i + u 2 j be the unit vector that has its initial point at (a, b) and points in the desired direction. It determines a line in the xy-plane:

Similar documents
14.4. Tangent Planes. Tangent Planes. Tangent Planes. Tangent Planes. Partial Derivatives. Tangent Planes and Linear Approximations

FUNCTIONS OF SEVERAL VARIABLES AND PARTIAL DIFFERENTIATION

MATH 8 FALL 2010 CLASS 27, 11/19/ Directional derivatives Recall that the definitions of partial derivatives of f(x, y) involved limits

Definitions and claims functions of several variables

CHAPTER 11 PARTIAL DERIVATIVES

Test Yourself. 11. The angle in degrees between u and w. 12. A vector parallel to v, but of length 2.

The Chain Rule, Higher Partial Derivatives & Opti- mization

Exam 2 Review Sheet. r(t) = x(t), y(t), z(t)

WESI 205 Workbook. 1 Review. 2 Graphing in 3D

LECTURE 19 - LAGRANGE MULTIPLIERS

MATH 105: Midterm #1 Practice Problems

Lecture 4 : Monday April 6th

Discussion 8 Solution Thursday, February 10th. Consider the function f(x, y) := y 2 x 2.

Exam 2 Summary. 1. The domain of a function is the set of all possible inputes of the function and the range is the set of all outputs.

Practice problems from old exams for math 233

266&deployment= &UserPass=b3733cde68af274d036da170749a68f6

Mock final exam Math fall 2007

Calculus II Fall 2014

MATH 259 FINAL EXAM. Friday, May 8, Alexandra Oleksii Reshma Stephen William Klimova Mostovyi Ramadurai Russel Boney A C D G H B F E

Review guide for midterm 2 in Math 233 March 30, 2009

Math 5BI: Problem Set 1 Linearizing functions of several variables

2.1 Partial Derivatives

MATH 12 CLASS 9 NOTES, OCT Contents 1. Tangent planes 1 2. Definition of differentiability 3 3. Differentials 4

This exam contains 9 problems. CHECK THAT YOU HAVE A COMPLETE EXAM.

Practice problems from old exams for math 233

Section 15.3 Partial Derivatives

[f(t)] 2 + [g(t)] 2 + [h(t)] 2 dt. [f(u)] 2 + [g(u)] 2 + [h(u)] 2 du. The Fundamental Theorem of Calculus implies that s(t) is differentiable and

Review Problems. Calculus IIIA: page 1 of??

MATH 261 EXAM II PRACTICE PROBLEMS

Final Exam Review Problems. P 1. Find the critical points of f(x, y) = x 2 y + 2y 2 8xy + 11 and classify them.

SOLUTIONS 2. PRACTICE EXAM 2. HOURLY. Problem 1) TF questions (20 points) Circle the correct letter. No justifications are needed.

the input values of a function. These are the angle values for trig functions

Math 148 Exam III Practice Problems

MATH Exam 2 Solutions November 16, 2015

Section 14.3 Partial Derivatives

Functions of several variables

11.2 LIMITS AND CONTINUITY

Math Final Exam - 6/11/2015

Unit 7 Partial Derivatives and Optimization

MATH Review Exam II 03/06/11

(d) If a particle moves at a constant speed, then its velocity and acceleration are perpendicular.

Lecture 19 - Partial Derivatives and Extrema of Functions of Two Variables

ES 111 Mathematical Methods in the Earth Sciences Lecture Outline 6 - Tues 17th Oct 2017 Functions of Several Variables and Partial Derivatives

Instructions: Good luck! Math 21a Second Midterm Exam Spring, 2009

11.7 Maximum and Minimum Values

On Surfaces of Revolution whose Mean Curvature is Constant

Calculus 3 Exam 2 31 October 2017

Graphs of sin x and cos x

VectorPlot[{y^2-2x*y,3x*y-6*x^2},{x,-5,5},{y,-5,5}]

Lecture 19. Vector fields. Dan Nichols MATH 233, Spring 2018 University of Massachusetts. April 10, 2018.

Math for Economics 1 New York University FINAL EXAM, Fall 2013 VERSION A

1. Vector Fields. f 1 (x, y, z)i + f 2 (x, y, z)j + f 3 (x, y, z)k.

Chapter 9 Linear equations/graphing. 1) Be able to graph points on coordinate plane 2) Determine the quadrant for a point on coordinate plane

1. Let f(x, y) = 4x 2 4xy + 4y 2, and suppose x = cos t and y = sin t. Find df dt using the chain rule.

Goals: To study constrained optimization; that is, the maximizing or minimizing of a function subject to a constraint (or side condition).

Differentiable functions (Sec. 14.4)

Exam 1 Study Guide. Math 223 Section 12 Fall Student s Name

Review Sheet for Math 230, Midterm exam 2. Fall 2006

MATH 234 THIRD SEMESTER CALCULUS

REVIEW SHEET FOR MIDTERM 2: ADVANCED

Directional Derivative, Gradient and Level Set

Independence of Path and Conservative Vector Fields

DIFFERENTIAL EQUATIONS. A principal model of physical phenomena.

B) 0 C) 1 D) No limit. x2 + y2 4) A) 2 B) 0 C) 1 D) No limit. A) 1 B) 2 C) 0 D) No limit. 8xy 6) A) 1 B) 0 C) π D) -1

Math 206 First Midterm February 1, 2012

Partial Differentiation 1 Introduction

Similarly, the point marked in red below is a local minimum for the function, since there are no points nearby that are lower than it:

4 to find the dimensions of the rectangle that have the maximum area. 2y A =?? f(x, y) = (2x)(2y) = 4xy

Section 3: Functions of several variables.

7/26/2018 SECOND HOURLY PRACTICE I Maths 21a, O.Knill, Summer Name:

ANSWER KEY. (a) For each of the following partials derivatives, use the contour plot to decide whether they are positive, negative, or zero.

MATH 20C: FUNDAMENTALS OF CALCULUS II FINAL EXAM

S56 (5.1) Logs and Exponentials.notebook October 14, 2016

MATH 253 Page 1 of 7 Student-No.: Midterm 2 November 16, 2016 Duration: 50 minutes This test has 4 questions on 7 pages, for a total of 40 points.

Maxima and Minima. Terminology note: Do not confuse the maximum f(a, b) (a number) with the point (a, b) where the maximum occurs.

Chapter 16. Partial Derivatives

Calculus II Final Exam Key

Double Integrals over More General Regions

Examples: Find the domain and range of the function f(x, y) = 1 x y 2.

18.3. Stationary Points. Introduction. Prerequisites. Learning Outcomes

10.1 Curves defined by parametric equations

Name: ID: Section: Math 233 Exam 2. Page 1. This exam has 17 questions:

I II III IV V VI VII VIII IX X Total

Unit 8 Trigonometry. Math III Mrs. Valentine

University of California, Berkeley Department of Mathematics 5 th November, 2012, 12:10-12:55 pm MATH 53 - Test #2

Estimating Areas. is reminiscent of a Riemann Sum and, amazingly enough, will be called a Riemann Sum. Double Integrals

Pre Calc. Conics.

WJEC LEVEL 2 CERTIFICATE 9550/01 ADDITIONAL MATHEMATICS

PREREQUISITE/PRE-CALCULUS REVIEW

Section 5.2 Graphs of the Sine and Cosine Functions

Mathematics Lecture. 3 Chapter. 1 Trigonometric Functions. By Dr. Mohammed Ramidh

Math Final Exam - 6/13/2013

Functions of more than one variable

INTEGRATION OVER NON-RECTANGULAR REGIONS. Contents 1. A slightly more general form of Fubini s Theorem

Mathematics (Project Maths Phase 2)

Section 8.4: The Equations of Sinusoidal Functions

Maxima and Minima. Chapter Local and Global extrema. 5.2 Continuous functions on closed and bounded sets Definition of global extrema

Calculus of Several Variables

VECTOR CALCULUS Julian.O 2016

Math 1205 Trigonometry Review

Transcription:

1 Directional Derivatives and Gradients Suppose we need to compute the rate of change of f(x, y) with respect to the distance from a point (a, b) in some direction. Let u = u 1 i + u 2 j be the unit vector that has its initial point at (a, b) and points in the desired direction. It determines a line in the xy-plane: x = a + s u 1, y = b + s u 2 where s is the arc length parameter that has its reference point at (a, b) and has positive values in the direction of u. Definition. The directional derivative of f(x, y) in the direction of u at (a, b) is denoted by D u f(a, b) and is defined by D u f(a, b) = d ds [f(a + s u 1, b + s u 2 )] = f x (a, b) u 1 + f y (a, b) u 2 s=0 provided this derivative exists. Analytically, D u f(a, b) is the instantaneous rate of change of f(x, y) with respect to the distance in the direction of u at the point (a, b). Geometrically, D u f(a, b) is the slope of the surface z = f(x, y) in the direction of u at the point (a, b, f(a, b)). 1

Generalisation to f(x, y, z) (and f(x 1,..., x n )) is straightforward. Definition. Let u = u 1 i + u 2 j + u 3 k be a unit vector. The directional derivative of f(x, y, z) in the direction of u at (a, b, c) is denoted by D u f(a, b, c) and is defined by D u f(a, b, c) = d ds [f(a + s u 1, b + s u 2, c + s u 3 )] s=0 = f x (a, b, c) u 1 + f y (a, b, c) u 2 + f z (a, b, c) u 3 Example. Find D u f(2, 1) in the direction of a = 3 i + 4 j ( 1 f(x, y) = ln 3 ) 2 e2/3 12 sin(x 2y) + 8y 2 x 3 6x 2 y + 32 Answer: D u f(2, 1) = 5/3 2

The gradient Note that D u f = f x u 1 + f y u 2 + f z u 3 = (f x i + f y j + f z k) (u1 i + u 2 j + u 3 k) Definition. Let e i be the standard orthonormal coordinate basis of R n, so that r = n i=1 x i e i. The gradient of f(x 1,, x n ) is defined by In particular f(x 1,, x n ) = n i=1 f(x 1,, x n ) e i x i f(x, y) = f x (x, y) i + f y (x, y) j f(x, y, z) = f x (x, y, z) i + f y (x, y, z) j + f z (x, y, z) k The symbol is read as either nabla (from ancient Hebrew) or del (it is inverted ). D u f(a, b) = f(a, b) u, D u f(a, b, c) = f(a, b, c) u, D u f = f u Example. Find r; r = x 2 + y 2 + z 2 and D u r(1, 1, 1) in the direction of a = i + 2 j + 2 k. 3

Properties of the gradient D u f(a, b) = f(a, b) u = f(a, b) u cos θ = f(a, b) cos θ Since 1 cos θ 1, if f(a, b) 0 then the maximum value of D u f(a, b) is f(a, b) and it occurs when θ = 0, that is, when u is in the direction of f(a, b). Geometrically, the maximum slope of the surface z = f(x, y) at (a, b) is in the direction of the gradient and is equal to f(a, b). If f(a, b) = 0 then D u f(a, b) = 0 in all directions at (a, b). It occurs where the surface z = f(x, y) has a relative maximum or minimum or a saddle point. 4

Since D u f(x 1,..., x n ) = f(x 1,..., x n ) cos θ, these properties hold for functions of any number of variables. Theorem. Let f be a function differentiable at a point P. 1. If f = 0 at P then all directional derivatives of f at P are 0. 2. If f 0 at P then the derivative in the direction of f at P has the largest value equal to f at P. 3. If f 0 at P then the derivative in the direction opposite to that of f at P has the smallest value equal to f at P. Example. The point P = (2, 3, 1) f(x, y, z) = 2xy + 3z 4 6 cos(3x 2y) 5

Gradients are normal to level curves and level surfaces Level curve C: f(x, y) = k. Let C be smoothly parametrised as x = x(s), y = y(s) where s is an arc length parameter. The unit tangent vector to C is T (s) = dx ds i + dy ds j Since f(x, y) is constant on C we expect D T f(x, y) = 0. Indeed D T f(x, y) = f T = (f x i + f y j) ( dx ds i + dy ds j) dx = f x ds + f dy y ds = d ds f(x(s), y(s)) = 0 f T Thus if (a, b) belongs to the level curve, and f(a, b) 0 then f(a, b) is normal to T at (a, b) and therefore to the level curve. 6

Definition. A vector is called normal to a surface at (a, b, c) if it is normal to a tangent vector to any curve on the surface through (a, b, c). Level surface σ: F (x, y, z) = k Let C, smoothly parametrised as x = x(s), y = y(s), z = z(s) be any curve on σ through (a, b, c). The unit tangent vector to C is and D T F (x, y, z) is T (s) = dx ds i + dy ds j + dz ds k D T F (x, y, z) = F T = (F x i + F y j + F z k) ( dx ds i + dy ds j + dz ds k) dx = F x ds + F dy y ds + F dz z ds = d ds F (x(s), y(s), z(s)) = 0 F T Thus, F (a, b, c) is normal to T at (a, b, c) and therefore to σ. 7

Tangent planes Consider a level surface σ: F (x, y, z) = k, and let P = (a, b, c) belong to σ. Since F (a, b, c) is normal to tangent vectors to curves on σ through P, all these tangent vectors belong to one and the same plane. This plane is called the tangent plane to the surface σ at P. To find an equation of the tangent plane we use that if we know a vector n normal to a plane through a point r 0 = a i + b j + c k then an equation of the plane is n ( r r 0 ) = 0 n 1 (x a) + n 2 (y b) + n 3 (z c) = 0 because r r 0 is parallel to the plane and therefore normal to n. Choosing n = F (a, b, c), we get the equation of the tangent plane to the level surface σ at P = (a, b, c) F x (a, b, c)(x a) + F y (a, b, c)(y b) + F z (a, b, c)(z c) = 0 The line through P parallel to F (a, b, c) is perpendicular to the tangent plane, and is called the normal line to the surface σ at P. Its parametric equations are x = a + F x (a, b, c)t, y = b + F y (a, b, c)t, z = c + F z (a, b, c)t Example. 4x 2 + y 2 + z 2 = 18 at (2, 1, 1). Tangent plane, normal line, the angle the tangent plane makes with the xy-plane? 8

Tangent planes to z = f(x, y) The graph of a function z = f(x, y) can be thought of as the level surface of the function F (x, y, z) = f(x, y) z with constant 0. We find 1. the gradient F (a, b, c) = f x (a, b) i + f y (a, b) j k, c = f(a, b) 2. the equation of the tangent plane to the surface z = f(x, y) at (a, b, f(a, b)) f x (a, b)(x a) + f y (a, b)(y b) (z c) = 0 z = f(a, b) + f x (a, b)(x a) + f y (a, b)(y b) that is the local linear approximation of f at (a, b), 3. the parametric equations of the normal line to the surface z = f(x, y) at (a, b, f(a, b)) x = a + f x (a, b) t, y = b + f y (a, b) t, z = f(a, b) t Example. Consider the surface ( 1 z = f(x, y) = ln 3 ) 2 e2/3 12 sin(x 2y) + 8y 2 x 3 6x 2 y + 32 1. Find an equation for the tangent plane and parametric equations for the normal line to the surface at the point P = (2, 1, z 0 ) where z 0 = f(2, 1). 2. Find points of intersection of the tangent plane with the x-, y- and z-axes. Sketch the tangent plane, and show the point P on it. Sketch the normal line to the surface at P. 9