is dependent on x in the notation, but you should remember that this is really y(x) and that is the function you are trying to solve for.

 

Sometimes you will be given an equation which is not obviously in this form but it can be transformed to this form. For instance:

 

\frac{1}{y}\frac{dy}{dx}=x^2+\frac{\sin x}{y}

 

This can easily be transformed into the canonical form for a linear first order DE. We are going to try and rewrite the left hand side of the equation in a form which will mean that we can solve the differential equation very easily.…

UCT MAM1000 lecture notes part 35- differential equations part iv – separable differential equations

Separable differential equations
In some ways these are the easiest differential equations to solve in theory, though in practice the final step (that of integrating) may be difficult or impossible. A separable differential equation is one of the form:

 

\frac{dy}{dx}=\frac{f(x)}{g(y)}

 

where f(x) and g(y) are any functions of x and y respectively. For instance:

 

\frac{dy}{dx}=x y

 

is of this form where f(x)=x and f(y)=\frac{1}{y}. The reason that these equations are simple in theory is because we can rearrange them to be:

 

g(y)dy=f(x)dx

 

ie. we have all the x stuff on one side and all the y stuff on the other and then we can integrate both sides:

 

\int g(y)dy=\int f(x)dx

 

and that’s it. As long as you can do the integrals, you can get a function y in terms of x. let’s look at some examples:

 

\frac{dy}{dx}=x y

 

gives the following integral:

 

\int\frac{1}{y}dy=\int x dx

 

and so:

 

\ln |y|+c_1=\frac{x^2}{2}+c_2

 

here we have one constant of integration from each side of the interval, but because they are just constants, we can put them into one constant and call it c:

 

\ln |y|=\frac{x^2}{2}+c

 

we can then rearrange this to give:

 

|y|=e^{\frac{x^2}{2}+c}=e^ce^{\frac{x^2}{2}}

 

We can then call e^c just a constant, and let’s call it y_0 because we can see that when x is zero, |y| is just going to be given by this constant:

 

|y|=y_0e^{\frac{x^2}{2}}

 

This has two solutions (one where y is positive, and one where it is negative), so we can choose one of them, depending on the initial condition for y.…

UCT MAM1000 lecture notes part 34 – differential equations part iii – Direction flows and Euler’s method

We haven’t yet studied any general ways to solve differential equations. In the first case of exponential growth we found an easy way to solve the equation, but for the logistic equation we just gave the solution and showed that it indeed satisfied the equation. Here we are going to look at some methods for finding not the exact solution, but approximations of the solutions. The first method is the method of Direction Fields and it will give us a good idea of what the solutions are going to look like. The second method, Euler’s method will give us an approximation to a single solution and we will be able to improve it to get arbitrarily good solutions to any differential equation (so long as there aren’t particularly nasty pathologies in the differential equation).

Direction Fields

Let’s take a differential equation:

 

\frac{dy}{dx}=x+y

 

Note that sometimes we will say explicitly that y(x) and sometimes we will leave it implicit, because the equation has a derivative of y with respect to x.…

UCT MAM1000 lecture notes part 32 – differential equations and rabbits moving at the speed of light

Up to now if I gave you an equation, and asked you to solve it for x you would be, in general, looking for a value of x which solved the equation. Given:

 

x^2+3x+2=0

 

You can solve this equation to find two values of x.

I could also give you an equation which linked x and y explicitly, and you could find a relationship between the two which, given a value of x would give you a value of y. You’ve been doing this now for many years. Now we’re going to add a hugely powerful tool to our mathematical arsenal. We’re going to allow our equations to include information about gradients of the function…let’s see what this means…

We’re going to take everything that you learnt about integration and turn it into a way to model and understand the world around us. This is a very powerful statement and indeed differential equations are without a doubt the most powerful mathematical tool we have to understand the behaviour of everything from fundamental particles to populations, economies, weather, flow of wealth, heat, fluids, the motion of planets, the life of stars, the flight of an aircraft, the trajectory of a meteor, the way a pendulum swings, the way a ponytail swings (see paper on this here), the way fish move, the way algae grow, the way a neuron fires, the way a fire spreads…and so much more.…

UCT MAM1000 lecture notes part x – summary

When you were a child you first learnt how to count. You learnt the relationship between a number and the quantity of objects around you. You quickly learnt to manipulate these numbers, you could add them, and you could multiply them, and you could subtract them. Subtracting them brought you to negative integers. Then you learnt how to divide them and this took you to fractions and thus the rational numbers. You could then manipulate these new numbers with the same operations.

At school you learnt about powers of numbers, and square roots of numbers, and you learnt about equations and how you could solve them to find the numbers which satisfied the equation. There were a few rules which acted like dead-ends however. You could never take the square root of a negative number. In fact any fractional power of a negative number should have filled you with trepidation (and possibly a frisson of excitement), though sometimes you saw that there were sneaky solutions to things like (-1)^\frac{1}{3}.…

Complexity from complex numbers – The beauty of the Mandelbrot set

We are about to show that you can get incredible structure from the simplest of algorithms when we use complex numbers.

The equation we are going to look at is an iterative equation:

 

z_{i+1}=z_i^2+C

 

with z_0=0. You simply get the next z_i from plugging in the previous one, squaring it and adding a number C. I’m going to give you a value for C, then you’re going to iterate this equation and see what happens. For instance, if I give you the number C=3:

 

\left(  \begin{array}{ccc}  i & z_i^2+C & \left| z_{i+1}\right| \\  1 & 0^2+3 & 3 \\  2 & 3^2+3 & 12 \\  3 & 12^2+3 & 147 \\  4 & 147^2+3 & 21612 \\  \end{array}  \right)

 

You can see that this number is just going to keep on increasing without end if we keep applying the algorithm. How about a smaller number, let’s say C=0.1:

 

\left(  \begin{array}{ccc}  i & z_i^2+C & \left| z_{i+1}\right| \\  1 & 0^2+0.1 & 0.1 \\  2 & 0.1^2+0.1 & 0.1121 \\  3 & 0.1121^2+0.1 & 0.112566 \\  4 & 0.112566^2+0.1 & 0.112671 \\  \end{array}  \right)

 

It looks like this is tending to some value. In fact it has come to a fixed point where z=z^2+0.1. There are actually two solutions to this equation but one of them is 0.112702 which is where we are tending towards.…

By | August 29th, 2015|English, Level: intermediate, Uncategorized|0 Comments