Physics 116C Solution of inhomogeneous differential equations using Green functions
|
|
- Dana Webb
- 7 years ago
- Views:
Transcription
1 Physics 6C Solution of inhomogeneous differential equations using Green functions Peter Young November 8, 23 Introduction In this handout we give an introduction to Green function techniques for solving inhomogeneous differential equations. We will concentrate on the simpler case of ordinary differential equations, but will also discuss partial differential equations briefly at the end. For this year, 23, I will not require Secs. 6 and 7 for the exams of homework, but I recommend that you read them for your general interest. 2 Inhomogeneous Equations A homogeneous linear ordinary differential equation can be written Ly(x) =, () where L is an operator involving derivatives with respect to x. Green functions, the topic of this handout, appear when we consider the inhomogeneous equation analogous to Eq. () Ly(x) = f(x), (2) where f(x) is some specified function of x. We require the solution for some specified boundary conditions. The idea of the method is to determine the Green function, G(x,x ), which is given by the solution of this equation with a particular right hand side, namely a delta function, i.e. LG(x,x ) = δ(x x ). (3) In Eq. (3), the differential operators in L act on x, and x is a constant. Once G has been determined, the solution of Eq. (2) can be obtained for any function f(x) from y(x) = G(x,x )f(x )dx, (4) which follows since Ly(x) = L G(x,x )f(x )dx = δ(x x )f(x )dx = f(x), (5) so y(x) satisfies Eq, (2) as required. Note that we used Eq. (3) to obtain the second equality in Eq. (5). We emphasize that the same Green function applies for any f(x), and so it only has to be calculated once for a given differential operator L and boundary conditions.
2 3 Eigenvalues of ODEs We have studied, especially in a long HW problem, second order linear ordinary differential equations which can be written as an eigenvalue problem of the form Ly n (x) = λ n y n (x), (6) where L is the same operator involving derivatives as in Eqs. () and (2), λ n is an eigenvalue and y n (x) is an eigenfunction (which satisfies some specified boundary conditions). Note that Eqs. (6) and (2) have the same left hand side but different right hand sides. In Eq. (2) the right hand side is a specified function of x, whereas in Eq. (6) the right hand side is proportional to the function being determined y(x). The general case that we are interested in is called a Sturm-Liouville problem, for which one can show that the eigenvalues are real, and the eigenfunctions are orthogonal, i.e. b a y n (x)y m (x)dx = δ nm, (7) where a and b are the upper and lower limits of the region where we are solving the problem, and we have also normalized the solutions. A simple example, which we will study in detail, will be 2 y + 4y = λy, (8) in the interval x π, with the boundary conditions y() = y(π) =. This corresponds to L = d2 dx (9) This is just the simple harmonic oscillator equation, and so the solutions are coskx and sinkx. The boundary condition y() = eliminates coskx and the condition y(π) = gives k = n a positive integer. (Note: For n = the solution vanishes and taking n < just gives the same solution as that for the corresponding positive value of n because sin( nx) = sin(nx). Hence we only need consider positive integer n.) The normalized eigenfunctions are therefore 2 y n (x) = sinnx, (n =,2,3, ), () π and the eigenvalues in Eq. (8) are λ n = 4 n2, () since the equation satisfied by y n (x) is y n +n 2 y n =. 4 Expression for the Green functions in terms of eigenfunctions In this section we will obtain an expression for the Green function in terms of the eigenfunctions y n (x) in Eq. (6). The general Sturm-Liouville problem has a weight function w(x) multiplying the eigenvalue on the RHS of Eq. (6) and the same weight function multiplies the integrand shown in the LHS of the orthogonality and normalization condition, Eq. (7). Furthermore the eigenfunctions may be complex, in which case one must take the complex conjugate of either y n or y m in in Eq. (7). Here, to keep the notation simple, we will just consider examples with w(x) = and real eigenfunctions. 2 Different books adopt different sign conventions for the definition of L, and hence of the Green functions. 2
3 We assume that the solution y(x) of the inhomogeneous equation, Eq. (2), can be written as a linear combination of the eigenfunctions y n (x), obtained with the same boundary conditions, i.e. y(x) = n c n y n (x), (2) for some choice of the constants c n. Substituting into Eq. (2) gives f(x) = Ly(x) = n c n Ly n (x) = n c n λ n y n (x). (3) To determine the c n we multiply by one of the eigenfunctions, y m (x) say, and integrate use the orthogonality of the eigenfunctions, Eq. (7). This gives b a f(x)y m (x)dx = n Substituting for c n into Eq. (2) gives y(x) = n λ n b c n λ n y n (x)y m (x)dx = c m λ m. (4) b which can be written in the form of Eq. (4) with a G(x,x ) = n a y n (x )f(x )dx y n (x), (5) λ n y n (x)y n (x ). (6) Note that G(x,x ) is a symmetric function of x and x which is a quite general result. Furthermore, it only depends on the eigenfunctions of the corresponding homogeneous equation, i.e. on the boundary conditions and L. It is independent of f(x) and so can be computed once and for all, and then applied to any f(x) just by doing the integral in Eq. (4). 5 Other boundary conditions We have chosen our Green function to have the boundary conditions of the desired solution. Suppose it was easier to find the Green function for some other boundary condition. How can we incorporate this solution into a Green function for the actual boundary condition? We have a Green function G, say, which satisfies boundary condition. This satisfies the equation LG (x,x ) = δ(x x ). (7) We also have a Green function G 2 for boundary condition 2 which satisfies the same equation, Subtracting these last two equations we get LG 2 (x,x ) = δ(x x ). (8) L [ G (x,x ) G 2 (x,x ) ] =, (9) so the difference, G G 2, satisfies the corresponding homogeneous equation. In other words the general expression for the Green function is G(x,x ) = G p (x,x )+F(x,x ), (2) where G p (x,x ) is a particular solution of the inhomogeneous equation, Eq. (3), while F(x,x ) is a solution of corresponding homogeneous equation chosen so that G satisfies the desired boundary conditions. In fact, you have already know that the general solution of an inhomogeneous differential equation is the sum of a particular solution of the inhomogeneous equation, plus a solution of the homogeneous equation chosen to satisfy the boundary conditions. Equation (2) is an example of this. 3
4 6 A simple example As an example of the use of Green functions let us determine the solution of the inhomogeneous equation corresponding to the homogeneous equation in Eq. (8), i.e. y + 4y = f(x), with y() = y(π) =. (2) First we will evaluate the solution by elementary means for two choices of f(x) (i) f(x) = sin2x, (ii) f(x) = x/2. (22) We will then obtain the solutions for these cases from the Green function determined according to Eq. (6). In the elementary approach, one writes the solution of Eq. (2) as a combination of a complementary function y c (x) (the solution with f(x) = ) and the particular integral y p (x) (a particular solution with f(x) included). Since, for f(x) =, the equation is the simple harmonic oscillator equation, y c (x) is given by y c (x) = Acos(x/2)+Bsin(x/2). (23) For the particular integral, we assume that y p (x) is of a similar form to f(x). We now determine the solution for the two choices of f(x) in Eq. (2). (i) For f(x) = sin2x we try y p (x) = Ccos2x+Dsin2x and substituting gives ( 4+/4)D =, and C =. This gives y(x) = y c (x)+y p (x) = 4 sin2x+acos(x/2)+bsin(x/2). (24) 5 The boundary conditions are y() = y(π) =, which gives A = B =. Hence y(x) = 4 sin2x, for f(x) = sin2x. (25) 5 (ii) Similarly for f(x) = x we try y p (x) = C +Dx and substituting into Eq. (2) gives C =,D = 2, and so y(x) = y c (x)+y p (x) = 2x+Acos(x/2)+Bsin(x/2). (26) The boundary conditions, y() = y(π) =, give A =,B = 2π. Hence This is plotted in the figure below y(x) = 2x 2πsin(x/2), for f(x) = x/2. (27) 4
5 Now lets work out the Green function, which is given by Eq. (6). The eigenfunction are given by () and the eigenvalues are given by Eq. () so we have G(x,x ) = 2 π sinnx sinnx n=. (28) 4 n2 We can now substitute this into Eq. (4) to solve Eq. (2) for the two choices of f(x) in Eq. (22). (i) First of all for f(x) = sin2x Eq. (4) becomes y(x) = 2 ( π ) sinnx sinnx sin2x dx = 2 π 4 n2 π n= n= sinnx 4 n2 π sinnx sin2x dx. (29) Because of the orthogonality of the sinnx in the interval from to π only the n = 2 term contributes, and the integral for this case is π/2. Hence the solution is in agreement with Eq. (25). y(x) = sin2x 4 22 = 4 5 sin2x. (3) (ii) Now we consider the case of f(x) = x/2. Substituting Eq, (28) into Eq. (4) gives y(x) = π n= sinnx 4 n2 π x sinnx dx. (3) There is no longer any orthogonality to simplify things and we just have to do the integral: π x sinnx dx = [ x cosnx ] π π cosnx + dx (32) n n = πcosnπ [ ] sinnx π + n n 2 (33) = ( ) nπ n. (34) 5
6 For the particular case of n = the integral is zero. Hence the solution is y(x) = ( ) n+ sinnx n( 4 n2 ). (35) n= This may not look the same as Eq. (27), but it is in fact, as one can check by expanding 2x 2πsinx/2 as a Fourier sine series in the interval to π, i.e. one writes 2x 2πsinx/2 = c n sinnx, (36) n= and determines the c n from the usual Fourier integral. Using the Green function may seem to be a complicated way to proceed, especially for our second choice of f(x). However, you should realize that the elementary derivation of the solution may not be so simple in other cases, and you should note that the Green function applies to all possible choices of the function on the RHS, f(x). Furthermore, we will see in the next section that one can often get a closed form expression for G, rather than an infinite series. It is then much easier to find a closed form expression for the solution. 7 Closed form expression for the Green function In many useful cases, one can obtain a closed form expression for the Green function by starting with the defining equation, Eq. (3). We will illustrate this for the example in the previous section for which Eq. (3) is G + 4 G = δ(x x ). (37) Remember that x is fixed (and lies between and π) while x is a variable, and the derivatives are with respect to x. We solve this equation separately in the two regions (i) x < x, and (ii) x < x π. In each region separately the equation is G +(/4)G =, for which the solutions are G(x,x ) = Acos(x/2)+Bsin(x/2), (38) where A and B will depend on x. Since y() =, we require G(,x ) = (recall Eq. (4)) and so, for the solution in the region x < x, the cosine is eliminated. Similarly G(π,x ) = and so, for the region x < x π, the sine is eliminated. Hence the solution is G(x,x ) = { Bsin(x/2) ( x < x ), Acos(x/2) (x < x π). (39) How do we determine the two coefficients A and B? We get one relation between them by requiring that the solution is continuous at x = x, i.e. the limit as x x from below is equal to the limit as x x from above. This gives Bsin(x /2) = Acos(x /2). (4) The second relation between A and B is obtained by integrating Eq. (37) from x = x ǫ to x +ǫ, and taking the limit ǫ, which gives so lim ǫ [ ] dg x +ǫ dx x ǫ + 4 lim ǫ lim ǫ ( dg dx x +ǫ x ǫ x +ǫ G(x,x )dx = lim dg dx x ǫ ǫ x +ǫ x ǫ δ(x x )dx (4) ) + =. (42) 6
7 Hence dg/dx has a discontinuity of at x = x, i.e. A 2 sin(x /2) B 2 cos(x /2) =. (43) Solving Eqs. (4) and (43) gives Substituting into Eq. (39) gives B = 2cos(x /2), (44) A = 2sin(x /2). (45) G(x,x ) = { 2cos(x /2)sin(x/2) ( x < x ), 2sin(x /2)cos(x/2) (x < x π). (46) A sketch of the solution is shown in the figure below. The discontinuity in slope at x = x (I took x = 3π/4) is clearly seen. It is instructive to rewrite Eq. (46) in terms of x <, the smaller of x and x, and x >, the larger of x and x. One has G(x,x ) = 2sin(x < /2)cos(x > /2), (47) irrespective of which is larger, which shows that G is symmetric under interchange of x and x as noted earlier. We now apply the closed form expression for G in Eq. (46) to solve our simple example, Eq. (2), with the two choices for f(x) shown in Eq. (22). (i) For f(x) = sin2x, Eqs. (4) and (46) give y(x) = 2cos(x/2) x sin2x sin(x /2)dx 2sin(x/2) Using formulae for sines and cosines of sums of angles and integrating gives ( sin(3x/2) y(x) = 2cos(x/2) sin(5x/2) ) ( cos(3x/2) 2sin(x/2) ( ) ( ) = 2 3 sin2x +2 5 sin2x π x sin2x cos(x /2)dx. (48) + cos(5x/2) ) (49) 5 (5) = 4 5 sin2x, (5) 7
8 where we again used formulae for sums and differences of angles. This result is in agreement with Eq. (25). (ii) For f(x) = x/2, Eqs. (4) and (46) give y(x) = cos(x/2) Integrating by parts gives x x sin(x /2)dx sin(x/2) π x x cos(x /2)dx (52) y(x) = cos(x/2)( 2xcos(x/2)+4sin(x/2)) sin(x/2)(2π 4cos(x/2) 2xsin(x/2)), (53) = 2x 2πsin(x/2), which agrees with Eq. (27). Note that we obtained the closed form result explicitly, as opposed to the method in Sec. 4 where the solution was obtained as an infinite series, Eq. (35). In general, to find a closed form expression for G(x,x ) we note from Eq. (3) that, for x x, it satisfies the homogeneous equation (54) LG(x,x ) =, (x x ). (55) We solve this equation separately for x < x and x > x, subject to the required boundary conditions, and match the solutions at x = x with the following two conditions (i) G(x,x ) is continuous at x = x, i.e. (ii) The derivative dg/dx has a discontinuity of at x = x, i.e. 8 Summary and PDE s lim x x +ǫ G(x,x ) = lim x x ǫ G(x,x ). (56) dg(x,x ) dg(x,x ) lim lim =. (57) x x +ǫ dx x x ǫ dx We have shown how to solve linear, inhomogeneous, ordinary differential equations by using Green functions. These can be represented in terms of eigenfunctions, see Sec. 4, and in many cases can alternatively be evaluated in closed form, see Secs. 6 and 7. The advantage of the Green function approach is that the Green function only needs to be computed once for a given differential operator L and boundary conditions, and this result can then be used to solve for any function f(x) on the RHS of Eq. (2) by using Eq. (4). So far we have used Green function techniques for ordinary differential equations. They can also be used, in a very similar manner, for partial differential equations. In particular, if we consider Poisson s equation, 2 y( r) = f( r), (58) the solution can be written as where the Green function satisfies y( r) = d r G( r, r )f( r ), (59) 2 G( r, r ) = δ (3)( r r ), (6) 8
9 in which the derivatives are with respect to the components of r, and the three-dimensional delta function is a product of three Dirac delta functions The Green function for this problem is given by δ (3)( r r ) = δ(x x )δ(y y )δ(z z ). (6) G( r, r ) = 4π r r +F( r, r ), (62) where F( r, r ) is a solution of Laplace s equation chosen so satisfy the boundary conditions, see e.g. Boas 3.8. To obtain in the /4π r r term in Eq. (62) one can argue physically that Eq. (6) is the equation for the potential at r due to a point charge at r and we know that this is given by Coulomb s law. From Eq. (62) it follows that the solution of Poisson s equation, Eq. (58) is y( r) = d r f( r ) 4π r r +H( r), (63) where H( r) is a solution of Laplace s equation chosen to satisfy the boundary conditions. While the advantages of Green functions may not be readily apparent from the simple examples presented here, they are used in many advanced applications in physics. 9
MATH 425, PRACTICE FINAL EXAM SOLUTIONS.
MATH 45, PRACTICE FINAL EXAM SOLUTIONS. Exercise. a Is the operator L defined on smooth functions of x, y by L u := u xx + cosu linear? b Does the answer change if we replace the operator L by the operator
More informationUsing a table of derivatives
Using a table of derivatives In this unit we construct a Table of Derivatives of commonly occurring functions. This is done using the knowledge gained in previous units on differentiation from first principles.
More informationIntroduction to Complex Fourier Series
Introduction to Complex Fourier Series Nathan Pflueger 1 December 2014 Fourier series come in two flavors. What we have studied so far are called real Fourier series: these decompose a given periodic function
More informationDifferentiation and Integration
This material is a supplement to Appendix G of Stewart. You should read the appendix, except the last section on complex exponentials, before this material. Differentiation and Integration Suppose we have
More information14.1. Basic Concepts of Integration. Introduction. Prerequisites. Learning Outcomes. Learning Style
Basic Concepts of Integration 14.1 Introduction When a function f(x) is known we can differentiate it to obtain its derivative df. The reverse dx process is to obtain the function f(x) from knowledge of
More informationA Brief Review of Elementary Ordinary Differential Equations
1 A Brief Review of Elementary Ordinary Differential Equations At various points in the material we will be covering, we will need to recall and use material normally covered in an elementary course on
More informationTaylor and Maclaurin Series
Taylor and Maclaurin Series In the preceding section we were able to find power series representations for a certain restricted class of functions. Here we investigate more general problems: Which functions
More informationCalculus 1: Sample Questions, Final Exam, Solutions
Calculus : Sample Questions, Final Exam, Solutions. Short answer. Put your answer in the blank. NO PARTIAL CREDIT! (a) (b) (c) (d) (e) e 3 e Evaluate dx. Your answer should be in the x form of an integer.
More informationIntegrals of Rational Functions
Integrals of Rational Functions Scott R. Fulton Overview A rational function has the form where p and q are polynomials. For example, r(x) = p(x) q(x) f(x) = x2 3 x 4 + 3, g(t) = t6 + 4t 2 3, 7t 5 + 3t
More informationSecond Order Linear Partial Differential Equations. Part I
Second Order Linear Partial Differential Equations Part I Second linear partial differential equations; Separation of Variables; - point boundary value problems; Eigenvalues and Eigenfunctions Introduction
More informationNonhomogeneous Linear Equations
Nonhomogeneous Linear Equations In this section we learn how to solve second-order nonhomogeneous linear differential equations with constant coefficients, that is, equations of the form ay by cy G x where
More informationInner Product Spaces
Math 571 Inner Product Spaces 1. Preliminaries An inner product space is a vector space V along with a function, called an inner product which associates each pair of vectors u, v with a scalar u, v, and
More informationCHAPTER 2. Eigenvalue Problems (EVP s) for ODE s
A SERIES OF CLASS NOTES FOR 005-006 TO INTRODUCE LINEAR AND NONLINEAR PROBLEMS TO ENGINEERS, SCIENTISTS, AND APPLIED MATHEMATICIANS DE CLASS NOTES 4 A COLLECTION OF HANDOUTS ON PARTIAL DIFFERENTIAL EQUATIONS
More informationTMA4213/4215 Matematikk 4M/N Vår 2013
Norges teknisk naturvitenskapelige universitet Institutt for matematiske fag TMA43/45 Matematikk 4M/N Vår 3 Løsningsforslag Øving a) The Fourier series of the signal is f(x) =.4 cos ( 4 L x) +cos ( 5 L
More informationClass Meeting # 1: Introduction to PDEs
MATH 18.152 COURSE NOTES - CLASS MEETING # 1 18.152 Introduction to PDEs, Fall 2011 Professor: Jared Speck Class Meeting # 1: Introduction to PDEs 1. What is a PDE? We will be studying functions u = u(x
More informationarxiv:1201.6059v2 [physics.class-ph] 27 Aug 2012
Green s functions for Neumann boundary conditions Jerrold Franklin Department of Physics, Temple University, Philadelphia, PA 19122-682 arxiv:121.659v2 [physics.class-ph] 27 Aug 212 (Dated: August 28,
More informationThe one dimensional heat equation: Neumann and Robin boundary conditions
The one dimensional heat equation: Neumann and Robin boundary conditions Ryan C. Trinity University Partial Differential Equations February 28, 2012 with Neumann boundary conditions Our goal is to solve:
More informationIntegration by substitution
Integration by substitution There are occasions when it is possible to perform an apparently difficult piece of integration by first making a substitution. This has the effect of changing the variable
More informationMethod of Green s Functions
Method of Green s Functions 8.303 Linear Partial ifferential Equations Matthew J. Hancock Fall 006 We introduce another powerful method of solving PEs. First, we need to consider some preliminary definitions
More informationy cos 3 x dx y cos 2 x cos x dx y 1 sin 2 x cos x dx
Trigonometric Integrals In this section we use trigonometric identities to integrate certain combinations of trigonometric functions. We start with powers of sine and cosine. EXAMPLE Evaluate cos 3 x dx.
More informationSolutions to Homework 10
Solutions to Homework 1 Section 7., exercise # 1 (b,d): (b) Compute the value of R f dv, where f(x, y) = y/x and R = [1, 3] [, 4]. Solution: Since f is continuous over R, f is integrable over R. Let x
More informationChapter 9. Systems of Linear Equations
Chapter 9. Systems of Linear Equations 9.1. Solve Systems of Linear Equations by Graphing KYOTE Standards: CR 21; CA 13 In this section we discuss how to solve systems of two linear equations in two variables
More informationSecond-Order Linear Differential Equations
Second-Order Linear Differential Equations A second-order linear differential equation has the form 1 Px d 2 y dx 2 dy Qx dx Rxy Gx where P, Q, R, and G are continuous functions. We saw in Section 7.1
More informationRepresentation of functions as power series
Representation of functions as power series Dr. Philippe B. Laval Kennesaw State University November 9, 008 Abstract This document is a summary of the theory and techniques used to represent functions
More information1. First-order Ordinary Differential Equations
Advanced Engineering Mathematics 1. First-order ODEs 1 1. First-order Ordinary Differential Equations 1.1 Basic concept and ideas 1.2 Geometrical meaning of direction fields 1.3 Separable differential
More information1 if 1 x 0 1 if 0 x 1
Chapter 3 Continuity In this chapter we begin by defining the fundamental notion of continuity for real valued functions of a single real variable. When trying to decide whether a given function is or
More informationSection 12.6: Directional Derivatives and the Gradient Vector
Section 26: Directional Derivatives and the Gradient Vector Recall that if f is a differentiable function of x and y and z = f(x, y), then the partial derivatives f x (x, y) and f y (x, y) give the rate
More informationImplicit Differentiation
Implicit Differentiation Sometimes functions are given not in the form y = f(x) but in a more complicated form in which it is difficult or impossible to express y explicitly in terms of x. Such functions
More informationSecond Order Linear Differential Equations
CHAPTER 2 Second Order Linear Differential Equations 2.. Homogeneous Equations A differential equation is a relation involving variables x y y y. A solution is a function f x such that the substitution
More informationI. Pointwise convergence
MATH 40 - NOTES Sequences of functions Pointwise and Uniform Convergence Fall 2005 Previously, we have studied sequences of real numbers. Now we discuss the topic of sequences of real valued functions.
More informationSeries FOURIER SERIES. Graham S McDonald. A self-contained Tutorial Module for learning the technique of Fourier series analysis
Series FOURIER SERIES Graham S McDonald A self-contained Tutorial Module for learning the technique of Fourier series analysis Table of contents Begin Tutorial c 004 g.s.mcdonald@salford.ac.uk 1. Theory.
More information3. INNER PRODUCT SPACES
. INNER PRODUCT SPACES.. Definition So far we have studied abstract vector spaces. These are a generalisation of the geometric spaces R and R. But these have more structure than just that of a vector space.
More informationApplication of Fourier Transform to PDE (I) Fourier Sine Transform (application to PDEs defined on a semi-infinite domain)
Application of Fourier Transform to PDE (I) Fourier Sine Transform (application to PDEs defined on a semi-infinite domain) The Fourier Sine Transform pair are F. T. : U = 2/ u x sin x dx, denoted as U
More informationtegrals as General & Particular Solutions
tegrals as General & Particular Solutions dy dx = f(x) General Solution: y(x) = f(x) dx + C Particular Solution: dy dx = f(x), y(x 0) = y 0 Examples: 1) dy dx = (x 2)2 ;y(2) = 1; 2) dy ;y(0) = 0; 3) dx
More information5 Numerical Differentiation
D. Levy 5 Numerical Differentiation 5. Basic Concepts This chapter deals with numerical approximations of derivatives. The first questions that comes up to mind is: why do we need to approximate derivatives
More informationSeparable First Order Differential Equations
Separable First Order Differential Equations Form of Separable Equations which take the form = gx hy or These are differential equations = gxĥy, where gx is a continuous function of x and hy is a continuously
More informationAlgebraic expressions are a combination of numbers and variables. Here are examples of some basic algebraic expressions.
Page 1 of 13 Review of Linear Expressions and Equations Skills involving linear equations can be divided into the following groups: Simplifying algebraic expressions. Linear expressions. Solving linear
More information4.3 Lagrange Approximation
206 CHAP. 4 INTERPOLATION AND POLYNOMIAL APPROXIMATION Lagrange Polynomial Approximation 4.3 Lagrange Approximation Interpolation means to estimate a missing function value by taking a weighted average
More informationFactoring Quadratic Expressions
Factoring the trinomial ax 2 + bx + c when a = 1 A trinomial in the form x 2 + bx + c can be factored to equal (x + m)(x + n) when the product of m x n equals c and the sum of m + n equals b. (Note: the
More informationPUTNAM TRAINING POLYNOMIALS. Exercises 1. Find a polynomial with integral coefficients whose zeros include 2 + 5.
PUTNAM TRAINING POLYNOMIALS (Last updated: November 17, 2015) Remark. This is a list of exercises on polynomials. Miguel A. Lerma Exercises 1. Find a polynomial with integral coefficients whose zeros include
More informationLinear Algebra Notes for Marsden and Tromba Vector Calculus
Linear Algebra Notes for Marsden and Tromba Vector Calculus n-dimensional Euclidean Space and Matrices Definition of n space As was learned in Math b, a point in Euclidean three space can be thought of
More informationa cos x + b sin x = R cos(x α)
a cos x + b sin x = R cos(x α) In this unit we explore how the sum of two trigonometric functions, e.g. cos x + 4 sin x, can be expressed as a single trigonometric function. Having the ability to do this
More informationSOLUTIONS. f x = 6x 2 6xy 24x, f y = 3x 2 6y. To find the critical points, we solve
SOLUTIONS Problem. Find the critical points of the function f(x, y = 2x 3 3x 2 y 2x 2 3y 2 and determine their type i.e. local min/local max/saddle point. Are there any global min/max? Partial derivatives
More information1 TRIGONOMETRY. 1.0 Introduction. 1.1 Sum and product formulae. Objectives
TRIGONOMETRY Chapter Trigonometry Objectives After studying this chapter you should be able to handle with confidence a wide range of trigonometric identities; be able to express linear combinations of
More informationAn Introduction to Partial Differential Equations in the Undergraduate Curriculum
An Introduction to Partial Differential Equations in the Undergraduate Curriculum J. Tolosa & M. Vajiac LECTURE 11 Laplace s Equation in a Disk 11.1. Outline of Lecture The Laplacian in Polar Coordinates
More informationLectures 5-6: Taylor Series
Math 1d Instructor: Padraic Bartlett Lectures 5-: Taylor Series Weeks 5- Caltech 213 1 Taylor Polynomials and Series As we saw in week 4, power series are remarkably nice objects to work with. In particular,
More informationSIGNAL PROCESSING & SIMULATION NEWSLETTER
1 of 10 1/25/2008 3:38 AM SIGNAL PROCESSING & SIMULATION NEWSLETTER Note: This is not a particularly interesting topic for anyone other than those who ar e involved in simulation. So if you have difficulty
More informationLS.6 Solution Matrices
LS.6 Solution Matrices In the literature, solutions to linear systems often are expressed using square matrices rather than vectors. You need to get used to the terminology. As before, we state the definitions
More informationLecture Notes on PDE s: Separation of Variables and Orthogonality
Lecture Notes on PDE s: Separation of Variables and Orthogonality Richard H. Rand Dept. Theoretical & Applied Mechanics Cornell University Ithaca NY 14853 rhr2@cornell.edu http://audiophile.tam.cornell.edu/randdocs/
More informationSystems with Persistent Memory: the Observation Inequality Problems and Solutions
Chapter 6 Systems with Persistent Memory: the Observation Inequality Problems and Solutions Facts that are recalled in the problems wt) = ut) + 1 c A 1 s ] R c t s)) hws) + Ks r)wr)dr ds. 6.1) w = w +
More information4.5 Linear Dependence and Linear Independence
4.5 Linear Dependence and Linear Independence 267 32. {v 1, v 2 }, where v 1, v 2 are collinear vectors in R 3. 33. Prove that if S and S are subsets of a vector space V such that S is a subset of S, then
More informationTRIGONOMETRY Compound & Double angle formulae
TRIGONOMETRY Compound & Double angle formulae In order to master this section you must first learn the formulae, even though they will be given to you on the matric formula sheet. We call these formulae
More informationIntroduction to Partial Differential Equations. John Douglas Moore
Introduction to Partial Differential Equations John Douglas Moore May 2, 2003 Preface Partial differential equations are often used to construct models of the most basic theories underlying physics and
More information2.2 Separable Equations
2.2 Separable Equations 73 2.2 Separable Equations An equation y = f(x, y) is called separable provided algebraic operations, usually multiplication, division and factorization, allow it to be written
More informationEuler s Formula Math 220
Euler s Formula Math 0 last change: Sept 3, 05 Complex numbers A complex number is an expression of the form x+iy where x and y are real numbers and i is the imaginary square root of. For example, + 3i
More information2.2 Magic with complex exponentials
2.2. MAGIC WITH COMPLEX EXPONENTIALS 97 2.2 Magic with complex exponentials We don t really know what aspects of complex variables you learned about in high school, so the goal here is to start more or
More informationy cos 3 x dx y cos 2 x cos x dx y 1 sin 2 x cos x dx y 1 u 2 du u 1 3u 3 C
Trigonometric Integrals In this section we use trigonometric identities to integrate certain combinations of trigonometric functions. We start with powers of sine and cosine. EXAMPLE Evaluate cos 3 x dx.
More informationUnit 7: Radical Functions & Rational Exponents
Date Period Unit 7: Radical Functions & Rational Exponents DAY 0 TOPIC Roots and Radical Expressions Multiplying and Dividing Radical Expressions Binomial Radical Expressions Rational Exponents 4 Solving
More informationx 2 + y 2 = 1 y 1 = x 2 + 2x y = x 2 + 2x + 1
Implicit Functions Defining Implicit Functions Up until now in this course, we have only talked about functions, which assign to every real number x in their domain exactly one real number f(x). The graphs
More informationTechniques of Integration
CHPTER 7 Techniques of Integration 7.. Substitution Integration, unlike differentiation, is more of an art-form than a collection of algorithms. Many problems in applied mathematics involve the integration
More informationSection 4.4. Using the Fundamental Theorem. Difference Equations to Differential Equations
Difference Equations to Differential Equations Section 4.4 Using the Fundamental Theorem As we saw in Section 4.3, using the Fundamental Theorem of Integral Calculus reduces the problem of evaluating a
More informationGeneral Theory of Differential Equations Sections 2.8, 3.1-3.2, 4.1
A B I L E N E C H R I S T I A N U N I V E R S I T Y Department of Mathematics General Theory of Differential Equations Sections 2.8, 3.1-3.2, 4.1 Dr. John Ehrke Department of Mathematics Fall 2012 Questions
More informationThe Matrix Elements of a 3 3 Orthogonal Matrix Revisited
Physics 116A Winter 2011 The Matrix Elements of a 3 3 Orthogonal Matrix Revisited 1. Introduction In a class handout entitled, Three-Dimensional Proper and Improper Rotation Matrices, I provided a derivation
More informationThe Heat Equation. Lectures INF2320 p. 1/88
The Heat Equation Lectures INF232 p. 1/88 Lectures INF232 p. 2/88 The Heat Equation We study the heat equation: u t = u xx for x (,1), t >, (1) u(,t) = u(1,t) = for t >, (2) u(x,) = f(x) for x (,1), (3)
More information2x + y = 3. Since the second equation is precisely the same as the first equation, it is enough to find x and y satisfying the system
1. Systems of linear equations We are interested in the solutions to systems of linear equations. A linear equation is of the form 3x 5y + 2z + w = 3. The key thing is that we don t multiply the variables
More informationScalar Valued Functions of Several Variables; the Gradient Vector
Scalar Valued Functions of Several Variables; the Gradient Vector Scalar Valued Functions vector valued function of n variables: Let us consider a scalar (i.e., numerical, rather than y = φ(x = φ(x 1,
More informationMath 241, Exam 1 Information.
Math 241, Exam 1 Information. 9/24/12, LC 310, 11:15-12:05. Exam 1 will be based on: Sections 12.1-12.5, 14.1-14.3. The corresponding assigned homework problems (see http://www.math.sc.edu/ boylan/sccourses/241fa12/241.html)
More informationChapter. Numerical Calculations
Chapter 3 Numerical Calculations 3-1 Before Performing a Calculation 3-2 Differential Calculations 3-3 Quadratic Differential Calculations 3-4 Integration Calculations 3-5 Maximum/Minimum Value Calculations
More information2.3. Finding polynomial functions. An Introduction:
2.3. Finding polynomial functions. An Introduction: As is usually the case when learning a new concept in mathematics, the new concept is the reverse of the previous one. Remember how you first learned
More information1.5. Factorisation. Introduction. Prerequisites. Learning Outcomes. Learning Style
Factorisation 1.5 Introduction In Block 4 we showed the way in which brackets were removed from algebraic expressions. Factorisation, which can be considered as the reverse of this process, is dealt with
More informationSolving DEs by Separation of Variables.
Solving DEs by Separation of Variables. Introduction and procedure Separation of variables allows us to solve differential equations of the form The steps to solving such DEs are as follows: dx = gx).
More informationPartial Fractions Examples
Partial Fractions Examples Partial fractions is the name given to a technique of integration that may be used to integrate any ratio of polynomials. A ratio of polynomials is called a rational function.
More informationis identically equal to x 2 +3x +2
Partial fractions 3.6 Introduction It is often helpful to break down a complicated algebraic fraction into a sum of simpler fractions. 4x+7 For example it can be shown that has the same value as 1 + 3
More information1 The 1-D Heat Equation
The 1-D Heat Equation 18.303 Linear Partial Differential Equations Matthew J. Hancock Fall 006 1 The 1-D Heat Equation 1.1 Physical derivation Reference: Guenther & Lee 1.3-1.4, Myint-U & Debnath.1 and.5
More information10.2 Series and Convergence
10.2 Series and Convergence Write sums using sigma notation Find the partial sums of series and determine convergence or divergence of infinite series Find the N th partial sums of geometric series and
More informationObjective: Use calculator to comprehend transformations.
math111 (Bradford) Worksheet #1 Due Date: Objective: Use calculator to comprehend transformations. Here is a warm up for exploring manipulations of functions. specific formula for a function, say, Given
More informationLimits and Continuity
Math 20C Multivariable Calculus Lecture Limits and Continuity Slide Review of Limit. Side limits and squeeze theorem. Continuous functions of 2,3 variables. Review: Limits Slide 2 Definition Given a function
More informationProbability Generating Functions
page 39 Chapter 3 Probability Generating Functions 3 Preamble: Generating Functions Generating functions are widely used in mathematics, and play an important role in probability theory Consider a sequence
More informationPartial Fractions. (x 1)(x 2 + 1)
Partial Fractions Adding rational functions involves finding a common denominator, rewriting each fraction so that it has that denominator, then adding. For example, 3x x 1 3x(x 1) (x + 1)(x 1) + 1(x +
More informationALGEBRA REVIEW LEARNING SKILLS CENTER. Exponents & Radicals
ALGEBRA REVIEW LEARNING SKILLS CENTER The "Review Series in Algebra" is taught at the beginning of each quarter by the staff of the Learning Skills Center at UC Davis. This workshop is intended to be an
More information19.6. Finding a Particular Integral. Introduction. Prerequisites. Learning Outcomes. Learning Style
Finding a Particular Integral 19.6 Introduction We stated in Block 19.5 that the general solution of an inhomogeneous equation is the sum of the complementary function and a particular integral. We have
More informationSecond Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients. y + p(t) y + q(t) y = g(t), g(t) 0.
Second Order Linear Nonhomogeneous Differential Equations; Method of Undetermined Coefficients We will now turn our attention to nonhomogeneous second order linear equations, equations with the standard
More information1 Completeness of a Set of Eigenfunctions. Lecturer: Naoki Saito Scribe: Alexander Sheynis/Allen Xue. May 3, 2007. 1.1 The Neumann Boundary Condition
MAT 280: Laplacian Eigenfunctions: Theory, Applications, and Computations Lecture 11: Laplacian Eigenvalue Problems for General Domains III. Completeness of a Set of Eigenfunctions and the Justification
More informationAn Introduction to Partial Differential Equations
An Introduction to Partial Differential Equations Andrew J. Bernoff LECTURE 2 Cooling of a Hot Bar: The Diffusion Equation 2.1. Outline of Lecture An Introduction to Heat Flow Derivation of the Diffusion
More information6.1 Add & Subtract Polynomial Expression & Functions
6.1 Add & Subtract Polynomial Expression & Functions Objectives 1. Know the meaning of the words term, monomial, binomial, trinomial, polynomial, degree, coefficient, like terms, polynomial funciton, quardrtic
More informationhttps://williamshartunionca.springboardonline.org/ebook/book/27e8f1b87a1c4555a1212b...
of 19 9/2/2014 12:09 PM Answers Teacher Copy Plan Pacing: 1 class period Chunking the Lesson Example A #1 Example B Example C #2 Check Your Understanding Lesson Practice Teach Bell-Ringer Activity Students
More informationPractice with Proofs
Practice with Proofs October 6, 2014 Recall the following Definition 0.1. A function f is increasing if for every x, y in the domain of f, x < y = f(x) < f(y) 1. Prove that h(x) = x 3 is increasing, using
More informationDefinition of derivative
Definition of derivative Contents 1. Slope-The Concept 2. Slope of a curve 3. Derivative-The Concept 4. Illustration of Example 5. Definition of Derivative 6. Example 7. Extension of the idea 8. Example
More informationDIFFERENTIABILITY OF COMPLEX FUNCTIONS. Contents
DIFFERENTIABILITY OF COMPLEX FUNCTIONS Contents 1. Limit definition of a derivative 1 2. Holomorphic functions, the Cauchy-Riemann equations 3 3. Differentiability of real functions 5 4. A sufficient condition
More informationINTERPOLATION. Interpolation is a process of finding a formula (often a polynomial) whose graph will pass through a given set of points (x, y).
INTERPOLATION Interpolation is a process of finding a formula (often a polynomial) whose graph will pass through a given set of points (x, y). As an example, consider defining and x 0 =0, x 1 = π 4, x
More informationDerivatives Math 120 Calculus I D Joyce, Fall 2013
Derivatives Mat 20 Calculus I D Joyce, Fall 203 Since we ave a good understanding of its, we can develop derivatives very quickly. Recall tat we defined te derivative f x of a function f at x to be te
More informationMicroeconomic Theory: Basic Math Concepts
Microeconomic Theory: Basic Math Concepts Matt Van Essen University of Alabama Van Essen (U of A) Basic Math Concepts 1 / 66 Basic Math Concepts In this lecture we will review some basic mathematical concepts
More informationSection 2.7 One-to-One Functions and Their Inverses
Section. One-to-One Functions and Their Inverses One-to-One Functions HORIZONTAL LINE TEST: A function is one-to-one if and only if no horizontal line intersects its graph more than once. EXAMPLES: 1.
More informationIntroduction to Schrödinger Equation: Harmonic Potential
Introduction to Schrödinger Equation: Harmonic Potential Chia-Chun Chou May 2, 2006 Introduction to Schrödinger Equation: Harmonic Potential Time-Dependent Schrödinger Equation For a nonrelativistic particle
More informationMath 432 HW 2.5 Solutions
Math 432 HW 2.5 Solutions Assigned: 1-10, 12, 13, and 14. Selected for Grading: 1 (for five points), 6 (also for five), 9, 12 Solutions: 1. (2y 3 + 2y 2 ) dx + (3y 2 x + 2xy) dy = 0. M/ y = 6y 2 + 4y N/
More informationLinear Programming Notes V Problem Transformations
Linear Programming Notes V Problem Transformations 1 Introduction Any linear programming problem can be rewritten in either of two standard forms. In the first form, the objective is to maximize, the material
More information1.7. Partial Fractions. 1.7.1. Rational Functions and Partial Fractions. A rational function is a quotient of two polynomials: R(x) = P (x) Q(x).
.7. PRTIL FRCTIONS 3.7. Partial Fractions.7.. Rational Functions and Partial Fractions. rational function is a quotient of two polynomials: R(x) = P (x) Q(x). Here we discuss how to integrate rational
More informationHomework # 3 Solutions
Homework # 3 Solutions February, 200 Solution (2.3.5). Noting that and ( + 3 x) x 8 = + 3 x) by Equation (2.3.) x 8 x 8 = + 3 8 by Equations (2.3.7) and (2.3.0) =3 x 8 6x2 + x 3 ) = 2 + 6x 2 + x 3 x 8
More informationNotes and questions to aid A-level Mathematics revision
Notes and questions to aid A-level Mathematics revision Robert Bowles University College London October 4, 5 Introduction Introduction There are some students who find the first year s study at UCL and
More informationcorrect-choice plot f(x) and draw an approximate tangent line at x = a and use geometry to estimate its slope comment The choices were:
Topic 1 2.1 mode MultipleSelection text How can we approximate the slope of the tangent line to f(x) at a point x = a? This is a Multiple selection question, so you need to check all of the answers that
More information