a n. n=1 m=0 (b n b n 1 ), n=1

Similar documents
10.2 Series and Convergence

To discuss this topic fully, let us define some terms used in this and the following sets of supplemental notes.

n k=1 k=0 1/k! = e. Example 6.4. The series 1/k 2 converges in R. Indeed, if s n = n then k=1 1/k, then s 2n s n = 1 n

x a x 2 (1 + x 2 ) n.

HOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)!

Section 1.3 P 1 = 1 2. = P n = 1 P 3 = Continuing in this fashion, it should seem reasonable that, for any n = 1, 2, 3,..., =

Lectures 5-6: Taylor Series

Arithmetic Progression

CHAPTER II THE LIMIT OF A SEQUENCE OF NUMBERS DEFINITION OF THE NUMBER e.

4/1/2017. PS. Sequences and Series FROM 9.2 AND 9.3 IN THE BOOK AS WELL AS FROM OTHER SOURCES. TODAY IS NATIONAL MANATEE APPRECIATION DAY

AFM Ch.12 - Practice Test

5.3 Improper Integrals Involving Rational and Exponential Functions

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES

Undergraduate Notes in Mathematics. Arkansas Tech University Department of Mathematics

1 if 1 x 0 1 if 0 x 1

FUNCTIONAL ANALYSIS LECTURE NOTES: QUOTIENT SPACES

A power series about x = a is the series of the form

CS 103X: Discrete Structures Homework Assignment 3 Solutions

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

k, then n = p2α 1 1 pα k

THE BANACH CONTRACTION PRINCIPLE. Contents

MATH10212 Linear Algebra. Systems of Linear Equations. Definition. An n-dimensional vector is a row or a column of n numbers (or letters): a 1.

CONTINUED FRACTIONS AND PELL S EQUATION. Contents 1. Continued Fractions 1 2. Solution to Pell s Equation 9 References 12

Metric Spaces. Chapter Metrics

Math 55: Discrete Mathematics

Notes on metric spaces

MATH 4330/5330, Fourier Analysis Section 11, The Discrete Fourier Transform

Mathematical Methods of Engineering Analysis

The sample space for a pair of die rolls is the set. The sample space for a random number between 0 and 1 is the interval [0, 1].

Linear Risk Management and Optimal Selection of a Limited Number

a 11 x 1 + a 12 x a 1n x n = b 1 a 21 x 1 + a 22 x a 2n x n = b 2.

9.2 Summation Notation

Math 115 Spring 2011 Written Homework 5 Solutions

Probability Generating Functions

Taylor and Maclaurin Series

Sequences and Series

6.2 Permutations continued

Numerical Analysis Lecture Notes

I remember that when I

1. Prove that the empty set is a subset of every set.

Basic Proof Techniques

FEGYVERNEKI SÁNDOR, PROBABILITY THEORY AND MATHEmATICAL

Metric Spaces Joseph Muscat 2003 (Last revised May 2009)

Critical points of once continuously differentiable functions are important because they are the only points that can be local maxima or minima.

Mathematical Induction. Lecture 10-11

SECTION 10-2 Mathematical Induction

WRITING PROOFS. Christopher Heil Georgia Institute of Technology

An example of a computable

Ideal Class Group and Units

Introduction. Appendix D Mathematical Induction D1

GEOMETRIC SEQUENCES AND SERIES

BANACH AND HILBERT SPACE REVIEW

Solutions of Equations in One Variable. Fixed-Point Iteration II

Lecture 4: Cauchy sequences, Bolzano-Weierstrass, and the Squeeze theorem

Continued Fractions and the Euclidean Algorithm

Compound Interest. Invest 500 that earns 10% interest each year for 3 years, where each interest payment is reinvested at the same rate:

How To Understand The Theory Of Hyperreals

Solutions for Practice problems on proofs

Properties of sequences Since a sequence is a special kind of function it has analogous properties to functions:

E3: PROBABILITY AND STATISTICS lecture notes

v w is orthogonal to both v and w. the three vectors v, w and v w form a right-handed set of vectors.

Notes on Determinant

mod 10 = mod 10 = 49 mod 10 = 9.

TOPIC 4: DERIVATIVES

Math 231b Lecture 35. G. Quick

Mathematics 31 Pre-calculus and Limits

Math 4310 Handout - Quotient Vector Spaces

Continued Fractions. Darren C. Collins

MATH 132: CALCULUS II SYLLABUS

16.3 Fredholm Operators

MISS. INDUCTION SEQUENCES and SERIES. J J O'Connor MT /10

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

Numerical Methods for Option Pricing

MA4001 Engineering Mathematics 1 Lecture 10 Limits and Continuity

Overview. Essential Questions. Precalculus, Quarter 4, Unit 4.5 Build Arithmetic and Geometric Sequences and Series

Wald s Identity. by Jeffery Hein. Dartmouth College, Math 100

Adaptive Online Gradient Descent

Stationary random graphs on Z with prescribed iid degrees and finite mean connections

Rolle s Theorem. q( x) = 1

Probability and Statistics Prof. Dr. Somesh Kumar Department of Mathematics Indian Institute of Technology, Kharagpur

Erdos and the Twin Prime Conjecture: Elementary Approaches to Characterizing the Differences of Primes

SOLUTIONS TO EXERCISES FOR. MATHEMATICS 205A Part 3. Spaces with special properties

Math 181 Handout 16. Rich Schwartz. March 9, 2010

NOTES ON LINEAR TRANSFORMATIONS

Representation of functions as power series

Solving Systems of Linear Equations

Systems of Linear Equations

Information Theory and Coding Prof. S. N. Merchant Department of Electrical Engineering Indian Institute of Technology, Bombay

Turing Degrees and Definability of the Jump. Theodore A. Slaman. University of California, Berkeley. CJuly, 2005

Handout #1: Mathematical Reasoning

Every Positive Integer is the Sum of Four Squares! (and other exciting problems)

Mathematical Induction

INDISTINGUISHABILITY OF ABSOLUTELY CONTINUOUS AND SINGULAR DISTRIBUTIONS

No: Bilkent University. Monotonic Extension. Farhad Husseinov. Discussion Papers. Department of Economics

6. Define log(z) so that π < I log(z) π. Discuss the identities e log(z) = z and log(e w ) = w.

Random variables, probability distributions, binomial random variable

IEOR 6711: Stochastic Models I Fall 2012, Professor Whitt, Tuesday, September 11 Normal Approximations and the Central Limit Theorem

NP-Completeness and Cook s Theorem

6.3 Conditional Probability and Independence

Markov random fields and Gibbs measures

Transcription:

Lecture 5 Infinite Series In today s lecture, we will restrict our attention to infinite series, which we will view as special kinds of sequences. We will bring what we learned about convergence of sequence to bear on infinite series. An infinite series is a formal sum of the form S = Here a n are some given real numbers. We would like to have a notion of convergence for series. Thus we consider the partial sums: S n = m=0 These are finite sums of numbers. We say that S converges if lim n S n converges. If we are given the partial sums S n, we may recover the terms of the series a n by a n = S n S n. In the first lecture, we viewed this identity as a form of the fundamental theorem. But, in any case, just as we may convert series to sequences, so we can convert a sequence to a series. We can write lim b n = n (b n b n ), where we fix b 0 to be zero. Every fact, we know about convergence of sequence translates into a fact about convergence of series. Theorem The series a n converges if and only if its tail n=m a n converges. (Here M is some particular natural number.) Proof This is basically just a reformulation of the Cauchy criterion for series. We let S j be the jth partial sum of the series a n and we let S M j = j n=m We note that the quantities Sj M then are the partial sums of the tail. Note that if j, k > M S M j S M k = S j S k.

We know from last time that the tail converges if and only if the Sj M s are a Cauchy sequence and the original series converges if and only if S j s are a Cauchy sequence, but restricting N from the definition of Cauchy sequence to be greater than M, we see that this is the same thing. Similarly, we can reformulate the Squeeze theorem as a criterion for convergence of series. Theorem Let {a n } and {b n } be two sequences of real numbers. Suppose that 0 a n b n for every natural number n. If b n converges then a n converges, and if diverges then b n diverges. a n Proof To get the second part, we apply Theorem 5 of lecture 4 to the partial sums. To get the first part, we observe that the limit of the partial sums is their least upper bound since they are an increasing sequence. Thus our assumption is that the partial sums of the b s have a least upper bound. In particular, since the a s are smaller, this implies that the partial sums of the a s are bounded above. Thus by the least upper bound property of the reals, they have a least upper bound. Definition A series a n is said to be absolutely convergent if a n converges. Theorem 3 If a n converges absolutely then it converges. Proof Since a n is absolutely convergent, it must be that the partial sums of a n which we denote T n = a j, j= are a convergent sequence and therefore a Cauchy sequence. Now denoting by S n, the nth partial sum of the series a n, we see that S n S m T n T m. Thus {S n } is also a Cauchy sequence and hence converges. A series a n need not be absolutely convergent in order to converge. If the series converges but is not absolutely convergent, we say that it is conditionally convergent. Example Consider ( )n n. This sum converges conditionally. To see this, we first observe that the sum does not converge absolutely. This is an application of

Example 4 in lecture 4. Next we combine the n st and nth term of the sum to obtain (n )n. The series ( )n n converges if and only if (n )(n) converges. We use Theorem to prove the convergence by comparison with Example of lecture 4. Example is just one example of a large class of alternating series that converges. Theorem 4 Let {a n } be a decreasing sequence of real numbers converging to 0. Then the series ( ) n a n converges. Proof It is enough to show that the series converges. Observe that But clearly since it telescopes. (a n a n ), a n a n a n a n+. a n a n+ = a, An important example of an absolutely convergent sequence is the geometric sequence. Example Let c and r < be positive real numbers. Then cr j = j=0 We can see this by calculating the partial sums, S n = j=0 c r. cr j = c( rn+ ). r 3

This formula for S n is most readily seen by induction. It clearly holds for n = 0 since the sum is just the 0th term. We observe that S n S n = c( rn r n+ r ) = cr n, which is the nth term. Since r <, we have that r n+ becomes arbitrarily small as n grows large. Thus S n converges to c r. We will use the geometric series (Example ) together with the squeeze theorem (Theorem ) to devise some useful tests for absolute convergence of series. Theorem 5 (The ratio test) Suppose a n 0 for any n sufficiently large. and suppose that lim n+ = L. n a n If L < then the series a n, converges absolutely. If L > then the series diverges. If the limit of the ratios does not exist or is equal to, then the ratio test fails, and we can reach no conclusion from Theorem 5 about the convergence of the series. Proof of the ratio test. Suppose that 0 L <. Choosing ɛ < L, we see that there is N so that for n N, we have From this, we see by induction that a n+ a n ɛ. a n a N ( ɛ) n N, for each n N. Now, we apply theorem to see that it suffices to show that the tail of the series a n, converges absolutely. To see this, we apply theorem, comparing it with the geometric series a N ( ɛ) n N, which by example converges absolutely. If on the other hand, L >, we may use the same idea to find N and ɛ so that a N 0 and so that for n > N, we have a n a N ( + ɛ) n N. 4

For such n, it is clear that the differences between consecutive partial sums S n+ S n = a n are growing. Hence the sequence of partial sums is not a Cauchy sequence. Theorem 6 (The nth root test) Suppose lim a n n = L. n Then if L <, the series n=0 a n converges absolutely. If L > then the series diverges. Proof of the nth root test. We proceed just as for Theorem 5. We suppose L < and pick ɛ < L. Then we conclude that there exists N so that for n N we have a n ( ɛ) n. Thus, we may apply Theorem to compare the tail of the series to the tail of the geometric series ( ɛ) n. On the other hand, if L >, we see that terms of the series are growing in absolute value and again we see that the partial sums are not a Cauchy sequence. The ratio and nth root tests can be used to show that series converge if they do so faster than geometric series. We provide an example. Example 3 The series n n, converges. We apply the ratio test and calculating (n + ) n (n + ) lim n n n = lim n n =. One of the reasons that the nth root test is important is that we can use it to understand the convergence properties of power series. This will be the topic of our next lecture. 5