Through level curves and contour lines give some information about the function

Similar documents
30.1 Continuity of scalar fields: Definition: Theorem: Module 10 : Scaler fields, Limit and Continuity

31.1.1Partial derivatives

We have seen that for a function the partial derivatives whenever they exist, play an important role. This motivates the following definition.

4 Limit and Continuity of Functions

Module 9 : Infinite Series, Tests of Convergence, Absolute and Conditional Convergence, Taylor and Maclaurin Series

43.1 Vector Fields and their properties

39.1 Absolute maxima/minima

Module 9 : Infinite Series, Tests of Convergence, Absolute and Conditional Convergence, Taylor and Maclaurin Series

To find an approximate value of the integral, the idea is to replace, on each subinterval

10.1.1Theorem: Module 4 : Local / Global Maximum / Minimum and Curve Sketching

Module 5 : Linear and Quadratic Approximations, Error Estimates, Taylor's Theorem, Newton and Picard Methods

The fundamental theorem of calculus for definite integration helped us to compute If has an anti-derivative,

Module 16 : Line Integrals, Conservative fields Green's Theorem and applications. Lecture 48 : Green's Theorem [Section 48.

11.1 Absolute Maximum/Minimum: Definition:

In this section you will learn the following : 40.1Double integrals

Module 7 : Applications of Integration - I. Lecture 20 : Definition of the power function and logarithmic function with positive base [Section 20.

8.1.1 Theorem (Chain Rule): Click here to View the Interactive animation : Applet 8.1. Module 3 : Differentiation and Mean Value Theorems

Module 1: A Crash Course in Vectors Lecture 4 : Gradient of a Scalar Function

Linear Algebra. Mark Dean. Lecture Notes for Fall 2014 PhD Class - Brown University

Module 7 : Applications of Integration - I. Lecture 21 : Relative rate of growth of functions [Section 21.1] Objectives

106 CHAPTER 3. TOPOLOGY OF THE REAL LINE. 2. The set of limit points of a set S is denoted L (S)

Module 14 : Double Integrals, Applilcations to Areas and Volumes Change of variables

We saw in the previous lectures that continuity and differentiability help to understand some aspects of a

Module 3 : Differentiation and Mean Value Theorems. Lecture 7 : Differentiation. Objectives. In this section you will learn the following :

for surface integrals, which helps to represent flux across a closed surface

8. Limit Laws. lim(f g)(x) = lim f(x) lim g(x), (x) = lim x a f(x) g lim x a g(x)

5.5 Deeper Properties of Continuous Functions

11.1 Vectors in the plane

x 2 For example, Theorem If S 1, S 2 are subspaces of R n, then S 1 S 2 is a subspace of R n. Proof. Problem 3.

Ordinary Differential Equation Introduction and Preliminaries

Lecture 29 Relevant sections in text: 3.9

Student Outcomes. Lesson Notes. Classwork. Example 1 (5 minutes) Students apply knowledge of geometry to writing and solving linear equations.

Module 5 : Plane Waves at Media Interface. Lecture 39 : Electro Magnetic Waves at Conducting Boundaries. Objectives

2. Introduction to commutative rings (continued)

The theory of manifolds Lecture 3

AMS 212A Applied Mathematical Methods I Appendices of Lecture 06 Copyright by Hongyun Wang, UCSC. ( ) cos2

August 23, 2017 Let us measure everything that is measurable, and make measurable everything that is not yet so. Galileo Galilei. 1.

Lecture: Cone programming. Approximating the Lorentz cone.

NCC Education Limited. Substitution Topic NCC Education Limited. Substitution Topic NCC Education Limited

Definitions and Properties of R N

Eigenvalues and Eigenvectors

Math 328 Course Notes

Name (print): Question 4. exercise 1.24 (compute the union, then the intersection of two sets)

MATRIX DETERMINANTS. 1 Reminder Definition and components of a matrix

The theory of manifolds Lecture 3. Tf : TR n TR m

Minimum and maximum values *

3.1 Asymptotic notation

Constructions with ruler and compass.

6.2 Deeper Properties of Continuous Functions

Proving the central limit theorem

Writing proofs for MATH 51H Section 2: Set theory, proofs of existential statements, proofs of uniqueness statements, proof by cases

Metric spaces and metrizability

1111: Linear Algebra I

What is proof? Lesson 1

MATH10212 Linear Algebra B Homework 7

10. Smooth Varieties. 82 Andreas Gathmann

A = , A 32 = n ( 1) i +j a i j det(a i j). (1) j=1

a. Do you think the function is linear or non-linear? Explain using what you know about powers of variables.

Lecture 04: Secret Sharing Schemes (2) Secret Sharing

Module 1 : Introduction : Review of Basic Concepts in Mechnics Lecture 4 : Static Indeterminacy of Structures

MATH 117 LECTURE NOTES

FUNCTIONAL ANALYSIS LECTURE NOTES: COMPACT SETS AND FINITE-DIMENSIONAL SPACES. 1. Compact Sets

Module 2 : Electrostatics Lecture 9 : Electrostatic Potential

Problem set #4. Due February 19, x 1 x 2 + x 3 + x 4 x 5 = 0 x 1 + x 3 + 2x 4 = 1 x 1 x 2 x 4 x 5 = 1.

2.1 Convergence of Sequences

Methods for Solving Linear Systems Part 2

From Lay, 5.4. If we always treat a matrix as defining a linear transformation, what role does diagonalisation play?

is holomorphic. In other words, a holomorphic function is a collection of compatible holomorphic functions on all charts.

Advanced Calculus I Chapter 2 & 3 Homework Solutions October 30, Prove that f has a limit at 2 and x + 2 find it. f(x) = 2x2 + 3x 2 x + 2

Lesson 8: Graphs of Simple Non Linear Functions

LECTURE 10: REVIEW OF POWER SERIES. 1. Motivation

Class IX Chapter 1 Number Sustems Maths

Chapter 2: Linear Independence and Bases

The Dirichlet s P rinciple. In this lecture we discuss an alternative formulation of the Dirichlet problem for the Laplace equation:

P = 1 F m(p ) = IP = P I = f(i) = QI = IQ = 1 F m(p ) = Q, so we are done.

Sufficient Conditions for Finite-variable Constrained Minimization

Repeated Eigenvalues and Symmetric Matrices

MTH5102 Spring 2017 HW Assignment 1: Prob. Set; Sec. 1.2, #7, 8, 12, 13, 20, 21 The due date for this assignment is 1/18/17.

3. The Sheaf of Regular Functions

COMPLEX ALGEBRAIC SURFACES CLASS 9

The Euclidean Topology

Lecture Notes on Secret Sharing

x n -2.5 Definition A list is a list of objects, where multiplicity is allowed, and order matters. For example, as lists

Module 6 : PHYSICS OF SEMICONDUCTOR DEVICES Lecture 32 : Bonding in Solids

1. Introduction to commutative rings and fields

Introduction to Bases in Banach Spaces

20.1 Detecting the Need for Structural Induction

9.4 Vector and Scalar Fields; Derivatives

Handout 2: Invariant Sets and Stability

Generell Topologi Exercise Sheet 2

2 Lecture Span, Basis and Dimensions

MATH 425, HOMEWORK 5, SOLUTIONS

Complex Analysis Slide 9: Power Series

Jim Lambers MAT 419/519 Summer Session Lecture 11 Notes

min f(x). (2.1) Objectives consisting of a smooth convex term plus a nonconvex regularization term;

Limit of a Function Philippe B. Laval

CSC321 Lecture 5 Learning in a Single Neuron

1 The Local-to-Global Lemma

22.3. Repeated Eigenvalues and Symmetric Matrices. Introduction. Prerequisites. Learning Outcomes

Lecture Notes on Metric Spaces

Transcription:

Module 10 : Scaler fields, Limit and Continuity Lecture 29 : Limit of scaler fields [Section 29.1] Objectives In this section you will learn the following : The notion of limits for scalar fields. 29.1 Limits of scalar fields Through level curves and contour lines give some information about the function sufficient to draw any definite conclusion about, they are not One would like to define concepts, as for functions of a single variable, which will help us analyze analytically. Recall that, for a function of one variable, the fundamental concept, which is used again and again to define various other concepts, is that of limit of. Intuitively, as for a function of one variable, we say approaches a limit, as approaches, if lies 'arbitrarily close' to for all points sufficiently close' to. To describe this concept of closeness' in we have the notion of distance between points. So, it is natural to say that a function of two variables has a limit as 'approaches' if the distance between and is arbitrarily' small for all points sufficiently close to. To make this definition meaningful, let us assume for the time being that is defined at all points 'sufficiently close' to, possibly not at. That is, we assume that there exists some such that. And we have the following definition. 29.1.1Definition: Let and be such that for some. We say approaches a limit as approaches, and write if for every, there is some,such that

that is, 29.1.2Examples: (i) Let Let To analyse, we first have to guess whether this limit can exists or not and if it exits, what is the possible value. Suppose it exists and is Then to prove that, we have to find for given such that Since it is obvious that if we take and chose then for a given, i.e., Hence, Similarly The functions and are projection maps on the -axis and -axis, respectively. (ii) Let We claim that Note that Thus, given, if we chose such that, then Hence, (iii) Let

where is some fixed real number. Then because given any, we can take and note that In the case of function of a real variable, the existence of limit at a point implied that both the left hand and right hand limit exist and are equal, That is, approached the same value when approached the point from the left or from the right. In, a point can be approached to along many different paths, and if the, then should approach irrespective of the path along which one approaches the point. Hence, we have the next theorem. 29.1.3Theorem (Path independence of the limit) : Let be such that for some Let be such that If is any path such that and then, 29.1.3Theorem (Path independence of the limit) : Let be such that for some Let be such that If is any path such that

and then, Proof Given, choose such that ----------(19) Also, choose, such that Then, for Hence by (19), we have 29.1.3Theorem (Path independence of the limit) : Let be such that for some Let be such that If is any path such that and then, Proof Given, choose such that ----------(19) Also, choose, such that Then, for Hence by (19), we have

29.1.4Note: From the above theorem, That is, a limit of exists and is same along every path to. This gives us a test for the nonexistence of a limit. 29.1.5Corollary(Test for non-existence of limit): If for a function either the limit of at does not exits along at least one path through or has different limits along at least two different paths through then does not exits. 29.1.6 Example: Consider the function To analyse, let us find this limit along some simple paths through, for example, along the line through the origin with slop Note that Since we have which is different along different lines. Hence, To define we required that be defined at all points sufficiently close to, except possibly at. This condition can be relaxed. All we need is that should be defined at least at points close to as close as we want. More precisely, we have the following:

29.1.7Definition: Suppose is such that for all Such a point is called a limit point of. 29.1.8Example: The point is a limit point each of the domains shown in the figure. Figure 1. is a limit point 29.1.9 Note: A limit point of a set need not belong to. However, if is a limit point of, then there exists a sequence of points of converging to 29.1.10Definition: Let is a limit point of and let We say if for all there exists a such that 29.1.11Example: Let The domain of is the set

The point but is a limit point of For any given if we choose then Hence, PRACTICE EXERCISES 1. Using definition, analyze for the following functions: (i) (ii) (iii) (iv) (v) (vi) Answers 2. Let Show that exists but does not exist for every fixed. 3. Let for some be such that If both and exists for all is a neighborhood of (0,0), show that

4. Let Show that both and exist and are equal but does not exist. Thus, the converse of exercise 3 above need not hold. 5. For analyse the existence of the following limits: 6. Another way of analysing is to write and noting that limit of as is equivalent to analysing Use this to analyse the following limits: (i) (ii) (iii) Recap Answers In this section you have learnt the following The notion of limits for scalar fields. [Section 29.2] Objectives In this section you will learn the following : Theorem that help us to compute the limits for scalar fields.

29.2 Limit theorems As in the case of function of a single variable, the following theorem is useful for computing limits. 29.2.1Theorem: Let and be a limit point of. Then the following hold: (i) if and only if for every sequence in such that (ii) If and,then and if Proof Proofs of all the statements are similar to that of functions of a single variable. To exhibit this, we prove (i). Let and choose such that ----------(20) Now, since, choose such that From (20) and (21), we have ----------(21)

Hence Conversely, let Suppose Then, there exists some such that for all, there exists with the property that Then, clearly for this sequence a contradiction. Hence We leave the proof of other parts as exercise for the reader. Back 29.2.2Example: Let us compute Since, for and using theorem 29.2.1, 29.2.3Theorem (Sandwich) : Let and be a limit point. Let there exist some such that If then Proof

Easy to prove and left as exercises. 29.2.4Example: We want to compute From the Maclaurin series expansion of, it follows that for in a neighborhood of, except at, Hence, in a neighborhood of, except the axes we have Thus, using sandwich theorem, l PRACTICE EXERCISES 1. Analyze the following: (i) (ii) Answers 2. Using Maclaurin series for, deduce that and hence deduce that 3. Using limit theorems, justify the following : (i)

(ii) (iii) (iv) Recap In this section you have learnt the following Theorem that help us to compute the limits for scalar fields.