PDEs, Homework #2 Solutions. is even in x, if the initial data φ, ψ are even. Hint: show u( x, t) is also a solution.

Size: px
Start display at page:

Download "PDEs, Homework #2 Solutions. is even in x, if the initial data φ, ψ are even. Hint: show u( x, t) is also a solution."

Transcription

1 PDEs, Homework # Solutions 1 Show that the solution u(x, t) of the initial value problem u tt = c u xx, u(x, ) = φ(x), u t (x, ) = ψ(x) (WE) is even in x, if the initial data φ, ψ are even Hint: show u( x, t) is also a solution To show that w(x, t) = u( x, t) is also a solution, we note that w tt (x, t) = u tt ( x, t) = c u xx ( x, t) = c w xx (x, t) and that w(x, t) satisfies the initial conditions w(x, ) = u( x, ) = φ( x) = φ(x), w t (x, ) = u t ( x, ) = ψ( x) = ψ(x) Since the initial value problem has a unique solution, this implies u( x, t) Solve the Neumann problem for the wave equation on the half line That is, find the solution to (WE) when x > and the boundary condition u x (, t) = is imposed for all t Hint: argue as for the Dirichlet problem but use an even extension Extend the initial data φ, ψ to the whole real line in such a way that the extension is even Then the solution to the Cauchy problem on the whole real line is φ ext(x ct) + φ ext (x + ct) + 1 c ψ ext (s) ds and we need to express this in terms of φ, ψ When x > ct, we get the usual formula φ(x ct) + φ(x + ct) + 1 c ψ(s) ds because x ± ct are both positive When < x < ct, only x + ct is positive and so φ(ct x) + φ(x + ct) + 1 [ ] ψ( s) ds + ψ(s) ds c Making the substitution r = s in the first integral, we conclude that φ(ct x) + φ(ct + x) + 1 [ ct x ct+x ] ψ(r) dr + ψ(r) dr c

2 3 Find all solutions u = u(x, y) of the second-order equation u xx + 4u xy + 3u yy = First of all, let us factor the given PDE and write = ( x + 4 x y + 3 y)u = ( x + y )( x + 3 y )u If we can find variables v, w such that v = x + y and w = x + 3 y, then = v w u = w u = F 1 (w) = u = F (w) + F 3 (v) To actually find the variables v and w, we note that v = x v x + y v y, w = x w x + y w y by the chain rule, while v = x + y and w = x + 3 y by above This gives x v = y v = x w = 1, y w = 3 so we can let x = v + w and y = v + 3w Solving for v and w, we conclude that y x = w, 3x y = v = u = F (y x) + G(3x y) 4 Show that the solution to the wave equation (WE) need not remain bounded at all times, even though it is initially bounded Hint: take the initial data to be constant Suppose that φ(x) = ψ(x) = 1, for instance Then the corresponding solution is c ds = 1 + t by d Alembert s formula, so the solution does not remain bounded at all times 5 Solve the wave equation (WE) in the case that φ(x) = x and ψ(x) = x + 1 According to d Alembert s formula, the solution is given by (x + ct) + (x ct) + 1 c (s + 1) ds When it comes to the integral on the right hand side, one easily finds that (s + 1) ds = (x + ct) (x ct) + ct = cxt + ct Using this fact and a little bit of algebra, we conclude that x + (ct) + xt + t

3 6 Suppose that a < b and consider the Cauchy problem (WE) in the case that { } 1 if a x b φ(x) = ψ(x) = otherwise Compute the limit lim t u(x, t) for each fixed x R According to d Alembert s formula, the solution is given by φ(x ct) + φ(x + ct) + 1 c ψ(s) ds Since x R is fixed, we have x ± ct ± as t, and this implies lim t 1 c ψ(s) ds = 1 c b a ds = b a c 7 Solve the following non-homogeneous wave equation on the real line: u tt c u xx = t, u(x, ) = x, u t (x, ) = 1 According to Duhamel s formula, the solution is given by (x + ct) + (x ct) + 1 c ds + 1 c t x+c(t τ) x c(t τ) τ dy dτ When it comes to the rightmost integral, one easily finds that 1 c t τ x+c(t τ) x c(t τ) dy dτ = t τ(t τ) dτ = [ τ t τ ] 3 t = t3 3 τ= 6 Using this fact and simplifying the remaining terms, we conclude that x + (ct) + t + t3 6 8 Use the substitution v(x, t) = e λt u(x, t) to solve the initial value problem u tt u xx + λu t + λ u =, u(x, ) = φ(x), u t (x, ) = ψ(x) on the real line Hint: you should find that v satisfies the wave equation v tt = v xx etting v = e λt u, we have v xx = e λt u xx and also v t = λe λt u + e λt u t, hence v tt v xx = (λ e λt u + λe λt u t + e λt u tt ) e λt u xx = e λt (λ u + λu t + u tt u xx )

4 According to the given PDE, this expression is zero and so v(x, t) satisfies v tt = v xx, v(x, ) = φ(x), v t (x, ) = λφ(x) + ψ(x) Solving this problem using d Alembert s formula with c = 1, we now find v(x, t) = φ(x + t) + φ(x t) + 1 x+t x t Thus, the solution to the original problem is given by [ e λt φ(x + t) + φ(x t) + x+t x t λφ(s) + ψ(s) ds ] λφ(s) + ψ(s) ds 9 Consider the wave equation with damping u tt c u xx + du t = on the real line Show that the energy is decreasing for all classical solutions of compact support, if d > Suppose u is a classical solution of compact support and consider the energy E(t) = 1 u t (x, t) + c u x (x, t) dx Since u is C by assumption, the integrand is C 1 and we have E (t) = = u t u tt + c u x u xt dx u t (c u xx du t ) dx + c u x u xt dx Integrating by parts and using the fact that u x vanishes at x = ±, we now get E (t) = = d u t (c u xx du t ) dx u t dx c u xx u t dx 1 Solve the Cauchy problem (WE) on the half line x > when φ(x) = ψ(x) = 1 and the Dirichlet condition u(, t) = is imposed for all t Is your solution a classical one? Hint: there are different formulas for the cases x > ct and x ct When x > ct, the solution is given by d Alembert s formula φ(x + ct) + φ(x ct) + 1 c When < x < ct, on the other hand, it is given by the formula φ(ct + x) φ(ct x) + 1 c ct+x ct x ψ(s) ds = 1 + t ψ(s) ds = x c Since these two expressions do not agree when x = ct, the solution is not continuous along the line x = ct, so it is certainly not a classical solution

5 11 Find the eigenfunctions and eigenvalues of x subject to Neumann boundary conditions on [, ] That is, find all nonzero functions F (x) and all λ R such that F (x) = λf (x), F () = F () = First of all, we multiply the given ODE by F (x) and then integrate to get λ F (x) dx = F (x)f (x) dx = F (x) dx Since the leftmost integral is positive, this implies λ If λ =, then we have F (x) = = F (x) = = F (x) = C If λ = m is positive, on the other hand, then we have F (x) = m F (x) = F (x) = C 1 sin(mx) + C cos(mx) In this case, the boundary condition F () = gives F (x) = mc 1 cos(mx) mc sin(mx) = = mc 1, while the boundary condition F () = gives = F () = mc sin(m) = m = kπ for some integer k In particular, we have m = kπ/ for some integer k, so ( kπx F (x) = C cos(mx) = C cos ), λ = m = ( ) kπ 1 Solve the wave equation u tt = 4u xx on the interval [, π] subject to the conditions u(x, ) = cos x, u t (x, ) = 1, u(, t) = = u(π, t) The solution of the Dirichlet problem for the wave equation u tt = c u xx on [, ] is n=1 ( a n sin nπct + b n cos nπct ) sin nπx, where the coefficients a n, b n are given by the formula a n = nπc sin nπx ψ(x) dx, b n = sin nπx φ(x) dx

6 In this case, we have c = and = π, so the coefficients a n are a n = 1 nπ sin(nx) dx = 1 cos(nπ) n π To compute the coefficients b n, one can integrate by parts to get b n = π sin(nx) cos x dx = n π and then integrate by parts again to arrive at b n = n π [ ] π cos(nx) cos x + n π cos(nx) sin x dx sin(nx) cos x dx This standard argument expresses b n in terms of b n, so it actually gives b n = n π [ ] cos(nπ) n b n = b n = n[cos(nπ) + 1] π(n 1) whenever n 1; the remaining case n = 1 can now be treated directly, as b 1 = π sin x cos x dx = 1 π [ (sin x) ] π =

College of the Holy Cross, Spring 2009 Math 373, Partial Differential Equations Midterm 1 Practice Questions

College of the Holy Cross, Spring 2009 Math 373, Partial Differential Equations Midterm 1 Practice Questions College of the Holy Cross, Spring 29 Math 373, Partial Differential Equations Midterm 1 Practice Questions 1. (a) Find a solution of u x + u y + u = xy. Hint: Try a polynomial of degree 2. Solution. Use

More information

MATH 425, PRACTICE FINAL EXAM SOLUTIONS.

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 information

Second Order Linear Partial Differential Equations. Part I

Second 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 information

An Introduction to Partial Differential Equations

An 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 information

Systems with Persistent Memory: the Observation Inequality Problems and Solutions

Systems 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 information

LS.6 Solution Matrices

LS.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 information

An Introduction to Partial Differential Equations in the Undergraduate Curriculum

An 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 information

The Heat Equation. Lectures INF2320 p. 1/88

The 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 information

Reference: Introduction to Partial Differential Equations by G. Folland, 1995, Chap. 3.

Reference: Introduction to Partial Differential Equations by G. Folland, 1995, Chap. 3. 5 Potential Theory Reference: Introduction to Partial Differential Equations by G. Folland, 995, Chap. 3. 5. Problems of Interest. In what follows, we consider Ω an open, bounded subset of R n with C 2

More information

Calculus 1: Sample Questions, Final Exam, Solutions

Calculus 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 information

1 Completeness of a Set of Eigenfunctions. Lecturer: Naoki Saito Scribe: Alexander Sheynis/Allen Xue. May 3, 2007. 1.1 The Neumann Boundary Condition

1 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 information

Numerical Methods for Differential Equations

Numerical Methods for Differential Equations Numerical Methods for Differential Equations Course objectives and preliminaries Gustaf Söderlind and Carmen Arévalo Numerical Analysis, Lund University Textbooks: A First Course in the Numerical Analysis

More information

I. Pointwise convergence

I. 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 information

PUTNAM TRAINING POLYNOMIALS. Exercises 1. Find a polynomial with integral coefficients whose zeros include 2 + 5.

PUTNAM 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 information

The one dimensional heat equation: Neumann and Robin boundary conditions

The 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 information

3. INNER PRODUCT SPACES

3. 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 information

tegrals as General & Particular Solutions

tegrals 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 information

Solutions to Homework 10

Solutions 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 information

MATH 304 Linear Algebra Lecture 20: Inner product spaces. Orthogonal sets.

MATH 304 Linear Algebra Lecture 20: Inner product spaces. Orthogonal sets. MATH 304 Linear Algebra Lecture 20: Inner product spaces. Orthogonal sets. Norm The notion of norm generalizes the notion of length of a vector in R n. Definition. Let V be a vector space. A function α

More information

3 Contour integrals and Cauchy s Theorem

3 Contour integrals and Cauchy s Theorem 3 ontour integrals and auchy s Theorem 3. Line integrals of complex functions Our goal here will be to discuss integration of complex functions = u + iv, with particular regard to analytic functions. Of

More information

Practice with Proofs

Practice 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 information

1 if 1 x 0 1 if 0 x 1

1 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 information

Partial Fractions. p(x) q(x)

Partial Fractions. p(x) q(x) Partial Fractions Introduction to Partial Fractions Given a rational function of the form p(x) q(x) where the degree of p(x) is less than the degree of q(x), the method of partial fractions seeks to break

More information

FIELDS-MITACS Conference. on the Mathematics of Medical Imaging. Photoacoustic and Thermoacoustic Tomography with a variable sound speed

FIELDS-MITACS Conference. on the Mathematics of Medical Imaging. Photoacoustic and Thermoacoustic Tomography with a variable sound speed FIELDS-MITACS Conference on the Mathematics of Medical Imaging Photoacoustic and Thermoacoustic Tomography with a variable sound speed Gunther Uhlmann UC Irvine & University of Washington Toronto, Canada,

More information

ARBITRAGE-FREE OPTION PRICING MODELS. Denis Bell. University of North Florida

ARBITRAGE-FREE OPTION PRICING MODELS. Denis Bell. University of North Florida ARBITRAGE-FREE OPTION PRICING MODELS Denis Bell University of North Florida Modelling Stock Prices Example American Express In mathematical finance, it is customary to model a stock price by an (Ito) stochatic

More information

1. First-order Ordinary Differential Equations

1. 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 information

Application 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) 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 information

Class Meeting # 1: Introduction to PDEs

Class 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 information

The two dimensional heat equation

The two dimensional heat equation The two dimensional heat equation Ryan C. Trinity University Partial Differential Equations March 6, 2012 Physical motivation Consider a thin rectangular plate made of some thermally conductive material.

More information

2.2 Separable Equations

2.2 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 information

EXISTENCE AND NON-EXISTENCE RESULTS FOR A NONLINEAR HEAT EQUATION

EXISTENCE AND NON-EXISTENCE RESULTS FOR A NONLINEAR HEAT EQUATION Sixth Mississippi State Conference on Differential Equations and Computational Simulations, Electronic Journal of Differential Equations, Conference 5 (7), pp. 5 65. ISSN: 7-669. UL: http://ejde.math.txstate.edu

More information

Chapter 5. Banach Spaces

Chapter 5. Banach Spaces 9 Chapter 5 Banach Spaces Many linear equations may be formulated in terms of a suitable linear operator acting on a Banach space. In this chapter, we study Banach spaces and linear operators acting on

More information

Constrained optimization.

Constrained optimization. ams/econ 11b supplementary notes ucsc Constrained optimization. c 2010, Yonatan Katznelson 1. Constraints In many of the optimization problems that arise in economics, there are restrictions on the values

More information

Real Roots of Univariate Polynomials with Real Coefficients

Real Roots of Univariate Polynomials with Real Coefficients Real Roots of Univariate Polynomials with Real Coefficients mostly written by Christina Hewitt March 22, 2012 1 Introduction Polynomial equations are used throughout mathematics. When solving polynomials

More information

General Theory of Differential Equations Sections 2.8, 3.1-3.2, 4.1

General 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 information

1 3 4 = 8i + 20j 13k. x + w. y + w

1 3 4 = 8i + 20j 13k. x + w. y + w ) Find the point of intersection of the lines x = t +, y = 3t + 4, z = 4t + 5, and x = 6s + 3, y = 5s +, z = 4s + 9, and then find the plane containing these two lines. Solution. Solve the system of equations

More information

Properties of BMO functions whose reciprocals are also BMO

Properties of BMO functions whose reciprocals are also BMO Properties of BMO functions whose reciprocals are also BMO R. L. Johnson and C. J. Neugebauer The main result says that a non-negative BMO-function w, whose reciprocal is also in BMO, belongs to p> A p,and

More information

5.4 The Heat Equation and Convection-Diffusion

5.4 The Heat Equation and Convection-Diffusion 5.4. THE HEAT EQUATION AND CONVECTION-DIFFUSION c 6 Gilbert Strang 5.4 The Heat Equation and Convection-Diffusion The wave equation conserves energy. The heat equation u t = u xx dissipates energy. The

More information

Scalar Valued Functions of Several Variables; the Gradient Vector

Scalar 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 information

y cos 3 x dx y cos 2 x cos x dx y 1 sin 2 x cos x dx

y 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 information

Vector Calculus Solutions to Sample Final Examination #1

Vector Calculus Solutions to Sample Final Examination #1 Vector alculus s to Sample Final Examination #1 1. Let f(x, y) e xy sin(x + y). (a) In what direction, starting at (,π/), is f changing the fastest? (b) In what directions starting at (,π/) is f changing

More information

How To Prove The Dirichlet Unit Theorem

How To Prove The Dirichlet Unit Theorem Chapter 6 The Dirichlet Unit Theorem As usual, we will be working in the ring B of algebraic integers of a number field L. Two factorizations of an element of B are regarded as essentially the same if

More information

Course Notes for Math 162: Mathematical Statistics Approximation Methods in Statistics

Course Notes for Math 162: Mathematical Statistics Approximation Methods in Statistics Course Notes for Math 16: Mathematical Statistics Approximation Methods in Statistics Adam Merberg and Steven J. Miller August 18, 6 Abstract We introduce some of the approximation methods commonly used

More information

Math 55: Discrete Mathematics

Math 55: Discrete Mathematics Math 55: Discrete Mathematics UC Berkeley, Spring 2012 Homework # 9, due Wednesday, April 11 8.1.5 How many ways are there to pay a bill of 17 pesos using a currency with coins of values of 1 peso, 2 pesos,

More information

Does Black-Scholes framework for Option Pricing use Constant Volatilities and Interest Rates? New Solution for a New Problem

Does Black-Scholes framework for Option Pricing use Constant Volatilities and Interest Rates? New Solution for a New Problem Does Black-Scholes framework for Option Pricing use Constant Volatilities and Interest Rates? New Solution for a New Problem Gagan Deep Singh Assistant Vice President Genpact Smart Decision Services Financial

More information

Introduction to Algebraic Geometry. Bézout s Theorem and Inflection Points

Introduction to Algebraic Geometry. Bézout s Theorem and Inflection Points Introduction to Algebraic Geometry Bézout s Theorem and Inflection Points 1. The resultant. Let K be a field. Then the polynomial ring K[x] is a unique factorisation domain (UFD). Another example of a

More information

A characterization of trace zero symmetric nonnegative 5x5 matrices

A characterization of trace zero symmetric nonnegative 5x5 matrices A characterization of trace zero symmetric nonnegative 5x5 matrices Oren Spector June 1, 009 Abstract The problem of determining necessary and sufficient conditions for a set of real numbers to be the

More information

Math 241, Exam 1 Information.

Math 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 information

Fibonacci Numbers and Greatest Common Divisors. The Finonacci numbers are the numbers in the sequence 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144,...

Fibonacci Numbers and Greatest Common Divisors. The Finonacci numbers are the numbers in the sequence 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144,... Fibonacci Numbers and Greatest Common Divisors The Finonacci numbers are the numbers in the sequence 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144,.... After starting with two 1s, we get each Fibonacci number

More information

Partial Fractions Examples

Partial 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 information

3. Mathematical Induction

3. Mathematical Induction 3. MATHEMATICAL INDUCTION 83 3. Mathematical Induction 3.1. First Principle of Mathematical Induction. Let P (n) be a predicate with domain of discourse (over) the natural numbers N = {0, 1,,...}. If (1)

More information

A Brief Review of Elementary Ordinary Differential Equations

A 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 information

e.g. arrival of a customer to a service station or breakdown of a component in some system.

e.g. arrival of a customer to a service station or breakdown of a component in some system. Poisson process Events occur at random instants of time at an average rate of λ events per second. e.g. arrival of a customer to a service station or breakdown of a component in some system. Let N(t) be

More information

SOLUTIONS. f x = 6x 2 6xy 24x, f y = 3x 2 6y. To find the critical points, we solve

SOLUTIONS. 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 information

Using a table of derivatives

Using 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 information

Numerical Analysis Lecture Notes

Numerical Analysis Lecture Notes Numerical Analysis Lecture Notes Peter J. Olver. Finite Difference Methods for Partial Differential Equations As you are well aware, most differential equations are much too complicated to be solved by

More information

Solving DEs by Separation of Variables.

Solving 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 information

Partial Differential Equations: Graduate Level Problems and Solutions. Igor Yanovsky

Partial Differential Equations: Graduate Level Problems and Solutions. Igor Yanovsky Partial Differential Equations: Graduate Level Problems and Solutions Igor Yanovsky Partial Differential Equations Igor Yanovsky, 5 Disclaimer: This handbook is intended to assist graduate students with

More information

ON CERTAIN DOUBLY INFINITE SYSTEMS OF CURVES ON A SURFACE

ON CERTAIN DOUBLY INFINITE SYSTEMS OF CURVES ON A SURFACE i93 c J SYSTEMS OF CURVES 695 ON CERTAIN DOUBLY INFINITE SYSTEMS OF CURVES ON A SURFACE BY C H. ROWE. Introduction. A system of co 2 curves having been given on a surface, let us consider a variable curvilinear

More information

Walrasian Demand. u(x) where B(p, w) = {x R n + : p x w}.

Walrasian Demand. u(x) where B(p, w) = {x R n + : p x w}. Walrasian Demand Econ 2100 Fall 2015 Lecture 5, September 16 Outline 1 Walrasian Demand 2 Properties of Walrasian Demand 3 An Optimization Recipe 4 First and Second Order Conditions Definition Walrasian

More information

Chapter 20. Vector Spaces and Bases

Chapter 20. Vector Spaces and Bases Chapter 20. Vector Spaces and Bases In this course, we have proceeded step-by-step through low-dimensional Linear Algebra. We have looked at lines, planes, hyperplanes, and have seen that there is no limit

More information

ORDINARY DIFFERENTIAL EQUATIONS

ORDINARY DIFFERENTIAL EQUATIONS ORDINARY DIFFERENTIAL EQUATIONS GABRIEL NAGY Mathematics Department, Michigan State University, East Lansing, MI, 48824. SEPTEMBER 4, 25 Summary. This is an introduction to ordinary differential equations.

More information

3. Reaction Diffusion Equations Consider the following ODE model for population growth

3. Reaction Diffusion Equations Consider the following ODE model for population growth 3. Reaction Diffusion Equations Consider the following ODE model for population growth u t a u t u t, u 0 u 0 where u t denotes the population size at time t, and a u plays the role of the population dependent

More information

Extremal equilibria for reaction diffusion equations in bounded domains and applications.

Extremal equilibria for reaction diffusion equations in bounded domains and applications. Extremal equilibria for reaction diffusion equations in bounded domains and applications. Aníbal Rodríguez-Bernal Alejandro Vidal-López Departamento de Matemática Aplicada Universidad Complutense de Madrid,

More information

The idea to study a boundary value problem associated to the scalar equation

The idea to study a boundary value problem associated to the scalar equation Topological Methods in Nonlinear Analysis Journal of the Juliusz Schauder Center Volume 23, 2004, 73 88 DEGREE COMPUTATIONS FOR POSITIVELY HOMOGENEOUS DIFFERENTIAL EQUATIONS Christian Fabry Patrick Habets

More information

arxiv:1201.6059v2 [physics.class-ph] 27 Aug 2012

arxiv: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 information

The integrating factor method (Sect. 2.1).

The integrating factor method (Sect. 2.1). The integrating factor method (Sect. 2.1). Overview of differential equations. Linear Ordinary Differential Equations. The integrating factor method. Constant coefficients. The Initial Value Problem. Variable

More information

Parabolic Equations. Chapter 5. Contents. 5.1.2 Well-Posed Initial-Boundary Value Problem. 5.1.3 Time Irreversibility of the Heat Equation

Parabolic Equations. Chapter 5. Contents. 5.1.2 Well-Posed Initial-Boundary Value Problem. 5.1.3 Time Irreversibility of the Heat Equation 7 5.1 Definitions Properties Chapter 5 Parabolic Equations Note that we require the solution u(, t bounded in R n for all t. In particular we assume that the boundedness of the smooth function u at infinity

More information

Methods of Solution of Selected Differential Equations Carol A. Edwards Chandler-Gilbert Community College

Methods of Solution of Selected Differential Equations Carol A. Edwards Chandler-Gilbert Community College Methods of Solution of Selected Differential Equations Carol A. Edwards Chandler-Gilbert Community College Equations of Order One: Mdx + Ndy = 0 1. Separate variables. 2. M, N homogeneous of same degree:

More information

Introduction to Complex Fourier Series

Introduction 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 information

Implicit Differentiation

Implicit 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 information

Lecture 14: Section 3.3

Lecture 14: Section 3.3 Lecture 14: Section 3.3 Shuanglin Shao October 23, 2013 Definition. Two nonzero vectors u and v in R n are said to be orthogonal (or perpendicular) if u v = 0. We will also agree that the zero vector in

More information

Student name: Earlham College. Fall 2011 December 15, 2011

Student name: Earlham College. Fall 2011 December 15, 2011 Student name: Earlham College MATH 320: Differential Equations Final exam - In class part Fall 2011 December 15, 2011 Instructions: This is a regular closed-book test, and is to be taken without the use

More information

Differentiation and Integration

Differentiation 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 information

UNIVERSITETET I OSLO

UNIVERSITETET I OSLO NIVERSITETET I OSLO Det matematisk-naturvitenskapelige fakultet Examination in: Trial exam Partial differential equations and Sobolev spaces I. Day of examination: November 18. 2009. Examination hours:

More information

Integrating algebraic fractions

Integrating algebraic fractions Integrating algebraic fractions Sometimes the integral of an algebraic fraction can be found by first epressing the algebraic fraction as the sum of its partial fractions. In this unit we will illustrate

More information

Høgskolen i Narvik Sivilingeniørutdanningen STE6237 ELEMENTMETODER. Oppgaver

Høgskolen i Narvik Sivilingeniørutdanningen STE6237 ELEMENTMETODER. Oppgaver Høgskolen i Narvik Sivilingeniørutdanningen STE637 ELEMENTMETODER Oppgaver Klasse: 4.ID, 4.IT Ekstern Professor: Gregory A. Chechkin e-mail: chechkin@mech.math.msu.su Narvik 6 PART I Task. Consider two-point

More information

Differential Operators and their Adjoint Operators

Differential Operators and their Adjoint Operators Differential Operators and their Adjoint Operators Differential Operators inear functions from E n to E m may be described, once bases have been selected in both spaces ordinarily one uses the standard

More information

Integrals of Rational Functions

Integrals 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 information

4.5 Linear Dependence and Linear Independence

4.5 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 information

Second 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. 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 information

Separable First Order Differential Equations

Separable 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 information

by the matrix A results in a vector which is a reflection of the given

by the matrix A results in a vector which is a reflection of the given Eigenvalues & Eigenvectors Example Suppose Then So, geometrically, multiplying a vector in by the matrix A results in a vector which is a reflection of the given vector about the y-axis We observe that

More information

Numerical Methods for Differential Equations

Numerical Methods for Differential Equations Numerical Methods for Differential Equations Chapter 1: Initial value problems in ODEs Gustaf Söderlind and Carmen Arévalo Numerical Analysis, Lund University Textbooks: A First Course in the Numerical

More information

1 The 1-D Heat Equation

1 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 information

Introduction to the Finite Element Method

Introduction to the Finite Element Method Introduction to the Finite Element Method 09.06.2009 Outline Motivation Partial Differential Equations (PDEs) Finite Difference Method (FDM) Finite Element Method (FEM) References Motivation Figure: cross

More information

Second-Order Linear Differential Equations

Second-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 information

Homework #1 Solutions

Homework #1 Solutions MAT 303 Spring 203 Homework # Solutions Problems Section.:, 4, 6, 34, 40 Section.2:, 4, 8, 30, 42 Section.4:, 2, 3, 4, 8, 22, 24, 46... Verify that y = x 3 + 7 is a solution to y = 3x 2. Solution: From

More information

0.8 Rational Expressions and Equations

0.8 Rational Expressions and Equations 96 Prerequisites 0.8 Rational Expressions and Equations We now turn our attention to rational expressions - that is, algebraic fractions - and equations which contain them. The reader is encouraged to

More information

THE FUNDAMENTAL THEOREM OF ALGEBRA VIA PROPER MAPS

THE FUNDAMENTAL THEOREM OF ALGEBRA VIA PROPER MAPS THE FUNDAMENTAL THEOREM OF ALGEBRA VIA PROPER MAPS KEITH CONRAD 1. Introduction The Fundamental Theorem of Algebra says every nonconstant polynomial with complex coefficients can be factored into linear

More information

2 Integrating Both Sides

2 Integrating Both Sides 2 Integrating Both Sides So far, the only general method we have for solving differential equations involves equations of the form y = f(x), where f(x) is any function of x. The solution to such an equation

More information

SECOND-ORDER LINEAR DIFFERENTIAL EQUATIONS

SECOND-ORDER LINEAR DIFFERENTIAL EQUATIONS SECOND-ORDER LINEAR DIFFERENTIAL EQUATIONS A second-order linear differential equation has the form 1 Px d y dx dy Qx dx Rxy Gx where P, Q, R, and G are continuous functions. Equations of this type arise

More information

Høgskolen i Narvik Sivilingeniørutdanningen

Høgskolen i Narvik Sivilingeniørutdanningen Høgskolen i Narvik Sivilingeniørutdanningen Eksamen i Faget STE6237 ELEMENTMETODEN Klassen: 4.ID 4.IT Dato: 8.8.25 Tid: Kl. 9. 2. Tillatte hjelpemidler under eksamen: Kalkulator. Bok Numerical solution

More information

Notes on metric spaces

Notes on metric spaces Notes on metric spaces 1 Introduction The purpose of these notes is to quickly review some of the basic concepts from Real Analysis, Metric Spaces and some related results that will be used in this course.

More information

Introduction to Partial Differential Equations. John Douglas Moore

Introduction 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 information

THE DIMENSION OF A VECTOR SPACE

THE DIMENSION OF A VECTOR SPACE THE DIMENSION OF A VECTOR SPACE KEITH CONRAD This handout is a supplementary discussion leading up to the definition of dimension and some of its basic properties. Let V be a vector space over a field

More information

8 Hyperbolic Systems of First-Order Equations

8 Hyperbolic Systems of First-Order Equations 8 Hyperbolic Systems of First-Order Equations Ref: Evans, Sec 73 8 Definitions and Examples Let U : R n (, ) R m Let A i (x, t) beanm m matrix for i,,n Let F : R n (, ) R m Consider the system U t + A

More information

sin(x) < x sin(x) x < tan(x) sin(x) x cos(x) 1 < sin(x) sin(x) 1 < 1 cos(x) 1 cos(x) = 1 cos2 (x) 1 + cos(x) = sin2 (x) 1 < x 2

sin(x) < x sin(x) x < tan(x) sin(x) x cos(x) 1 < sin(x) sin(x) 1 < 1 cos(x) 1 cos(x) = 1 cos2 (x) 1 + cos(x) = sin2 (x) 1 < x 2 . Problem Show that using an ɛ δ proof. sin() lim = 0 Solution: One can see that the following inequalities are true for values close to zero, both positive and negative. This in turn implies that On the

More information

EXERCISES PDE 31.10.12-02.11.12. v(x)

EXERCISES PDE 31.10.12-02.11.12. v(x) EXERCISES PDE 31.1.12-2.11.12 1. Exercise Let U R N 2 be a bounded open set. We say that v C (Ū) is subharmonic iff v in U. (a) Prove that subharmonic functions enjoy the following form of the mean-value

More information

Properties of Legendre Polynomials

Properties of Legendre Polynomials Chapter C Properties of Legendre Polynomials C Definitions The Legendre Polynomials are the everywhere regular solutions of Legendre s Equation, which are possible only if x 2 )u 2xu + mu = x 2 )u ] +

More information