Math 447/547 Partial Differential Equations Prof. Carlson Homework 7 Text section Solve the diffusion problem. u(t,0) = 0 = u x (t,l).

Size: px
Start display at page:

Download "Math 447/547 Partial Differential Equations Prof. Carlson Homework 7 Text section 4.2 1. Solve the diffusion problem. u(t,0) = 0 = u x (t,l)."

Transcription

1 Math 447/547 Partia Differentia Equations Prof. Carson Homework 7 Text section Sove the diffusion probem with the mixed boundary conditions u t = ku xx, < x <, u(t,) = = u x (t,). Soution The anaysis proceeds initiay as on p. 85. The probem for X(x) is X = λx, X() = = X (). For positive eigenvaues λ = β 2 soutions must have the form X n (x) = A n sin(βx) because of the boundary condition at x =. The condition at x = becomes cos(β) = so that β = (n + 1/2)π/, n =,1,2,... It is easy to see that is not an eigenvaue. For genera compex eigenvaues λ we have X(x) = Ce i λx + De i λx. C + D =, i λce λ i λde λ =. Together we find that e i λ + e i λ =, 1

2 or This gives e i λ [e 2i λ + 1] =. 2 λ = (π + 2nπ)/, or λ = (π/2 + nπ)/ n =,1,2,... Thus the positive eigenvaues are the ony ones. The genera soution then has the form u(t,x) = n X n (x)t n (t) = A n exp( (n + 1/2) 2 π 2 kt/ 2 )sin((n + 1/2)πx/). n= 2. Consider the equation u tt = c 2 u xx for < x < with the boundary conditions u x (t,) = = u(t,). a) Show that the eigenfunctions are cos((n + 1/2)πx/). b) Write the series expansion for a soution u(t,x). Soution a) The anaysis proceeds pretty much as in the previous probem. One checks easiy that cannot be an eigenvaue. For other compex λ we have X(x) = Ce i λx + De i λx. i λc i λd =, Ce i λ + De i λ =. Together we find that or e i λ + e i λ =, e i λ [e 2i λ + 1] =. This gives λ = (π/2 + nπ)/, n =,1,2,... 2

3 as before. We now have X n (x) = C n cos( (n + 1/2)π (n + 1/2)π x) + D n sin( x). To satisfy the boundary condition at we must have D n =, so eigenfunctions are nonzero mutipes of cos( (n+1/2)π x). b) As in p. 83 (5) the equation for T n is This gives and u(t,x) = T n + λc 2 T n =. T n (t) = A n cos((n + 1/2)πct/) + B n sin((n + 1/2)πct/), [A n cos((n+ 1 2 )πct/)+b n sin((n+ 1 2 )πct/)]cos((n+1/2)πx). n= 3. Sove the Schrödinger equation u t = iku xx, u x (t,) =, u(t,) =, x. As in probem 2, The equation for T n is X n (x) = cos( (n + 1/2)π x). so T n + 1/2)π (t) + ik[(n ] 2 T n (t) =, T n (t) = C n exp( ik(n + 1/2)2 π 2 t), 2 3

4 and u(t,x) = n= C n exp( ik(n + 1/2)2 π 2 2 t)cos((n + 1/2)πx). 4. (NOT ASSIGNED) Consider diffusion inside an encosed circuar tube. Let its ength (circumference) be 2. Let x denote the arc ength parameter where x. Then the concentration of the diffusing substance satisfies u t = ku xx, x, u(t, ) = u(t,), u x (t, ) = u x (t,). a) Show that the eigenvaues are λ = (nπ/) 2 for n =,1,2,... Soution There are constant eigenfunctions for eigenvaue λ =. For other λ we have X(x) = Ce λx + De λx. Ce λ + De λ = Ce λ + De λ, and λ[ce λ De λ ] = λ[ce λ De λ ]. Some arithmetic eads to or so that e λ = e λ 1 = e 2 λ, λ = nπ/. b) Show that the concentration is u(t,x) = a 2 + (a n cos( nπx ) + b n sin( nπx ))exp( n 2 π 2 kt/ 2 ). n=1 Soution So far we have identified the eigenvaues, but not the eigenfunctions. Notice that for each n = 1,2,3,... both functions cos( nπx ) and 4

5 sin( nπx ) satisfy the periodic boundary conditions. The ony exceptiona case is n = when the function 1 satisfies the boundary conditions, but x does not. This resuts in the given form for u(t,x). 9. On the interva x 1 of ength 1, consider the eigenvaue probem X = λx, X () + X() =, X(1) =. a) Find an eigenfunction with eigenvaue. Ca in X. Soution Any mutipe of the function 1 x satisfies the boundary conditions. b) Find an equation for the positive eigenvaues λ = β 2. Soution We may write X n (x) = C n cos(βx) + D n sin(βx). βd n + C n =, C n cos(β) + D n sin(β) =. Together these give or β cos(β) + sin(β) =, tan(β) = β. c) Show graphicay that there are an infinite number of positive eigenvaues. Soution Pot the functions tan(β) and β and see where they intersect. d) Is there a negative eigenvaue? Soution Suppose that λ = γ 2, γ >. Then we woud have X n (x) = C n cosh(βx) + D n sinh(βx) and the boundary conditions woud give γd n + C n =, C n cosh(γ) + D n sinh(γ) =. 5

6 The equation for γ is γ = tanh(γ). Since we see that tanh() = and tanh(γ) = eγ e γ e γ + e γ tanh(γ) < 1, γ <. Compute tanh (γ) = 4 (e γ + e γ ) 2. Notice that e γ + e γ has a minimum vaue of which is achieved ony at γ =. Thus < tanh (γ) < 1, < γ <. If there were a point γ 1 > such that γ = tanh(γ 1 ), then the function γ tanh(γ 1 ) woud vanish at and at γ 1. By Roe s theorem the function woud have a positive root for the derivative. But the above anaysis shows that 1 tanh (γ) >, < γ <. Thus there are no negative eigenvaues. 11. a) Prove that the tota energy is conserved for the wave equation with Dirichet boundary conditions, where the energy is defined to be E = 1 2 (c 2 u 2 t + u2 x ) dx. Soution We have de dt = 1 2 (c 2 2u t u tt + 2u x u xt ) dx = 1 2 (2u t u xx + 2u x u xt ) dx. 6

7 Integrate the second term by parts to get de dt = 1 2 The boundary conditions are Differentiation gives (2u t u xx + 2u xx u t ) dx + u x u t. u(t,) = = u(t,). u t (t,) = = u t (t,), so de dt =. b) Do the same for Neumann boundary conditions. Soution The ony difference is that the vanishing of the boundary terms comes from u x (t,) = = u x (t,). c) For the Robin boundary conditions, show that E R = 1 2 (c 2 u 2 t + u 2 x) dx a u 2 (t,) a u 2 (t,). Soution Differentiation and integration by parts gives de R dt = u x u t + a u(t,)u t (t,) + a u(t,)u t (t,) = u t (t,)[u x (t,) + a u(t,)] u t (t,)[u x (t,) a u(t,)] =. 7

Math 2280 - Assignment 6

Math 2280 - Assignment 6 Math 2280 - Assignment 6 Dylan Zwick Spring 2014 Section 3.8-1, 3, 5, 8, 13 Section 4.1-1, 2, 13, 15, 22 Section 4.2-1, 10, 19, 28 1 Section 3.8 - Endpoint Problems and Eigenvalues 3.8.1 For the eigenvalue

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

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

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

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

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

1 Inner Products and Norms on Real Vector Spaces

1 Inner Products and Norms on Real Vector Spaces Math 373: Principles Techniques of Applied Mathematics Spring 29 The 2 Inner Product 1 Inner Products Norms on Real Vector Spaces Recall that an inner product on a real vector space V is a function from

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

The 1-D Wave Equation

The 1-D Wave Equation The -D Wave Equation 8.303 Linear Partial Differential Equations Matthew J. Hancock Fall 006 -D Wave Equation : Physical derivation Reference: Guenther & Lee., Myint-U & Debnath.-.4 [Oct. 3, 006] We consider

More information

1 Variational calculation of a 1D bound state

1 Variational calculation of a 1D bound state TEORETISK FYSIK, KTH TENTAMEN I KVANTMEKANIK FÖRDJUPNINGSKURS EXAMINATION IN ADVANCED QUANTUM MECHAN- ICS Kvantmekanik fördjupningskurs SI38 för F4 Thursday December, 7, 8. 13. Write on each page: Name,

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

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

α α λ α = = λ λ α ψ = = α α α λ λ ψ α = + β = > θ θ β > β β θ θ θ β θ β γ θ β = γ θ > β > γ θ β γ = θ β = θ β = θ β = β θ = β β θ = = = β β θ = + α α α α α = = λ λ λ λ λ λ λ = λ λ α α α α λ ψ + α =

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

Physics 43 Homework Set 9 Chapter 40 Key

Physics 43 Homework Set 9 Chapter 40 Key Physics 43 Homework Set 9 Chpter 4 Key. The wve function for n electron tht is confined to x nm is. Find the normliztion constnt. b. Wht is the probbility of finding the electron in. nm-wide region t x

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

Practice problems for Homework 11 - Point Estimation

Practice problems for Homework 11 - Point Estimation Practice problems for Homework 11 - Point Estimation 1. (10 marks) Suppose we want to select a random sample of size 5 from the current CS 3341 students. Which of the following strategies is the best:

More information

Coffeyville Community College #MATH 202 COURSE SYLLABUS FOR DIFFERENTIAL EQUATIONS. Ryan Willis Instructor

Coffeyville Community College #MATH 202 COURSE SYLLABUS FOR DIFFERENTIAL EQUATIONS. Ryan Willis Instructor Coffeyville Community College #MATH 202 COURSE SYLLABUS FOR DIFFERENTIAL EQUATIONS Ryan Willis Instructor COURSE NUMBER: MATH 202 COURSE TITLE: Differential Equations CREDIT HOURS: 3 INSTRUCTOR: OFFICE

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

Solutions to Practice Problems for Test 4

Solutions to Practice Problems for Test 4 olutions to Practice Problems for Test 4 1. Let be the line segmentfrom the point (, 1, 1) to the point (,, 3). Evaluate the line integral y ds. Answer: First, we parametrize the line segment from (, 1,

More information

CHAPTER IV - BROWNIAN MOTION

CHAPTER IV - BROWNIAN MOTION CHAPTER IV - BROWNIAN MOTION JOSEPH G. CONLON 1. Construction of Brownian Motion There are two ways in which the idea of a Markov chain on a discrete state space can be generalized: (1) The discrete time

More information

6.2 Permutations continued

6.2 Permutations continued 6.2 Permutations continued Theorem A permutation on a finite set A is either a cycle or can be expressed as a product (composition of disjoint cycles. Proof is by (strong induction on the number, r, of

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

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

2m dx 2 = Eψ(x) (1) Total derivatives can be used since there is but one independent variable. The equation simplifies to. ψ (x) + k 2 ψ(x) = 0 (2)

2m dx 2 = Eψ(x) (1) Total derivatives can be used since there is but one independent variable. The equation simplifies to. ψ (x) + k 2 ψ(x) = 0 (2) CHAPTER 3 QUANTUM MECHANICS OF SOME SIMPLE SYSTEMS The Free Particle The simplest system in quantum mechanics has the potential energy V equal to zero everywhere. This is called a free particle since it

More information

Scientific Programming

Scientific Programming 1 The wave equation Scientific Programming Wave Equation The wave equation describes how waves propagate: light waves, sound waves, oscillating strings, wave in a pond,... Suppose that the function h(x,t)

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

88 CHAPTER 2. VECTOR FUNCTIONS. . First, we need to compute T (s). a By definition, r (s) T (s) = 1 a sin s a. sin s a, cos s a

88 CHAPTER 2. VECTOR FUNCTIONS. . First, we need to compute T (s). a By definition, r (s) T (s) = 1 a sin s a. sin s a, cos s a 88 CHAPTER. VECTOR FUNCTIONS.4 Curvature.4.1 Definitions and Examples The notion of curvature measures how sharply a curve bends. We would expect the curvature to be 0 for a straight line, to be very small

More information

Laminar to Turbulent Transition in Cylindrical Pipes

Laminar to Turbulent Transition in Cylindrical Pipes Course I: Fluid Mechanics & Energy Conversion Laminar to Turbulent Transition in Cylindrical Pipes By, Sai Sandeep Tallam IIT Roorkee Mentors: Dr- Ing. Buelent Unsal Ms. Mina Nishi Indo German Winter Academy

More information

Energy Density / Energy Flux / Total Energy in 3D

Energy Density / Energy Flux / Total Energy in 3D Lecture 5 Phys 75 Energy Density / Energy Fux / Tota Energy in D Overview and Motivation: In this ecture we extend the discussion of the energy associated with wave otion to waves described by the D wave

More information

Oscillations. Vern Lindberg. June 10, 2010

Oscillations. Vern Lindberg. June 10, 2010 Oscillations Vern Lindberg June 10, 2010 You have discussed oscillations in Vibs and Waves: we will therefore touch lightly on Chapter 3, mainly trying to refresh your memory and extend the concepts. 1

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

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

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

How To Understand The Theory Of Algebraic Functions

How To Understand The Theory Of Algebraic Functions Homework 4 3.4,. Show that x x cos x x holds for x 0. Solution: Since cos x, multiply all three parts by x > 0, we get: x x cos x x, and since x 0 x x 0 ( x ) = 0, then by Sandwich theorem, we get: x 0

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 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

MAT 1341: REVIEW II SANGHOON BAEK

MAT 1341: REVIEW II SANGHOON BAEK MAT 1341: REVIEW II SANGHOON BAEK 1. Projections and Cross Product 1.1. Projections. Definition 1.1. Given a vector u, the rectangular (or perpendicular or orthogonal) components are two vectors u 1 and

More information

Dd2 = kp, (2.1) t = D 2 P. x 2, (2.2) P(t, x) = e at+bx, (2.3)

Dd2 = kp, (2.1) t = D 2 P. x 2, (2.2) P(t, x) = e at+bx, (2.3) Chapter 2 Diffusion equations 2. Separation of variables: intervals Diffusion equation is a linear partial differential equation, since the functions related to u in the equations (u t and u are both linear.

More information

UNIT I: RANDOM VARIABLES PART- A -TWO MARKS

UNIT I: RANDOM VARIABLES PART- A -TWO MARKS UNIT I: RANDOM VARIABLES PART- A -TWO MARKS 1. Given the probability density function of a continuous random variable X as follows f(x) = 6x (1-x) 0

More information

3 0 + 4 + 3 1 + 1 + 3 9 + 6 + 3 0 + 1 + 3 0 + 1 + 3 2 mod 10 = 4 + 3 + 1 + 27 + 6 + 1 + 1 + 6 mod 10 = 49 mod 10 = 9.

3 0 + 4 + 3 1 + 1 + 3 9 + 6 + 3 0 + 1 + 3 0 + 1 + 3 2 mod 10 = 4 + 3 + 1 + 27 + 6 + 1 + 1 + 6 mod 10 = 49 mod 10 = 9. SOLUTIONS TO HOMEWORK 2 - MATH 170, SUMMER SESSION I (2012) (1) (Exercise 11, Page 107) Which of the following is the correct UPC for Progresso minestrone soup? Show why the other numbers are not valid

More information

CITY UNIVERSITY LONDON. BEng Degree in Computer Systems Engineering Part II BSc Degree in Computer Systems Engineering Part III PART 2 EXAMINATION

CITY UNIVERSITY LONDON. BEng Degree in Computer Systems Engineering Part II BSc Degree in Computer Systems Engineering Part III PART 2 EXAMINATION No: CITY UNIVERSITY LONDON BEng Degree in Computer Systems Engineering Part II BSc Degree in Computer Systems Engineering Part III PART 2 EXAMINATION ENGINEERING MATHEMATICS 2 (resit) EX2005 Date: August

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

3.5 Pendulum period. 2009-02-10 19:40:05 UTC / rev 4d4a39156f1e. g = 4π2 l T 2. g = 4π2 x1 m 4 s 2 = π 2 m s 2. 3.5 Pendulum period 68

3.5 Pendulum period. 2009-02-10 19:40:05 UTC / rev 4d4a39156f1e. g = 4π2 l T 2. g = 4π2 x1 m 4 s 2 = π 2 m s 2. 3.5 Pendulum period 68 68 68 3.5 Penduum period 68 3.5 Penduum period Is it coincidence that g, in units of meters per second squared, is 9.8, very cose to 2 9.87? Their proximity suggests a connection. Indeed, they are connected

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

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

Homework #2 Solutions

Homework #2 Solutions MAT Spring Problems Section.:, 8,, 4, 8 Section.5:,,, 4,, 6 Extra Problem # Homework # Solutions... Sketch likely solution curves through the given slope field for dy dx = x + y...8. Sketch likely solution

More information

Maximum Likelihood Estimation

Maximum Likelihood Estimation Math 541: Statistical Theory II Lecturer: Songfeng Zheng Maximum Likelihood Estimation 1 Maximum Likelihood Estimation Maximum likelihood is a relatively simple method of constructing an estimator for

More information

FINAL EXAM SOLUTIONS Math 21a, Spring 03

FINAL EXAM SOLUTIONS Math 21a, Spring 03 INAL EXAM SOLUIONS Math 21a, Spring 3 Name: Start by printing your name in the above box and check your section in the box to the left. MW1 Ken Chung MW1 Weiyang Qiu MW11 Oliver Knill h1 Mark Lucianovic

More information

Particular Solution to a Time-Fractional Heat Equation

Particular Solution to a Time-Fractional Heat Equation Particular Solution to a Time-Fractional Heat Equation Simon P. Kelow Kevin M. Hayden (SPK39@nau.edu) (Kevin.Hayden@nau.edu) July 21, 2013 Abstract When the derivative of a function is non-integer order,

More information

Nonlinear Systems of Ordinary Differential Equations

Nonlinear Systems of Ordinary Differential Equations Differential Equations Massoud Malek Nonlinear Systems of Ordinary Differential Equations Dynamical System. A dynamical system has a state determined by a collection of real numbers, or more generally

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

Math 115 Spring 2011 Written Homework 5 Solutions

Math 115 Spring 2011 Written Homework 5 Solutions . Evaluate each series. a) 4 7 0... 55 Math 5 Spring 0 Written Homework 5 Solutions Solution: We note that the associated sequence, 4, 7, 0,..., 55 appears to be an arithmetic sequence. If the sequence

More information

Mark Howell Gonzaga High School, Washington, D.C.

Mark Howell Gonzaga High School, Washington, D.C. Be Prepared for the Calculus Exam Mark Howell Gonzaga High School, Washington, D.C. Martha Montgomery Fremont City Schools, Fremont, Ohio Practice exam contributors: Benita Albert Oak Ridge High School,

More information

1 Sufficient statistics

1 Sufficient statistics 1 Sufficient statistics A statistic is a function T = rx 1, X 2,, X n of the random sample X 1, X 2,, X n. Examples are X n = 1 n s 2 = = X i, 1 n 1 the sample mean X i X n 2, the sample variance T 1 =

More information

Math 461 Fall 2006 Test 2 Solutions

Math 461 Fall 2006 Test 2 Solutions Math 461 Fall 2006 Test 2 Solutions Total points: 100. Do all questions. Explain all answers. No notes, books, or electronic devices. 1. [105+5 points] Assume X Exponential(λ). Justify the following two

More information

Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics

Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics Undergraduate Notes in Mathematics Arkansas Tech University Department of Mathematics An Introductory Single Variable Real Analysis: A Learning Approach through Problem Solving Marcel B. Finan c All Rights

More information

Solutions to Practice Problems

Solutions to Practice Problems Higher Geometry Final Exam Tues Dec 11, 5-7:30 pm Practice Problems (1) Know the following definitions, statements of theorems, properties from the notes: congruent, triangle, quadrilateral, isosceles

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

Intermediate Value Theorem, Rolle s Theorem and Mean Value Theorem

Intermediate Value Theorem, Rolle s Theorem and Mean Value Theorem Intermediate Value Theorem, Rolle s Theorem and Mean Value Theorem February 21, 214 In many problems, you are asked to show that something exists, but are not required to give a specific example or formula

More information

Transmission Lines. Smith Chart

Transmission Lines. Smith Chart Smith Chart The Smith chart is one of the most useful graphical tools for high frequency circuit applications. The chart provides a clever way to visualize complex functions and it continues to endure

More information

Week 3: Consumer and Firm Behaviour: The Work-Leisure Decision and Profit Maximization

Week 3: Consumer and Firm Behaviour: The Work-Leisure Decision and Profit Maximization AROEOOIS 2006 Week 3: onsumer and Firm Behaviour: The Work-Leisure Decision and Profit aximization Questions for Review 1. How are a consumer s preferences over goods represented? By utiity functions:

More information

SOLUTIONS TO HOMEWORK ASSIGNMENT #4, MATH 253

SOLUTIONS TO HOMEWORK ASSIGNMENT #4, MATH 253 SOLUTIONS TO HOMEWORK ASSIGNMENT #4, MATH 253 1. Prove that the following differential equations are satisfied by the given functions: (a) 2 u + 2 u 2 y + 2 u 2 z =0,whereu 2 =(x2 + y 2 + z 2 ) 1/2. (b)

More information

5.3 Improper Integrals Involving Rational and Exponential Functions

5.3 Improper Integrals Involving Rational and Exponential Functions Section 5.3 Improper Integrals Involving Rational and Exponential Functions 99.. 3. 4. dθ +a cos θ =, < a

More information

Math 267 - Practice exam 2 - solutions

Math 267 - Practice exam 2 - solutions C Roettger, Fall 13 Math 267 - Practice exam 2 - solutions Problem 1 A solution of 10% perchlorate in water flows at a rate of 8 L/min into a tank holding 200L pure water. The solution is kept well stirred

More information

Name: ID: Discussion Section:

Name: ID: Discussion Section: Math 28 Midterm 3 Spring 2009 Name: ID: Discussion Section: This exam consists of 6 questions: 4 multiple choice questions worth 5 points each 2 hand-graded questions worth a total of 30 points. INSTRUCTIONS:

More information

SAT Math Facts & Formulas

SAT Math Facts & Formulas Numbers, Sequences, Factors SAT Mat Facts & Formuas Integers:..., -3, -2, -1, 0, 1, 2, 3,... Reas: integers pus fractions, decimas, and irrationas ( 2, 3, π, etc.) Order Of Operations: Aritmetic Sequences:

More information

RAJALAKSHMI ENGINEERING COLLEGE MA 2161 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS PART A

RAJALAKSHMI ENGINEERING COLLEGE MA 2161 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS PART A RAJALAKSHMI ENGINEERING COLLEGE MA 26 UNIT I - ORDINARY DIFFERENTIAL EQUATIONS. Solve (D 2 + D 2)y = 0. 2. Solve (D 2 + 6D + 9)y = 0. PART A 3. Solve (D 4 + 4)x = 0 where D = d dt 4. Find Particular Integral:

More information

Trigonometric Functions and Triangles

Trigonometric Functions and Triangles Trigonometric Functions and Triangles Dr. Philippe B. Laval Kennesaw STate University August 27, 2010 Abstract This handout defines the trigonometric function of angles and discusses the relationship between

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

Math 22B, Homework #8 1. y 5y + 6y = 2e t

Math 22B, Homework #8 1. y 5y + 6y = 2e t Math 22B, Homework #8 3.7 Problem # We find a particular olution of the ODE y 5y + 6y 2e t uing the method of variation of parameter and then verify the olution uing the method of undetermined coefficient.

More information

Linear Equations and Inequalities

Linear Equations and Inequalities Linear Equations and Inequalities Section 1.1 Prof. Wodarz Math 109 - Fall 2008 Contents 1 Linear Equations 2 1.1 Standard Form of a Linear Equation................ 2 1.2 Solving Linear Equations......................

More information

RESONANCES AND BALLS IN OBSTACLE SCATTERING WITH NEUMANN BOUNDARY CONDITIONS

RESONANCES AND BALLS IN OBSTACLE SCATTERING WITH NEUMANN BOUNDARY CONDITIONS RESONANCES AND BALLS IN OBSTACLE SCATTERING WITH NEUMANN BOUNDARY CONDITIONS T. J. CHRISTIANSEN Abstract. We consider scattering by an obstacle in R d, d 3 odd. We show that for the Neumann Laplacian if

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

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

Review Solutions MAT V1102. 1. (a) If u = 4 x, then du = dx. Hence, substitution implies 1. dx = du = 2 u + C = 2 4 x + C.

Review Solutions MAT V1102. 1. (a) If u = 4 x, then du = dx. Hence, substitution implies 1. dx = du = 2 u + C = 2 4 x + C. Review Solutions MAT V. (a) If u 4 x, then du dx. Hence, substitution implies dx du u + C 4 x + C. 4 x u (b) If u e t + e t, then du (e t e t )dt. Thus, by substitution, we have e t e t dt e t + e t u

More information

Section 5.1 Continuous Random Variables: Introduction

Section 5.1 Continuous Random Variables: Introduction Section 5. Continuous Random Variables: Introduction Not all random variables are discrete. For example:. Waiting times for anything (train, arrival of customer, production of mrna molecule from gene,

More information

[1] Diagonal factorization

[1] Diagonal factorization 8.03 LA.6: Diagonalization and Orthogonal Matrices [ Diagonal factorization [2 Solving systems of first order differential equations [3 Symmetric and Orthonormal Matrices [ Diagonal factorization Recall:

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

MATH PROBLEMS, WITH SOLUTIONS

MATH PROBLEMS, WITH SOLUTIONS MATH PROBLEMS, WITH SOLUTIONS OVIDIU MUNTEANU These are free online notes that I wrote to assist students that wish to test their math skills with some problems that go beyond the usual curriculum. These

More information

The Mean Value Theorem

The Mean Value Theorem The Mean Value Theorem THEOREM (The Extreme Value Theorem): If f is continuous on a closed interval [a, b], then f attains an absolute maximum value f(c) and an absolute minimum value f(d) at some numbers

More information

Probability Calculator

Probability Calculator Chapter 95 Introduction Most statisticians have a set of probability tables that they refer to in doing their statistical wor. This procedure provides you with a set of electronic statistical tables that

More information

Inner Product Spaces

Inner 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 information

1.3. DOT PRODUCT 19. 6. If θ is the angle (between 0 and π) between two non-zero vectors u and v,

1.3. DOT PRODUCT 19. 6. If θ is the angle (between 0 and π) between two non-zero vectors u and v, 1.3. DOT PRODUCT 19 1.3 Dot Product 1.3.1 Definitions and Properties The dot product is the first way to multiply two vectors. The definition we will give below may appear arbitrary. But it is not. It

More information

Calculus with Parametric Curves

Calculus with Parametric Curves Calculus with Parametric Curves Suppose f and g are differentiable functions and we want to find the tangent line at a point on the parametric curve x f(t), y g(t) where y is also a differentiable function

More information

Representation of functions as power series

Representation 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 information

Techniques of Mathematical Modelling. Warning: these are rather longer than actual fhs questions would be. In parts they are also somewhat harder.

Techniques of Mathematical Modelling. Warning: these are rather longer than actual fhs questions would be. In parts they are also somewhat harder. Specimen fhs questions. Techniques of Mathematical Modelling Warning: these are rather longer than actual fhs questions would be. In parts they are also somewhat harder. 1. Explain what is meant by a conservation

More information

TOPIC 4: DERIVATIVES

TOPIC 4: DERIVATIVES TOPIC 4: DERIVATIVES 1. The derivative of a function. Differentiation rules 1.1. The slope of a curve. The slope of a curve at a point P is a measure of the steepness of the curve. If Q is a point on the

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

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

Signal detection and goodness-of-fit: the Berk-Jones statistics revisited

Signal detection and goodness-of-fit: the Berk-Jones statistics revisited Signal detection and goodness-of-fit: the Berk-Jones statistics revisited Jon A. Wellner (Seattle) INET Big Data Conference INET Big Data Conference, Cambridge September 29-30, 2015 Based on joint work

More information

Calculus AB 2014 Scoring Guidelines

Calculus AB 2014 Scoring Guidelines P Calculus B 014 Scoring Guidelines 014 The College Board. College Board, dvanced Placement Program, P, P Central, and the acorn logo are registered trademarks of the College Board. P Central is the official

More information

Math 319 Problem Set #3 Solution 21 February 2002

Math 319 Problem Set #3 Solution 21 February 2002 Math 319 Problem Set #3 Solution 21 February 2002 1. ( 2.1, problem 15) Find integers a 1, a 2, a 3, a 4, a 5 such that every integer x satisfies at least one of the congruences x a 1 (mod 2), x a 2 (mod

More information

Feb 28 Homework Solutions Math 151, Winter 2012. Chapter 6 Problems (pages 287-291)

Feb 28 Homework Solutions Math 151, Winter 2012. Chapter 6 Problems (pages 287-291) Feb 8 Homework Solutions Math 5, Winter Chapter 6 Problems (pages 87-9) Problem 6 bin of 5 transistors is known to contain that are defective. The transistors are to be tested, one at a time, until the

More information

Fourth-Order Compact Schemes of a Heat Conduction Problem with Neumann Boundary Conditions

Fourth-Order Compact Schemes of a Heat Conduction Problem with Neumann Boundary Conditions Fourth-Order Compact Schemes of a Heat Conduction Problem with Neumann Boundary Conditions Jennifer Zhao, 1 Weizhong Dai, Tianchan Niu 1 Department of Mathematics and Statistics, University of Michigan-Dearborn,

More information

Chapter 22: The Electric Field. Read Chapter 22 Do Ch. 22 Questions 3, 5, 7, 9 Do Ch. 22 Problems 5, 19, 24

Chapter 22: The Electric Field. Read Chapter 22 Do Ch. 22 Questions 3, 5, 7, 9 Do Ch. 22 Problems 5, 19, 24 Chapter : The Electric Field Read Chapter Do Ch. Questions 3, 5, 7, 9 Do Ch. Problems 5, 19, 4 The Electric Field Replaces action-at-a-distance Instead of Q 1 exerting a force directly on Q at a distance,

More information

MATH 31B: MIDTERM 1 REVIEW. 1. Inverses. yx 3y = 1. x = 1 + 3y y 4( 1) + 32 = 1

MATH 31B: MIDTERM 1 REVIEW. 1. Inverses. yx 3y = 1. x = 1 + 3y y 4( 1) + 32 = 1 MATH 3B: MIDTERM REVIEW JOE HUGHES. Inverses. Let f() = 3. Find the inverse g() for f. Solution: Setting y = ( 3) and solving for gives and g() = +3. y 3y = = + 3y y. Let f() = 4 + 3. Find a domain on

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

JANUARY 2016 EXAMINATIONS. Life Insurance I

JANUARY 2016 EXAMINATIONS. Life Insurance I PAPER CODE NO. MATH 273 EXAMINER: Dr. C. Boado-Penas TEL.NO. 44026 DEPARTMENT: Mathematical Sciences JANUARY 2016 EXAMINATIONS Life Insurance I Time allowed: Two and a half hours INSTRUCTIONS TO CANDIDATES:

More information