We describe numerical and graphical methods for understanding differential equations.
Slope fields
We cannot (yet!) solve the differential equation However, from the equation alone, we can describe some facts about the solution.
Given a differential equation, say , we can pick points in the plane and compute what the slope of a solution at those points will be. Repeating this process, we can generate a slope field. The slope field for the differential equation looks like this:
Let’s be explicit:
- Choosing a grid of points.
- At each point, computing the slope given by the differential equation, using the and -values of the point.
- At each point, drawing a short line segment with that slope.
Here is the slope field for the differential equation , with a few solutions of the differential equation also graphed.
Notice that the slope field suggests one solution to this differential equation, which is a straight line.Autonomous differential equations
Consider the following differential equations
The first differential equation, , is rather easy to solve, we simply integrate both sides. This type of differential equation is called a pure-time differential equation. Pure-time differential equations express the derivative of the solution explicitly as a function of an independent variable. We can symbolically describe a pure-time differential equation as
On the other hand, the second differential equation, does not involve the independent variable, , at all! Such differential equations are called autonomous differential equations.
Finally the third differential equation, , expresses as a function of both and the independent variable . Such a differential equation is called a nonautonomous differential equation. We can symbolically describe a nonautonomous differential equation as
Since autonomous differential equations only depend on the function’s value their behavior does not depend on the independent variable,
Consider the autonomous differential equation: The constant functions and are solutions to this differential equation. In fact, for any autonomous differential equation , where is a function of , if for any constant , then will be a constant solution to the differential equation. These constant solutions are also known as equilibrium solutions. We can witness these solutions if we inspect the slope field:
Finally, let’s work an example problem:
Euler’s Method
In science and mathematics, finding exact solutions to differential equations is not always possible. We have already seen that slope fields give us a powerful way to understand the qualitative features of solutions. Sometimes we need a more precise quantitative understanding, meaning we would like numerical approximations of the solutions.
Again, suppose you have set up the following differential equation If we know that solves this differential equation, and , how might we go about approximating ? One idea is to repeatedly use linear approximation.
Let us approximate just using the two subintervals Since , we know that by linear approximation.
But now, we have so Plotting our approximation with the actual solution we find: This approximation could be improved by using more subintervals. We will now formalize the method of using repeated linear approximation to approximate solutions to differential equations, and call it Euler’s Method.- Set and .
- Decide either a step-size or how many subintervals you want to divide the interval into. Either way: and .
- Iteratively define for .
Then , and so .
Let’s try an example.