HOMEWORK 4 SOLUTIONS. All questions are from Vector Calculus, by Marsden and Tromba

Similar documents
Math 53 Worksheet Solutions- Minmax and Lagrange

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

(a) We have x = 3 + 2t, y = 2 t, z = 6 so solving for t we get the symmetric equations. x 3 2. = 2 y, z = 6. t 2 2t + 1 = 0,

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

Math 241, Exam 1 Information.

Solutions for Review Problems

Section 12.6: Directional Derivatives and the Gradient Vector

( 1) = 9 = 3 We would like to make the length 6. The only vectors in the same direction as v are those

SECOND DERIVATIVE TEST FOR CONSTRAINED EXTREMA

DERIVATIVES AS MATRICES; CHAIN RULE

A QUICK GUIDE TO THE FORMULAS OF MULTIVARIABLE CALCULUS

Linear and quadratic Taylor polynomials for functions of several variables.

Limits and Continuity

Math 265 (Butler) Practice Midterm II B (Solutions)

Name: ID: Discussion Section:

Constrained optimization.

Practice with Proofs

Solutions to Homework 5

L 2 : x = s + 1, y = s, z = 4s Suppose that C has coordinates (x, y, z). Then from the vector equality AC = BD, one has

Figure 1.1 Vector A and Vector F

Math 120 Final Exam Practice Problems, Form: A

Practice Final Math 122 Spring 12 Instructor: Jeff Lang

Lecture 2. Marginal Functions, Average Functions, Elasticity, the Marginal Principle, and Constrained Optimization

8 Polynomials Worksheet

5.3 The Cross Product in R 3

Adding vectors We can do arithmetic with vectors. We ll start with vector addition and related operations. Suppose you have two vectors

Math 432 HW 2.5 Solutions

Section 13.5 Equations of Lines and Planes

TOPIC 4: DERIVATIVES

Increasing for all. Convex for all. ( ) Increasing for all (remember that the log function is only defined for ). ( ) Concave for all.

Two vectors are equal if they have the same length and direction. They do not

+ 4θ 4. We want to minimize this function, and we know that local minima occur when the derivative equals zero. Then consider

This makes sense. t /t 2 dt = 1. t t 2 + 1dt = 2 du = 1 3 u3/2 u=5

4.3 Lagrange Approximation

Class Meeting # 1: Introduction to PDEs

Partial f (x; y) x f (x; x2 y2 and then we evaluate the derivative as if y is a constant.

Economics 121b: Intermediate Microeconomics Problem Set 2 1/20/10

In this section, we will consider techniques for solving problems of this type.

Section 3.2 Polynomial Functions and Their Graphs

Average rate of change of y = f(x) with respect to x as x changes from a to a + h:

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

Solutions to Practice Problems for Test 4

MATH 425, PRACTICE FINAL EXAM SOLUTIONS.

FINAL EXAM SOLUTIONS Math 21a, Spring 03

constraint. Let us penalize ourselves for making the constraint too big. We end up with a

5 Double Integrals over Rectangular Regions

Fundamental Theorems of Vector Calculus

Scalar Valued Functions of Several Variables; the Gradient Vector

Lecture 14: Section 3.3

Chapter 9. Systems of Linear Equations

Section 9.5: Equations of Lines and Planes

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

Linear Algebra Notes for Marsden and Tromba Vector Calculus

Homework # 3 Solutions

Unified Lecture # 4 Vectors

Solutions to Homework 10

SOLUTIONS TO HOMEWORK ASSIGNMENT #4, MATH 253

Functions. MATH 160, Precalculus. J. Robert Buchanan. Fall Department of Mathematics. J. Robert Buchanan Functions

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

Calculus 1: Sample Questions, Final Exam, Solutions

Exam 1 Sample Question SOLUTIONS. y = 2x

Module 1 : Conduction. Lecture 5 : 1D conduction example problems. 2D conduction

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

MATH 10550, EXAM 2 SOLUTIONS. x 2 + 2xy y 2 + x = 2

Numerisches Rechnen. (für Informatiker) M. Grepl J. Berger & J.T. Frings. Institut für Geometrie und Praktische Mathematik RWTH Aachen

Chapter 6. Linear Transformation. 6.1 Intro. to Linear Transformation

Høgskolen i Narvik Sivilingeniørutdanningen

Understanding Basic Calculus

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

An Introduction to Partial Differential Equations

CHAPTER 2. Eigenvalue Problems (EVP s) for ODE s

Lagrange Interpolation is a method of fitting an equation to a set of points that functions well when there are few points given.

BALTIC OLYMPIAD IN INFORMATICS Stockholm, April 18-22, 2009 Page 1 of?? ENG rectangle. Rectangle

6. Differentiating the exponential and logarithm functions

Consumer Theory. The consumer s problem

Recall that two vectors in are perpendicular or orthogonal provided that their dot

2 Integrating Both Sides

JUST THE MATHS UNIT NUMBER 8.5. VECTORS 5 (Vector equations of straight lines) A.J.Hobson

Math 113 HW #7 Solutions

Representation of functions as power series

DIFFERENTIABILITY OF COMPLEX FUNCTIONS. Contents

Section 3.7. Rolle s Theorem and the Mean Value Theorem. Difference Equations to Differential Equations

Homework #2 Solutions

Multi-variable Calculus and Optimization

Definition: A vector is a directed line segment that has and. Each vector has an initial point and a terminal point.

Lecture L26-3D Rigid Body Dynamics: The Inertia Tensor

The Heat Equation. Lectures INF2320 p. 1/88

1 if 1 x 0 1 if 0 x 1

Answers to the Practice Problems for Test 2

Numerical Methods for Differential Equations

Circle Name: Radius: Diameter: Chord: Secant:

5 Numerical Differentiation

9.4. The Scalar Product. Introduction. Prerequisites. Learning Style. Learning Outcomes

Rotation Matrices and Homogeneous Transformations

Equations, Inequalities & Partial Fractions

Rolle s Theorem. q( x) = 1

Section 1.4. Lines, Planes, and Hyperplanes. The Calculus of Functions of Several Variables

Lecture 5 Principal Minors and the Hessian

10.2 Series and Convergence

Equations Involving Lines and Planes Standard equations for lines in space

Transcription:

HOMEWORK SOLUTIONS All questions are from Vector Calculus, by Marsden and Tromba Question :..6 Let w = f(x, y) be a function of two variables, and let x = u + v, y = u v. Show that Solution. By the chain rule, w u v = w w y. Thus, i.e., w u v = u w v = w v + w v = w x w y. ( ) w = v u (w x w y ) = u w x u w y ( wy u + w y u = w x u + w x u = w xx + w xy (w yx + w yy ) = w xx w yy w u v = w w y. ) Question :.. (a) : Show that the function g(x, t) = + e t sin x satisfies the heat equation: g t = g xx. [Here g(x, t) represents the temperature in a metal rod at position x and time t.] (b) : Sketch the graph of g for t. (Hint: Look at sections by the planes t =, t =, and t =.) (c) : What happens to g(x, t) as t? Interpret this limit in terms of the behavior of heat in the rod. Solution. (a) : Since g(x, y) = + e t sin x, then g t = e t sin x, g x = e t cos x, and g xx = e t sin x. Therefore, g t = g xx. (b) : The graph of g is shown in Figure. Date: Math c Practical, 8.

HOMEWORK SOLUTIONS t = t = t = z x t Figure. The graph of g at t =,, and. (c) : Note that lim g(x, t) = lim ( + t t e t sin x) = This means that the temperature in the rod at position x tends to be a constant (= ) as the time t is large enough. Question :.. Determine the second-order Taylor formula for f(x, y) = x + y + about x =, y =. Solution. We first compute the partial derivatives up through second order: f x = f xy = f xx = f yy = x ( + x + y ), f y y = ( + x + y ) 8xy ( + x + y ), f 8xy yx = ( + x + y ) ( + x + y ) + 8x ( + x + y ) ( + x + y ) + 8y ( + x + y ).

HOMEWORK SOLUTIONS Next, we evaluate these derivatives at (, ), obtaining and f x (, ) = f y (, ) =, f xy (, ) = f yx (, ) = f xx (, ) = f yy (, ) =. Therefore, the second order Taylor formula is where h = (h, h ) and where f(h) = h h + R (, h), R (, h) h as h. Question :..6 Determine the second-order Taylor formula for the function expanded about the point x =, y =. f(x, y) = e (x ) cos y Solution. The ingredients needed in the second-order Taylor formula are computed as follows: f x = (x )e (x ) cos y f y = e (x ) sin y f xx = e (x ) cos y + (x ) e (x ) cos y f xy = (x )e (x ) sin y = f yx f yy = e (x ) cos y. Evaluating the function and these derivatives at the point (, ) gives f(, ) = f x (, ) = f y (, ) = f xx (, ) = f xy (, ) = f yx (, ) = and f yy (, ) =. Consequently, the second order Taylor formula is where h = (h, h ) and where f(h) = + h h + R ((, ), h), R ((, ), h) h as h. Question 5:..7 Find the critical points for the function f(x, y) = x + xy + x + y + y +. and then determine whether they are local maxima, local minima, or saddle points.

HOMEWORK SOLUTIONS Solution. Here, We have = 6x + y +, =, y = x + y +. y = when x = y = /. Therefore, the only critical point is ( /, /). Now, ( /, /) = 6, f y ( /, /) =, and f y ( /, /) =, which yields D = 6. = >. Therefore ( /, /) is a local minimum. Question 6:..7 Find the local maxima and minima for z = (x +y )e x y. Solution. We first locate the critical points of f(x, y) = (x + y )e x y. f(x, y) = e x y (x( y x )i + y( x y )j) Thus, f(x, y) = if and only if (x, y) = (, ), (, ±), or (±, ). To determine whether they are maxima or minima, we need to calculate the second partial derivatives. = ( + x y + x (6y 5))e x y = ( 5y + 6y + x (y ))e x y, and y y = (y + x )e x y. Therefore, f (, ) = e, f y (, ) = 6e, and f y (, ) =, which yields D = (e)(6e) = e >, and (, ) is a local minimum. (, ±) =, f y (, ±) =, and f y (, ±) =, which yields D = ( )( ) = >, and (, ±) are local maxima. (±, ) =, f y (±, ) =, and f y (, ±) =, which yields D = ( )() = 6 <, and (±, ) are saddle points. Question 7:..5 Write the number as a sum of three numbers so that the sum of the products taken two at a time is a maximum. Solution. Let the three numbers be x, y, z. Thus, We want to find the maximum value for We differentiate to get x + y + z =, z = x y. S(x, y) = xy + yz + xz = xy + (x + y)( x y) = x xy y + x + y. S S = x y +, y = x y +. These vanish when x = y =, then z = (x + y) =. Therefore, when x = y = z = is the only critical point. The condition x, y, z describes a cube in R and on the boundary of the cube (either x =, x =, y =, y =, z =, z = ), S is zero. Therefore the maximum of S occurs on the interior of this cube, i.e., at a local maximum. Since x =, y =, z = is the only critical point, it must be a maximum.

HOMEWORK SOLUTIONS 5 Question 8:.. Find the extrema of f(x, y) = x y subject to the constraint x y =. Solution. By the method of Lagrange multipliers, we write the constraint as g =, where g(x, y) = x y and then write the Lagrange multiplier equations as f = λ g. Thus, we get = λ x = λ y x y =. First of all, the first two equations imply that x and y. Hence we can eliminate λ, giving x = y. From the last equation this would imply that =. Hence there are no extrema. Question 9:.. Let P be a point on a surface S in R defined by the equation f(x, y, z) =, where f is of class C. Suppose that P is a point where the distance from the origin to S is maximized. Show that the vector emanating from the origin and ending at P is perpendicular to S. Solution. We want to maximize the function g(x, y, z) = x + y + z subject to the constraint f(x, y, z) =. Suppose this maximum occurs at P = (x, y, z ), then by the method of Lagrange multipliers we have the equations x = λ { f(x, y, z )} y = λ { f(x, y, z )} z = λ { f(x, y, z )} where { f(x, y, z )} i denotes the ith component of f(x, y, z ), i. If v = (x, y, z ) is the vector from the origin ending at P, then these equations say that v = ( ) λ f(x, y, z ). But f(x, y, z ) is perpendicular to S at P, and since v is a scalar multiple of f(x, y, z ) it is also perpendicular to S at P. Question :..8 A company s production function is Q(x, y) = xy. The cost of production is C(x, y) = x + y. If this company can spend C(x, y) =, what is the maximum quantity that can be produced? Solution. We want to maximize Q subject to the constraint C(x, y) =. Since both x, y, this imposes the condition that x 5, y /. Thus, we wish to maximize Q on the line segment x+y =, x, y. If the maximum occurs at an interior point (x, y ) of this segment, then Q(x, y ) = λ C(x, y ); that is, y = λ x = λ x + y =. Thus 6λ + 6λ =, λ = 5/6, y = 5/, x = 5/, Q(x, y ) = 5/6. The value of Q at the endpoints of this segment are Q(, ) = = Q(5, ). Consequently the maximum occurs at (5/, 5/) and the maximum value of Q is 5/6.