Welcome, please note that the offical syllabus is linked here. Please note this webpage is where test solutions and further assignments are to be posted. For your convenience, I have provided a few links to points further down this page.

- I. Course Contact Information
- II. Useful Materials and Links:
- III. Additional Examples:
- IV. Test Reviews and Solutions:
- V. Course Notes:
- VI. Bonus Point Policy:
- VII. Practice Homework List:

- Instructor: Dr. James S. Cook
- Office: Applied Science 105
- Office Hours: M-W-TH 5:00-6:20pm and by appointment.
- Email: jcook4@liberty.edu (preferred)
- Office Phone: 434-582-2476
- Lectures and tests are in Applied Science 114
- Lecture Times: 2:00-3:15pm

- Course Syllabus
- My NCSU webpage (you'll find the old ed. of my notes in the ma 341 course).
- Notes concerning the basics of complex variables
- Yet more notes on the complex exponential:
- Concerning rearrangement of power series. Domain changing algebra.

These notes show you what I expect you already saw in calculus II. We do review some of these materials in this course:

I will post reviews and solutions for our course here once it's time.

- Review for Test 1
- Review for Test 2
- Review for Test 3
- Review for Test 4 (not in-class)
- Final Exam Guide

Sorry these took so long to put up this summer. The first few pages are blank at the moment because I plan to add an introduction and overview once I've written all the notes. The notes are finished for the summer. I may add notes on Chapter 10 if I find it is needed. At the present there are 40+ pages of Practice Homework solutions on Chapter 10. Beyond that, the text is in many ways better than my notes in this course so I recommend that you read it.

Notes that are covered by Test I ( if at all ):

- [1-12] Introduction to Differential Equations: I begin with a few unjustified calculations from physics. My goal is simply to convince you that DEqns are useful and of foundational importance to physics ( and hence to all applied sciences ). We will not justify some of those calculations until the end of the course when we study Partial Differential Equations (PDEs). Pages 9-12 include many important terms which we use throughout the course. Slope fields and Euler's Method are discussed (but not tested). Our focus is on finding closed form solutions.
- [13-23] Separation of variables and applications: The proof of separation of variables is U-substitution. We also discuss applications including exponential population growth, radioactive decay, position and velocity, orthogonal trajectories, mixing tank and the logistic model. To summarize: if you can describe a physical process in terms of how the change in the quantities of interest then the basic law which governs the process will be a differential equation.
- [24-28] The integrating factor method allows us to solve many problems for which separation of variables fails. In general dy/dx + py = q is called a linear ODE and if p,q are continuous functions then the integrating factor method will solve it. Next we discuss exact DEqns. In short, if the DEqns is dF = 0 for some function F(x,y) then the solutions are simply level curves of F. We discuss how to check if a given DEqn Mdx + Ndy = dF for some F. We also describe how to find F from the Pfaffian form Mdx + Ndy. (Writing a DEqn as a sum of functions times differentials is called a Pfaffian form of the DEqn)
- [29-37] Sometimes a given DEqn fails to be exact, however if we multiply by a function "mu" then the resulting DEqn becomes exact. Since we know how to solve exact DEqns this is nice. The difficulty is that there is a great variety of possibilities for "mu" (again called the integrating factor, however this is no longer calculated the same way as in Section 2.3). Fortunately we are not faced with the question of how to find "mu" in general, we will always be given some hint to guide us. Then pages 35-37 discuss the idea of substitution. We see how a clever change of variables can sometimes recast an insolvable problem into a nice separable DEqn. Again, we are fortunate that we are not asked to find a general method of which substitution is "best". Many problems do allow for educated guessing on the basis of a manifest pattern, but that's about it.
- [38-40] I give an example of how symmetry guides a choice of cannonical coordinates. I don't give a very careful definition of what a "symmetry of a differential equation" is or even what precisely how a "change of coordinates" is made. But, I do give an example where the DEqn looks very hard in Cartesian coordinates yet once we change of polar coordinates it becomes separable. This is due to the fact that the polar coordinates are cannonical coordinates with respect to the rotational symmetry the given DEqn possesses. This is not required material, however it is an invitation to further study. There is still much ongoing research on the topic of "geometry of differential equations". These notes are largely inspired from Peter Hydon's text "Symmetry Methods for Differential Equations: A Beginners Guide". If you reach a deep understanding of that text then things like the integrating factor method will not seem like a "trick", instead they will gain a nice geometric motivation.
- [41-45] Newtonian Physics flows from his 2nd Law F = dP/dt where P = mv for simple examples in rectilinear coordinates. We study a few token examples and find that we already know more than enough DEqns to squash any of these applications. The falling raindrop problem is one of my favorites ( there are many other variations on the model given in these notes)
- [46-55] Higher order linear constant coefficent homogeneous ordinary differential equations are easy. We learn that an n-th order DEqns has n-solutions y1,y2,...,yn and the general solution is simply a linear combination of those n-solutions; y = c1*y1 + c2*y2 + ... + cn*yn. The question then is simply: "How to find y1,y2,...,yn ?". Turns out it's just an algebra problem. We calculate the "Characteristic Equation" then its roots guide us to the formulas for y1,y2,...,yn. Our focus is largely on the n=2 case where the Characteristic Equation is a quadratic equation. We also introduce the "operator notation" for a differential equation so we can write higher order examples like y'''+3y''+3y'+y = 0 as (D+1)^3[y]=0 (nice compact notation that reveals the most important aspect of the differential equation, namely that the Characteristic Eqn is (r+1)^3 = 0). Finally, I should mention that when the Characteristic Eqn has a complex root it naturally suggests we have a complex solution. However, we want real-values solutions so this is not quite satifactory. The solution is simple, any complex solution we find always contains two real-solutions, they're just the real and imaginary parts of the complex solution. You need to review the complex exponential function in order to understand the details completely. I have relegated those calculations to an Appendix on Complex Math.

- [56-65] I begin by discussing linear independence of functions and how the Wronskian sometimes helps. In short, the Wronskian is a useful tool for determining the linear independence of n-functions which are solutions to a common DEqn of order n. Linear independence is an important concept which we by in large take for granted in this course since the methods we develope tend to guide us to solutions which are automatically independent. We also define important terms such as "Linear Operator" and "nonhomogeneous" or "homogeneous" DEqn. The Theorems stated on page 66 are the foundation of most of what we do in about 45% of the course. Don't worry too much about the Wronskian, I have much more than I expect you to understand on that topic. Sorry this particular section of notes is so verbose.
- [67-74] These notes go through a derivation of the solution to the n-th order homogeneous linear constant coefficient differential equation. To summarize, I show that the n-th order differential equation can be written as an operator equation and then the operator can be factored into n operators of the simple form. Then we learn that this breaks the problem into n-pieces. Better yet, the factorization of the operators matches the factorization of the characteristic polynomial. The operator idea is important and it will be used again in the annihilator method.
- [75-88] Here we discuss how the Method of Undetermined Coefficients treats the nonhomogeneous constant coefficient ODE in many cases. I begin by outlining the method just for the n=2 case. However, we soon learn that to understand the choice of the particular solution we need knowledge of higher order (n > 2) DEqns in order to apply the annihilator method. The really neat thing is we can take the given nonhomogeneous problem and convert it to a corresponding homogeneous problem which we know how to solve in all possible cases already. This is nice because it takes the guesswork out of finding the particular solution Yp. Once we find the right form for Yp then it is just a matter of algebra to determine the undetermined coefficients A,B,C etc... Finally, on pages 85-86 I revisit the question of linear independence yet again and I try to explain why it is we need both Yh and Yp to form the general solution.
- [89-90] Variation of Parameters is a slight generalization of the Method of Undetermined Coefficents. Instead of looking for undetermined constants we look for undetermined functions. The method boils down to calculating Eqn (10) once you find the fundamental solution set. You should reserve Variation of Parameters as a method of last resort, if undetermined coefficients works it's much easier. Variation of Parameters is quite general, it even applies to DEqns with variable coefficients like xy''+cos(x)y'-y = exp(x). I can't ask many such problems at this point because we have no method to even calculate the fundamental solution set. There are precious few linear ODEs with easy to find fundamental solution sets ( see Problem 23 for how to create new DEqns which have formulas sort-of like the constant coefficient case).
- [91-93] The superposition principle states that the response of a linear system is the sum of the responses to each external force, or current, or voltage etc... Mathematically, it means we can break down a complicated sum of nonhomogeneous terms and treat each summand independently. This is very labor saving for certain examples.
- [94-101] The n=2 Cauchy Euler problem is solved and several examples are provided. Generally variable coefficient linear ODEs are not so easy to solve but the Cauchy Euler problem actually amounts to P(xD)[y]=0 so the same operator arguments we made for the constant coefficient case transfer over to the situation here. However, the eigenfunctions and generalized eigenfunctions of xD differ from that of D so the solutions look quite different. We also discuss Reduction of Order on pages 96-97. Reduction of order gives us a general method for calculating a second linearly independent function given we already have calculated the first solution. Reduction of order probably gives the most satisfying answer as to where the x comes from in the double root solution xexp(rx).
- [102-108] We apply the mathematics for solving n-th order constant coefficienct ODEs to two common real world applications: the RLC circuit and the spring-mass system with damping. We provide analysis of how a given system will respond to various different external forces or voltages. It turns out there is a certain frequency which makes for the largest long term current or motion for the system, this frequency is called the resonant frequency. In the special case of pure, un-damped, harmonic motion the result of coupling a system to a resonant source is catastrophic without doubt (see E95 for the math). Unfortunately pure harmonic motion is impossible fro physical springs or circuits since friction and resistance are inevitable.
- [i-12i] Complex Math Appendix.

- [109-114] Laplace Transform is motivated and defined, just kidding motivation is up to you.
- [115-121] Additional Theorems for Laplace Transform are given, we see how to deal with derivatives and more... I provide proofs for some of the Theorems, usually it's not that hard. Basically you just start with the definition and do calculus.
- [122-126] Inverse Laplace Transforms are discussed here. For successful calculation you need both a mastery of partial fractions algebra and an complete and working knowledge of the known Laplace Transforms.
- [127-133] We finally get to the point of the Chapter. We can solve differential equations via the Laplace technique ( see page 127 for a flow-chart of the logic ). E130 and E131 show that we can also treat problems where the "initial" conditions are not at zero, it's a good trick to know about. Finally E132 shows how Laplace Transforms can be used to solve variable coefficient problems in some cases, the math in the "frequency" or "s-domain" is unusual in that it is not just algebra, we actually have to do calculus to solve for Y(s) ( in contrast the constant-coeff. problems give us an algebra problem in the s-domain ). Honestly, I do not recommend Laplace transforms for solving variable coefficient problems in general, solution via series techniques is much more promising.
- [134-140] Laplace Transforms of discontinuous functions and periodic functions are discussed. The Gamma Function is defined and used to help quantify the transform of non-integer powers of t. Pages 134-136 are the most crucial parts of these notes since we are not covering periodic functions as part of the required material. You should pay particular attention to the formulation of piecewise-defined functions in terms of the unit-step (also called the Heaviside function). The unit-step functions allow us to write formulas which cover multiple cases with a single formula.
- [141-143] Convolution products allow us to break up inverse transforms of product. The cost is that to find explicit formulas we have to complete certain integrals which can be tiresome at times. This is not part of the required material, however if you ever find you are using Laplace Transforms in a course I would urge you to come back and read this material then. Convolution is an important tool for harder problems.
- [145-154] The Dirac Delta Function is used to model forces which act in an instant of time, like a hammer hitting a nail. The impact of the hammer is spread over a very small time increment. Often we are not interested in the precise mechanism of how the nail is impacted by the hammer, instead we only care about the overal outcome. Namely the momentum that the nail is driven into the wood. The Dirac Delta function allows us to model such phenomenon. The delta functions are used in electromagnetism to model the charge density of a point charge. The mathematics we want is something that is zero everywhere except one point where it somehow integrates to a finite value for any region containing that point. This is in complete violation of the usual rules and properties of functions and their integrals, however this is not surprising since the Dirac Delta Function is in truth a "Distribution". The theory of distributions is beyond this course, but rest assured that there is a solid mathematical framework in which the Dirac Delta function finds a home. The infinite dimensional analogue of the Delta Function which one encounters in Quantum Field Theory is not so well justified, but people (physicists) use it anyway. I digress... I conclude these notes with a few hearty examples of how Dirac Delta functions and/or discontinuous forcing functions are naturally handled by the Laplace technique. To make these notes more interesting I should have reinterpreted one of the last examples in terms of and RLC circuit with some switches, the math is similar.
- [155-160] Power series provide a prolific tool to analyze a great variety of functions. Most functions we encounter are analytic, at least locally, so Taylor's Theorem guarantees we can represent a function by a sort of unending polynomial. I review a few of the basic notions from Calculus II. We discuss the IOC and ROC as well as how to manipulate series by addition, multiplication etc... Also I remind you we know certain standard examples by memory ( or we should ). I do not seek to over-emphasize issues of convergence in this course. We need at least the basics to keep out of trouble, but our overal emphasis is more on calculation. We'll leave existence for the mathematicians in most problems we work. I should mention we are being slightly sloppy on certain points in this regard. There is always a question as to whether or not a given series actually converges, and if so where. The text is much more careful than my notes on this issue.
- [161-165] I demonstrate how to solve DEqns via power series. The idea is simple, the details are not. To summarize,(1.) suppose the solution is a power series with unknown coefficients (2.) substitute solution into the DEqn (3.) solve the resulting recurrence equations for the unknown coefficients. It's interesting that homogeneous and nonhomogenous cases are treated the same way ( however, the nonhomogeneous case will produce terms in the solution which do not depend on an arbitrary constant, those terms are the particular solution naturally)
- [166-170] Singular points are defined. We cannot hope to find series solutions around a singular point in general. However, certain singularities are called "regular" if they are not too bad. Not too bad in the sense that the Method of Frobenius will provide solutions near such points.
- [171-178] The Method of Frobenius is nontrivial. It provides solutions for DEqns with regular singular points. These are not power series solutions in all cases. There are essentially three cases that can happen and it is all based on an intuitive generalization of the Cauchy-Euler problem. We do not treat the complex case in these notes. I combine sections 8.6 and 8.7 into a uniform discussion.

- I'm leaving this one for the text. I do have over 40 pages of grueling homework solutions on these problems and I'm going to leave it at that for now. If I was lecturing in person I would probably solve a wave-guide problem from electromagnetics and if I was sufficiently rested we might work out the hydrogen atom. The main thing keeping me from doing better and more interesting examples is a lack of proficiency with special functions. In general if we tackle interesting problems with some sort of curved geometry we will need to learn how to solve a new type of ODEn. I don't think I'll find the time this summer to do it justice. So, we'll stick to the text with it's standard heat and wave equations. The general idea stays the same for other equations so if you master the problems I've assigned it should give you a good basis for trying harder problems. Also, I have not delved too deeply into weirder boundary conditions. Different cases require various tricks, in fact it is not unusual to take a whole semester to unravel the quirks. Again, our goal here is just to get you started. I think you'll find the assigned problems challenge enough.
- There is no in-class test for this part of the class, I am relegating it all to the Problem Set IV and then to Test IV which is a reworking of Problem Set IV.

It is possible to earn bonus points by asking particularly good questions or suggesting corrections to errors in notes and materials on the course website. This does not include spelling or grammatical errors, those are provided for your amusement.

There are 4 Problem Sets which will be collected. These consist about 70% of standard example problems which are not terribly difficult once you understand the concept and about 30% that is harder and/or abstract. I have provided solutions for problems like the standard examples. The practice homework is not collected but it is representative of the skill set I expect you should assimilate as the course unfolds. This summer Problem Set IV and Test IV are identical. Test IV is 100% takehome. The final exam covers those things covered by Tests I,II, III as well as theory which I hope you have assimilated by the end of the course.

(these links will work once I post the assignments for this semester)

- [due Sept 4] Problem Set I: first order and homogeneous differential equations (Test 1 is Sept. 8)
- [due Sept 25] Problem Set II: nonhomogeneous differential equations (Test 1 is Sept. 29)
- [due Oct 30] Problem Set III: Laplace transforms and series solutions to differential equations (Test 1 is Nov. 3)
- [due Dec 3] Problem Set IV: separation of variables and Fourier series for solving boundary value problems

(the * problems indicate the problem is explicitly about a real-world application. However, all the problems in this course are real world since you are in the real world and you will be doing the problems. Besides that obvious comment, all the mathematics mentioned in this course is used in engineering, physics and much much more... if you want to see more of that add a physics minor or an engineering major. My focus is math.)

Section # |
My Lecture Notes |
Solutions |
Assignment |
Description / Hints / Mathematica helps |

Sec. 2.2 | [13-23] | PH-[1-3] | 9, 11, 15, 21, 25, 35* | separation of variables |

Sec. 2.3 | [24-28] | PH-[4-6] | 7, 9, 11, 15, 21, 23* | integrating factor method |

Sec. 2.4 | [24-28] | PH-[7-9] | 11, 13, 17, 23, 29 | exact equations |

Sec. 2.5 | [29-37] | PH-[10-13] | 7, 9, 11, 13 | special integrating factors |

Sec. 2.6 | [29-37] | PH-[14-16] | 9, 15, 17, 41 | transformation tricks |

Sec. 3.4 | [41-45] | PH-[17-21] | 1*, 5*, 19*, 23*, 33*, 35* | Newtonian Mechanics |

Sec. 4.2 | [46-55] | PH-[22-23] | 1, 5, 13, 17, 27, 29 | homogeneous constant coefficient ordinary differential equations with real roots |

Sec. 4.3 | [46-55] | PH-[24-26] | 1, 5, 13, 21, 32*, 33*, 35* | homogeneous constant coefficient ordinary differential equations with complex roots |

Sec. 6.2 | [46-55] | PH-[27-30] | 1, 9, 13, 15, 17, 35* | higher order homogeneous constant coefficient ODEs. |

Event | Test I | Sept. 8 | Sections 2.2, 2.3, 2.4, 2.5, 2.6, 3.4, 4.2, 4.3, 6.2 | solutions of first order differential equations and homogeneous constant coefficient ODEs. |

Sec. 6.1 | [56-65] | PH-[31-33] | 1, 5, 7, 9, 17, 23 | theory of linear ODEs. |

Sec. 6.3 | [75-88] | PH-[34-37] | 5, 11, 13, 15, 17, 21, 23, 25, 27 | annihilators; a way to find the particular solution. |

Sec. 4.4 | [75-88] | PH-[38-39] | 9, 11, 15, 17, 21, 23, 27, 31 | undetermined coefficients ( section 6.3 justifies where the guess for the particular solution comes from). |

Sec. 4.5 | [91-93] | PH-[40-43] | 1, 3, 17, 21, 25, 29, 43* | superposition principle. |

Sec. 4.6 | [89-90] | PH-[44-48] | 1, 5, 15 | variation of parameters ( for things not covered by undetermined coefficients) |

Sec. 4.7 | [94-101] | PH-[49-50] | 45, 47 | variable coeffcients. |

Sec. 4.9 | [102-108] | PH-[51-52] | 3, 5, 9*, 11* [use math software for #3 and 5] | springs and vibrations. |

Sec. 4.10 | [102-108] | PH-[53-58] | 9*, 11* | forced vibrations. |

Sec. 5.7 | [102-108] | PH-[59-62] | 3*, 5*, 7*, 9*, 11*, 13* | RLC circuits and the analogy to springs with forced vibrations |

Event | Test II | Sept. 29 | Sections 6.1, 6.3, 4.4, 4.5, 4.6, 4.7, 4.9, 4.10, 5.7 | solutions of nonhomogeneous constant coefficient ODEs and select applications to springs and RLC circuits, variable coefficient DEqns. |

Sec. 7.2 | [109-114] | PH-[63-64] | 9, 13, 15, 17, 19, 21, 23 | Laplace Transformations |

Sec. 7.3 | [115-121] | PH-[65-66] | 5, 7, 11, 13, 15, 17, 19, 25 | Properties of Laplace Transformations |

Sec. 7.4 | [122-126] | PH-[67-71] | 1, 3, 21, 23, 27, 33, 35 | Inverse Laplace Transformations |

Sec. 7.5 | [127-133] | PH-[72-76] | 3, 9, 11, 35 | How to solve differential equations via Laplace Transformations |

Sec. 7.6 | [134-140] | PH-[77-81] | 5, 7, 9, 11, 17, 19, 33, 39, 59 | discontinuous functions (this is most interesting feature of the Laplace method in my opinion) |

Sec. 7.8 | [145-154] | PH-[82-84] | 1, 5, 29 | Dirac Delta "functions" |

Sec. 8.2 | [155-160] | PH-[85-89] | 1, 5, 9, 11, 15, 25, 29, 31, 33 | power series refresher |

Sec. 8.3 | [161-165] | PH-[90-97] | 1, 9, 13, 17, 19, 21, 27 | power series solutions to DEqns |

Sec. 8.4 | [166-170] | PH-[98-103] | 7, 11, 13, 17, 21, 31* | analytic coefficients |

Sec. 8.5 | [94-101] | PH-[104-105] | 1, 5, 13 | Cauchy-Euler Problem |

Sec. 8.6 | [171-178] | PH-[106-114] | 1, 17, 21, 23, 25, 27, 33, 41 | Frobenius method |

Sec. 8.7 | [171-178] | PH-[106-114] | 5, 11, 15 (note to self, find Ginny solution) | finding a second linearly independent solution |

Event | Test III | Nov. 3 | Sections 7.2, 7.3, 7.4, 7.5, 7.6, 7.8, 8.2, 8.3, 8.4, 8.6, 8.7 | Laplace transform and series solutions to ODEs |

Sec. 10.2 | . | PH-[118-126] | 1, 5, 9, 13, 15, 21, 23, 29, 33 | separation of variables for PDEs with nice boundary conditions |

Sec. 10.3 | . | PH-[127-132] | 1, 5, 7, 9, 11, 13, 19, 21, 29 | Fourier series |

Sec. 10.4 | . | PH-[133-134] | 5, 13, 17 | Fourier cosine and sine series |

Sec. 10.5 | . | PH-[135-144] | 3, 7, 15 | the heat equation |

Sec. 10.6 | . | PH-[145-149] | 1, 13, 15 | the wave equation |

Sec. 10.7 | . | PH-[150-161] | 1, 3, 7, 9, 11 | Laplace's equation |

Event | Test IV | take-home | Sections 10.2, 10.3, 10.4, 10.5, 10.6, 10.7 | PDEs with nice solutions. |

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7 . PH-[150-161] 1, 3, 7, 9, 11 Laplace's equation Event Test IV take-home Sections 10.2, 10.3, 10.4, 10.5, 10.6, 10.7 PDEs with nice solutions.

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