In earlier work, we have used the tangent line to the graph of a function at a point to approximate the values of near . The usefulness of this approximation is that we need to know very little about the function; armed with only the value and the derivative , we may find the equation of the tangent line and the approximation
Remember that a first-order differential equation gives us information about the derivative of an unknown function. Since the derivative at a point tells us the slope of the tangent line at this point, a differential equation gives us crucial information about the tangent lines to the graph of a solution. We will use this information about the tangent lines to create a slope field for the differential equation, which enables us to sketch solutions to initial value problems. Our aim will be to understand the solutions qualitatively. That is, we would like to understand the basic nature of solutions, such as their long-range behavior, without precisely determining the value of a solution at a particular point.
Suppose that is a solution to this differential equation corresponding to the initial value . On the graph of versus , what is the slope of the tangent line to the curve at the point ?
Suppose (instead) that is a solution to this differential equation corresponding to the initial value . On the graph of versus , what is the slope of the tangent line to the curve at the point ?
Suppose that is a solution to this differential equation that passes through the point . On the graph of versus , what is the slope of the tangent line to the curve at the point ?
If we only know the differential equation, (but not any points on the solution curve), which of the following could be a solution to the equation? Select all that apply.
Given this differential equation (but not an initial value or the solution) what information is sufficient to determine the slope of the tangent line to the solution curve at a point on the curve?
Preview Activity 7.2.1 shows that we can sketch the solution to an initial value problem if we know an appropriate collection of tangent lines. We can use the differential equation to find the slope of the tangent line at any point of interest, and hence plot such a collection.
Let’s continue looking at the differential equation . If , this equation says that . Note that this value holds regardless of the value of . We will therefore sketch tangent lines for several values of and with a slope of , as shown in Figure 7.2.1.
Let’s continue in the same way: if , the differential equation tells us that , and this holds regardless of the value of . We now sketch tangent lines for several values of and with a slope of in Figure 7.2.2.
In Figure 7.2.3, we begin to see the solutions to the differential equation emerge. For the sake of even greater clarity, we add more tangent lines to provide the more complete picture shown at right in Figure 7.2.4.
Figure 7.2.4 is called a slope field for the differential equation. It allows us to sketch solutions just as we did in the preview activity. We can begin with the initial value and start sketching the solution by following the tangent line. Whenever the solution passes through a point at which a tangent line is drawn, that line is tangent to the solution. This principle leads us to the sequence of images in Figure 7.2.5.
Just as we did for the equation , we can construct a slope field for any differential equation of interest. The slope field provides us with visual information about how we expect solutions to the differential equation to behave.
Make a plot of versus on the axes provided in Figure 7.2.7. Looking at the graph, for what values of does increase and for what values of does decrease?
Subsection7.2.2Equilibrium solutions and stability
As our work in Activity 7.2.2 demonstrates, first-order autonomous equations may have solutions that are constant. These are simple to detect by inspecting the differential equation : constant solutions necessarily have a zero derivative, so .
Make a plot of versus on the axes provided in Figure 7.2.9. Looking at the graph, for what values of does increase and for what values of does decrease?
An equilibrium solution is called stable if nearby solutions converge to . This means that if the initial condition varies slightly from , then . Conversely, an equilibrium solution is called unstable if nearby solutions are pushed away from . Using your work above, classify the equilibrium solutions you found in (b) as either stable or unstable.
Suppose that describes the population of a species of living organisms and that the initial value is positive. What can you say about the eventual fate of this population?
Now consider a general autonomous differential equation of the form . Remember that an equilibrium solution satisfies . If we graph as a function of , for which of the differential equations represented in Figure 7.2.11 and Figure 7.2.12 is a stable equilibrium and for which is unstable? Why?
Autonomous differential equations sometimes have constant solutions that we call equilibrium solutions. These may be classified as stable or unstable, depending on the behavior of nearby solutions.
On a print-out of these slope fields, sketch for each three solution curves to the differential equations that generated them. Then complete the following statements:
Match the following equations with their direction field. Clicking on each picture will give you an enlarged view. While you can probably solve this problem by guessing, it is useful to try to predict characteristics of the direction field and then match them to the picture.
Setting equal to a constant other than zero gives the curve of points where the slope is that constant. These are called isoclines, and can be used to construct the direction field picture by hand.
List the constant (or equilibrium) solutions to this differential equation in increasing order and indicate whether or not these equilibria are stable, semi-stable, or unstable. (It helps to sketch the graph. 1
From your sketch, what is the equation of the solution to the differential equation that passes through (1,0)? (Verify that your solution is correct by substituting it into the differential equation.)
By considering the differential equation and the graphs you have sketched, what is the relationship between and at a point where a solution has a local minimum?
Consider the situation from problem 2 of Section 7.1: Suppose that the population of a particular species is described by the function , where is expressed in millions. Suppose further that the population’s rate of change is governed by the differential equation
Sketch a slope field for this differential equation. You do not have enough information to determine the actual slopes, but you should have enough information to determine where slopes are positive, negative, zero, large, or small, and hence determine the qualitative behavior of solutions.
Remember that we referred to this model for population growth as “growth with a threshold.” Explain why this characterization makes sense by considering solutions whose inital value is close to 1.
The population of a species of fish in a lake is where is measured in thousands of fish and is measured in months. The growth of the population is described by the differential equation
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Sketch a graph of and use it to determine the equilibrium solutions and whether they are stable or unstable. Write a complete sentence that describes the long-term behavior of the fish population.
Suppose now that the owners of the lake allow fishers to remove 1000 fish from the lake every month (remember that is measured in thousands of fish). Modify the differential equation to take this into account. Sketch the new graph of versus . Determine the new equilibrium solutions and decide whether they are stable or unstable.
What is the largest number of fish that can be removed per month without eliminating the fish population? If fish are removed at this maximum rate, what is the eventual population of fish?
Let be the number of thousands of mice that live on a farm; assume time is measured in years. 2
This problem is based on an ecological analysis presented in a research paper by C.S. Hollings: The Components of Predation as Revealed by a Study of Small Mammal Predation of the European Pine Sawfly, Canadian Entomology91: 283-320.
The population of the mice grows at a yearly rate that is twenty times the number of mice. Express this as a differential equation.
Suppose that . Find the equilibrium solutions and determine whether they are stable or unstable. Use this to explain the long-term behavior of the mice population depending on the initial population of the mice.
Suppose that . Find the equilibrium solutions and determine whether they are stable or unstable. Use this to explain the long-term behavior of the mice population depending on the initial population of the mice.