Differential Equations Notes

Math 243 - Fall 2025

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Week 1 Notes

Day Section Topic
Mon, Aug 25 1.1 Modeling with Differential Equations
Wed, Aug 27 1.2 Separable Differential Equations
Fri, Aug 29 1.3 Geometric and Quantitative Analysis

Mon, Aug 25

We talked about some examples of differential equations.

  1. Exponential Growth/Decay. The rate of change in a variable yy with respect to time tt is proportional to yy itself. dydt=ky.\dfrac{dy}{dt} = k y.
    1. Check that y(t)=Cekty(t) = Ce^{kt} is a solution.
    2. Find the constant CC which satisfies the initial value problem with initial condition y(0)=1000y(0) = 1000.

We talked about dependent and independent variables, the order of a differential equation and how to tell if a function is a solution of a differential equation. We also talked about initial conditions.

  1. Spring-Mass Model. The force FF of a mass mm at the end of a spring can be modeled by Hooke’s Law which says F=kxF = -k x where xx is the displacement of the spring from its rest position. md2xdt2=kx.m\dfrac{d^2 x}{dt^2} = -kx.

    1. Show that x=sintx = \sin t and x=costx = \cos t are two different solutions of the spring equation when m=k=1m = k = 1.
    2. How would the solutions change if mm and kk were not both equal to 1? How would the oscillation of the spring change if the mass was twice as heavy?
    3. How would the spring equation change if there was also a linear drag force F=bdxdtF = -b \frac{dx}{dt}? What if there is a non-linear drag force F=b(dxdt)2F = -b \left(\frac{dx}{dt}\right)^2?

The last question led to a discussion of linear versus non-linear differential equations. It’s usually much harder to solve non-linear equations! We will also study systems of differential equations, like the following.

  1. Rabbits and Foxes. Suppose there are RR rabbits and FF foxes in an ecosystem. The rabbit population would grow exponentially, except for the foxes which prey on the rabbits. The fox population would decay exponentially if there wasn’t food to eat, but as long as they can catch enough rabbits, it will grow. The number of rabbits that are eaten by foxes is proportional to the product RFRF.
    dRdt=aRbRFdFdt=cR+dRF\begin{align*} \dfrac{dR}{dt} &= a R - b RF \\ \dfrac{dF}{dt} &= -c R + d RF \end{align*}

Here is a graph showing these equations as a vector field (with constants a=3,b=4,c=1,d=2a = 3, b = 4, c = 1, d= 2).

  1. Logistic Growth. dPdt=kP(1PN)\dfrac{dP}{dt} = kP \left( 1 - \dfrac{P}{N} \right) where kk is a proportionality constant and NN is the carrying capacity.

    1. Under what circumstances does the population PP stop changing in this model?
    2. What are the units for the constants kk and NN?
    3. Suppose that we use the logistic growth equation to model a population of rabbits in a region. What if we introduce a predator that always consumes bb rabbits per year. How would that change the differential equation above?

Wed, Aug 27

Today we talked about separable equations. We solved the following examples.

  1. Solve dydx=x2y\dfrac{dy}{dx} = - x^2 y.

  2. Solve xy2y=x+1xy^2 y' = x+1. (https://youtu.be/1_Q4kndQrtk)

Not every differential equation is separable. For example: dydx=xy\frac{dy}{dx} = x-y is not separable.

  1. Which of the following differential equations are separable? (https://youtu.be/6vUjGgI8Dso)

    1. xy+y=3xy' + y = 3
    2. 2x+2y+2y1=02x + 2y + 2y' - 1 = 0
    3. y=(x2+x)(y2+y)y' = (x^2+x)(y^2+y)
    4. xdydx+ydydx=xx \dfrac{dy}{dx} + y \dfrac{dy}{dx} = x

We finished with this example:

  1. Newton’s Law of Cooling. The temperature of a small object changes at a rate proportional to the difference between the object’s temperature and its surroundings.

    1. Express Newton’s Law of Cooling as a differential equation.
    2. Is that differential equation separable?
  1. Mixing Problem. Salty water containing 0.02 kg of salt per liter is flowing into a mixing tank at a rate of 10 L/min. At the same time, water is draining from the tank at 10 L/min.

    1. Write a differential equation to model how the amount of salt in the tank changes with respect to time.
    2. Solve the differential equation if the amound of salt in the tank is initially 15 kg. (https://youtu.be/aFfAz9wnoyY)

We didn’t get to this last example in class, but it is a good practice problem.

  1. dydx=4sinx3y2\dfrac{dy}{dx} = \dfrac{4 \sin x}{3 y^2} with initial condition y(0)=2y(0) = 2. (https://youtu.be/cc3qtMBdQlE)

Fri, Aug 29

Today we talked about slope fields.

  1. Sketch the slope field for dydx=xy\dfrac{dy}{dx} = x - y. (https://youtu.be/24pxJ1DuWR8)

Here is a slope field grapher tool that I made a few years ago. You can also use Sage to plot slope fields. Here is an example from the book, with color added.

t, y = var('t, y')
f(t, y) = y^2/2 - t
plot_slope_field(f, (t, -1, 5), (y, -5, 10), headaxislength=3, headlength=3, 
    axes_labels=['$t$','$y(t)$'], color = "blue")
Open example in SageCell
  1. Consider the logistic equation with harvesting. dPdt=kP(1PN)h\dfrac{dP}{dt} = k P \left(1 - \dfrac{P}{N} \right) - h where hh is a number of rabbits that are harvested each year.

    1. If k=1k = 1, N=8N = 8, and h=1.5h = 1.5, then what are the values of PP where dPdt=0\dfrac{dP}{dt} = 0? Slope field
    2. Graph the function y=kx(1xN)h.y =k x \left(1 - \dfrac{x}{N} \right) - h. Where does the graph cross the x-axis? Is the slope positive or negative at those crossing points?

The logistic equation (with or without harvesting) is autonomous which means that the rate of change dPdt\dfrac{dP}{dt} does not depend on time, just on PP. An equilibrium solution for an autonomous differential equation is a solution where y(t)=0y'(t) = 0 for all tt.

  1. In the logistic equation above, what happens to the equilibrium solutions when the rate of harvesting is increased to h=2h = 2 and then to h=2.5h = 2.5? What happens to the slope field? What does that mean about the population of rabbits?

Week 2 Notes

Day Section Topic
Mon, Sep 1 Labor day - no class
Wed, Sep 3 1.4 Analyzing Equations Numerically
Fri, Sep 5 1.4 Analyzing Equations Numerically - con’d

Week 3 Notes

Day Section Topic
Mon, Sep 8 1.5 First-Order Linear Equations
Wed, Sep 10 1.6 Existence and Uniqueness of Solutions
Fri, Sep 12 1.7 Bifurcations

Week 4 Notes

Day Section Topic
Mon, Sep 15 2.1 Modeling with Systems
Wed, Sep 17 2.2 The Geometry of Systems
Fri, Sep 19 2.2 The Geometry of Systems - con’d

Week 5 Notes

Day Section Topic
Mon, Sep 22 2.3 Numerical Techniques for Systems
Wed, Sep 24 2.4 Solving System Analytically
Fri, Sep 26 2.4 Solving System Analytically - con’d

Week 6 Notes

Day Section Topic
Mon, Sep 29 Review
Wed, Oct 1 Midterm 1
Fri, Oct 3 3.1 Linear Algebra in a Nutshell

Week 7 Notes

Day Section Topic
Mon, Oct 6 3.2 Planar Systems
Wed, Oct 8 3.2 Planar Systems - con’d
Fri, Oct 10 3.3 Phase Plane Analysis of Linear Systems

Week 8 Notes

Day Section Topic
Mon, Oct 13 Fall break - no class
Wed, Oct 15 3.4 Complex Eigenvalues
Fri, Oct 17 3.5 Repeated Eigenvalues

Week 9 Notes

Day Section Topic
Mon, Oct 20 3.6 Changing Coordinates
Wed, Oct 22 3.7 The Trace-Determinant Plane
Fri, Oct 24 3.7 The Trace-Determinant Plane - con’d

Week 10 Notes

Day Section Topic
Mon, Oct 27 Review
Wed, Oct 29 Midterm 2
Fri, Oct 31 3.8 Linear Systems in Higher Dimensions

Week 11 Notes

Day Section Topic
Mon, Nov 3 3.9 The Matrix Exponential
Wed, Nov 5 4.1 Homogeneous Linear Equations
Fri, Nov 7 4.2 Forcing

Week 12 Notes

Day Section Topic
Mon, Nov 10 4.3 Sinusoidal Forcing
Wed, Nov 12 4.4 Forcing and Resonance
Fri, Nov 14 5.1 Linearization

Week 13 Notes

Day Section Topic
Mon, Nov 17 5.1 Linearization - con’d
Wed, Nov 19 Review
Fri, Nov 21 Midterm 3
Mon, Nov 23 6.1 The Laplace Transform

Week 14 Notes

Day Section Topic
Mon, Dec 1 6.1 The Laplace Transform - con’d
Wed, Dec 3 6.2 Solving Initial Value Problems
Fri, Dec 5 6.2 Solving Initial Value Problems - con’d
Mon, Dec 8 Recap & review