Arithmetic and Geometric Progressions
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Methods of Measuring Population Change
Methods of Measuring Population Change CDC 103 – Lecture 10 – April 22, 2012 Measuring Population Change • If past trends in population growth can be expressed in a mathematical model, there would be a solid justification for making projections on the basis of that model. • Demographers developed an array of models to measure population growth; four of these models are usually utilized. 1 Measuring Population Change Arithmetic (Linear), Geometric, Exponential, and Logistic. Arithmetic Change • A population growing arithmetically would increase by a constant number of people in each period. • If a population of 5000 grows by 100 annually, its size over successive years will be: 5100, 5200, 5300, . • Hence, the growth rate can be calculated by the following formula: • (100/5000 = 0.02 or 2 per cent). 2 Arithmetic Change • Arithmetic growth is the same as the ‘simple interest’, whereby interest is paid only on the initial sum deposited, the principal, rather than on accumulating savings. • Five percent simple interest on $100 merely returns a constant $5 interest every year. • Hence, arithmetic change produces a linear trend in population growth – following a straight line rather than a curve. Arithmetic Change 3 Arithmetic Change • The arithmetic growth rate is expressed by the following equation: Geometric Change • Geometric population growth is the same as the growth of a bank balance receiving compound interest. • According to this, the interest is calculated each year with reference to the principal plus previous interest payments, thereby yielding a far greater return over time than simple interest. • The geometric growth rate in demography is calculated using the ‘compound interest formula’. -
Formal Power Series - Wikipedia, the Free Encyclopedia
Formal power series - Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Formal_power_series Formal power series From Wikipedia, the free encyclopedia In mathematics, formal power series are a generalization of polynomials as formal objects, where the number of terms is allowed to be infinite; this implies giving up the possibility to substitute arbitrary values for indeterminates. This perspective contrasts with that of power series, whose variables designate numerical values, and which series therefore only have a definite value if convergence can be established. Formal power series are often used merely to represent the whole collection of their coefficients. In combinatorics, they provide representations of numerical sequences and of multisets, and for instance allow giving concise expressions for recursively defined sequences regardless of whether the recursion can be explicitly solved; this is known as the method of generating functions. Contents 1 Introduction 2 The ring of formal power series 2.1 Definition of the formal power series ring 2.1.1 Ring structure 2.1.2 Topological structure 2.1.3 Alternative topologies 2.2 Universal property 3 Operations on formal power series 3.1 Multiplying series 3.2 Power series raised to powers 3.3 Inverting series 3.4 Dividing series 3.5 Extracting coefficients 3.6 Composition of series 3.6.1 Example 3.7 Composition inverse 3.8 Formal differentiation of series 4 Properties 4.1 Algebraic properties of the formal power series ring 4.2 Topological properties of the formal power series -
Sequence Rules
SEQUENCE RULES A connected series of five of the same colored chip either up or THE JACKS down, across or diagonally on the playing surface. There are 8 Jacks in the card deck. The 4 Jacks with TWO EYES are wild. To play a two-eyed Jack, place it on your discard pile and place NOTE: There are printed chips in the four corners of the game board. one of your marker chips on any open space on the game board. The All players must use them as though their color marker chip is in 4 jacks with ONE EYE are anti-wild. To play a one-eyed Jack, place the corner. When using a corner, only four of your marker chips are it on your discard pile and remove one marker chip from the game needed to complete a Sequence. More than one player may use the board belonging to your opponent. That completes your turn. You same corner as part of a Sequence. cannot place one of your marker chips on that same space during this turn. You cannot remove a marker chip that is already part of a OBJECT OF THE GAME: completed SEQUENCE. Once a SEQUENCE is achieved by a player For 2 players or 2 teams: One player or team must score TWO SE- or a team, it cannot be broken. You may play either one of the Jacks QUENCES before their opponents. whenever they work best for your strategy, during your turn. For 3 players or 3 teams: One player or team must score ONE SE- DEAD CARD QUENCE before their opponents. -
Math Club: Recurrent Sequences Nov 15, 2020
MATH CLUB: RECURRENT SEQUENCES NOV 15, 2020 In many problems, a sequence is defined using a recurrence relation, i.e. the next term is defined using the previous terms. By far the most famous of these is the Fibonacci sequence: (1) F0 = 0;F1 = F2 = 1;Fn+1 = Fn + Fn−1 The first several terms of this sequence are below: 0; 1; 1; 2; 3; 5; 8; 13; 21; 34;::: For such sequences there is a method of finding a general formula for nth term, outlined in problem 6 below. 1. Into how many regions do n lines divide the plane? It is assumed that no two lines are parallel, and no three lines intersect at a point. Hint: denote this number by Rn and try to get a recurrent formula for Rn: what is the relation betwen Rn and Rn−1? 2. The following problem is due to Leonardo of Pisa, later known as Fibonacci; it was introduced in his 1202 book Liber Abaci. Suppose a newly-born pair of rabbits, one male, one female, are put in a field. Rabbits are able to mate at the age of one month so that at the end of its second month a female can produce another pair of rabbits. Suppose that our rabbits never die and that the female always produces one new pair (one male, one female) every month from the second month on. How many pairs will there be in one year? 3. Daniel is coming up the staircase of 20 steps. He can either go one step at a time, or skip a step, moving two steps at a time. -
0.999… = 1 an Infinitesimal Explanation Bryan Dawson
0 1 2 0.9999999999999999 0.999… = 1 An Infinitesimal Explanation Bryan Dawson know the proofs, but I still don’t What exactly does that mean? Just as real num- believe it.” Those words were uttered bers have decimal expansions, with one digit for each to me by a very good undergraduate integer power of 10, so do hyperreal numbers. But the mathematics major regarding hyperreals contain “infinite integers,” so there are digits This fact is possibly the most-argued- representing not just (the 237th digit past “Iabout result of arithmetic, one that can evoke great the decimal point) and (the 12,598th digit), passion. But why? but also (the Yth digit past the decimal point), According to Robert Ely [2] (see also Tall and where is a negative infinite hyperreal integer. Vinner [4]), the answer for some students lies in their We have four 0s followed by a 1 in intuition about the infinitely small: While they may the fifth decimal place, and also where understand that the difference between and 1 is represents zeros, followed by a 1 in the Yth less than any positive real number, they still perceive a decimal place. (Since we’ll see later that not all infinite nonzero but infinitely small difference—an infinitesimal hyperreal integers are equal, a more precise, but also difference—between the two. And it’s not just uglier, notation would be students; most professional mathematicians have not or formally studied infinitesimals and their larger setting, the hyperreal numbers, and as a result sometimes Confused? Perhaps a little background information wonder . -
On Generalized Hypergeometric Equations and Mirror Maps
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 142, Number 9, September 2014, Pages 3153–3167 S 0002-9939(2014)12161-7 Article electronically published on May 28, 2014 ON GENERALIZED HYPERGEOMETRIC EQUATIONS AND MIRROR MAPS JULIEN ROQUES (Communicated by Matthew A. Papanikolas) Abstract. This paper deals with generalized hypergeometric differential equations of order n ≥ 3 having maximal unipotent monodromy at 0. We show that among these equations those leading to mirror maps with inte- gral Taylor coefficients at 0 (up to simple rescaling) have special parameters, namely R-partitioned parameters. This result yields the classification of all generalized hypergeometric differential equations of order n ≥ 3havingmax- imal unipotent monodromy at 0 such that the associated mirror map has the above integrality property. 1. Introduction n Let α =(α1,...,αn) be an element of (Q∩]0, 1[) for some integer n ≥ 3. We consider the generalized hypergeometric differential operator given by n n Lα = δ − z (δ + αk), k=1 d where δ = z dz . It has maximal unipotent monodromy at 0. Frobenius’ method yields a basis of solutions yα;1(z),...,yα;n(z)ofLαy(z) = 0 such that × (1) yα;1(z) ∈ C({z}) , × (2) yα;2(z) ∈ C({z})+C({z}) log(z), . n−2 k × n−1 (3) yα;n(z) ∈ C({z})log(z) + C({z}) log(z) , k=0 where C({z}) denotes the field of germs of meromorphic functions at 0 ∈ C.One can assume that yα;1 is the generalized hypergeometric series ∞ + (α) y (z):=F (z):= k zk ∈ C({z}), α;1 α k!n k=0 where the Pochhammer symbols (α)k := (α1)k ···(αn)k are defined by (αi)0 =1 ∗ and, for k ∈ N ,(αi)k = αi(αi +1)···(αi + k − 1). -
Integral Points in Arithmetic Progression on Y2=X(X2&N2)
Journal of Number Theory 80, 187208 (2000) Article ID jnth.1999.2430, available online at http:ÂÂwww.idealibrary.com on Integral Points in Arithmetic Progression on y2=x(x2&n2) A. Bremner Department of Mathematics, Arizona State University, Tempe, Arizona 85287 E-mail: bremnerÄasu.edu J. H. Silverman Department of Mathematics, Brown University, Providence, Rhode Island 02912 E-mail: jhsÄmath.brown.edu and N. Tzanakis Department of Mathematics, University of Crete, Iraklion, Greece E-mail: tzanakisÄitia.cc.uch.gr Communicated by A. Granville Received July 27, 1998 1. INTRODUCTION Let n1 be an integer, and let E be the elliptic curve E: y2=x(x2&n2). (1) In this paper we consider the problem of finding three integral points P1 , P2 , P3 whose x-coordinates xi=x(Pi) form an arithmetic progression with x1<x2<x3 . Let T1=(&n,0), T2=(0, 0), and T3=(n, 0) denote the two-torsion points of E. As is well known [Si1, Proposition X.6.1(a)], the full torsion subgroup of E(Q)isE(Q)tors=[O, T1 , T2 , T3]. One obvious solution to our problem is (P1 , P2 , P3)=(T1 , T2 , T3). It is natural to ask whether there are further obvious solutions, say of the form (T1 , Q, T2)or(T2 , T3 , Q$) or (T1 , T3 , Q"). (2) 187 0022-314XÂ00 35.00 Copyright 2000 by Academic Press All rights of reproduction in any form reserved. 188 BREMNER, SILVERMAN, AND TZANAKIS This is equivalent to asking whether there exist integral points having x-coordinates equal to &nÂ2or2n or 3n, respectively. -
Sequences, Series and Taylor Approximation (Ma2712b, MA2730)
Sequences, Series and Taylor Approximation (MA2712b, MA2730) Level 2 Teaching Team Current curator: Simon Shaw November 20, 2015 Contents 0 Introduction, Overview 6 1 Taylor Polynomials 10 1.1 Lecture 1: Taylor Polynomials, Definition . .. 10 1.1.1 Reminder from Level 1 about Differentiable Functions . .. 11 1.1.2 Definition of Taylor Polynomials . 11 1.2 Lectures 2 and 3: Taylor Polynomials, Examples . ... 13 x 1.2.1 Example: Compute and plot Tnf for f(x) = e ............ 13 1.2.2 Example: Find the Maclaurin polynomials of f(x) = sin x ...... 14 2 1.2.3 Find the Maclaurin polynomial T11f for f(x) = sin(x ) ....... 15 1.2.4 QuestionsforChapter6: ErrorEstimates . 15 1.3 Lecture 4 and 5: Calculus of Taylor Polynomials . .. 17 1.3.1 GeneralResults............................... 17 1.4 Lecture 6: Various Applications of Taylor Polynomials . ... 22 1.4.1 RelativeExtrema .............................. 22 1.4.2 Limits .................................... 24 1.4.3 How to Calculate Complicated Taylor Polynomials? . 26 1.5 ExerciseSheet1................................... 29 1.5.1 ExerciseSheet1a .............................. 29 1.5.2 FeedbackforSheet1a ........................... 33 2 Real Sequences 40 2.1 Lecture 7: Definitions, Limit of a Sequence . ... 40 2.1.1 DefinitionofaSequence .......................... 40 2.1.2 LimitofaSequence............................. 41 2.1.3 Graphic Representations of Sequences . .. 43 2.2 Lecture 8: Algebra of Limits, Special Sequences . ..... 44 2.2.1 InfiniteLimits................................ 44 1 2.2.2 AlgebraofLimits.............................. 44 2.2.3 Some Standard Convergent Sequences . .. 46 2.3 Lecture 9: Bounded and Monotone Sequences . ..... 48 2.3.1 BoundedSequences............................. 48 2.3.2 Convergent Sequences and Closed Bounded Intervals . .... 48 2.4 Lecture10:MonotoneSequences . -
3 Formal Power Series
MT5821 Advanced Combinatorics 3 Formal power series Generating functions are the most powerful tool available to combinatorial enu- merators. This week we are going to look at some of the things they can do. 3.1 Commutative rings with identity In studying formal power series, we need to specify what kind of coefficients we should allow. We will see that we need to be able to add, subtract and multiply coefficients; we need to have zero and one among our coefficients. Usually the integers, or the rational numbers, will work fine. But there are advantages to a more general approach. A favourite object of some group theorists, the so-called Nottingham group, is defined by power series over a finite field. A commutative ring with identity is an algebraic structure in which addition, subtraction, and multiplication are possible, and there are elements called 0 and 1, with the following familiar properties: • addition and multiplication are commutative and associative; • the distributive law holds, so we can expand brackets; • adding 0, or multiplying by 1, don’t change anything; • subtraction is the inverse of addition; • 0 6= 1. Examples incude the integers Z (this is in many ways the prototype); any field (for example, the rationals Q, real numbers R, complex numbers C, or integers modulo a prime p, Fp. Let R be a commutative ring with identity. An element u 2 R is a unit if there exists v 2 R such that uv = 1. The units form an abelian group under the operation of multiplication. Note that 0 is not a unit (why?). -
Formal Power Series License: CC BY-NC-SA
Formal Power Series License: CC BY-NC-SA Emma Franz April 28, 2015 1 Introduction The set S[[x]] of formal power series in x over a set S is the set of functions from the nonnegative integers to S. However, the way that we represent elements of S[[x]] will be as an infinite series, and operations in S[[x]] will be closely linked to the addition and multiplication of finite-degree polynomials. This paper will introduce a bit of the structure of sets of formal power series and then transfer over to a discussion of generating functions in combinatorics. The most familiar conceptualization of formal power series will come from taking coefficients of a power series from some sequence. Let fang = a0; a1; a2;::: be a sequence of numbers. Then 2 the formal power series associated with fang is the series A(s) = a0 + a1s + a2s + :::, where s is a formal variable. That is, we are not treating A as a function that can be evaluated for some s0. In general, A(s0) is not defined, but we will define A(0) to be a0. 2 Algebraic Structure Let R be a ring. We define R[[s]] to be the set of formal power series in s over R. Then R[[s]] is itself a ring, with the definitions of multiplication and addition following closely from how we define these operations for polynomials. 2 2 Let A(s) = a0 + a1s + a2s + ::: and B(s) = b0 + b1s + b1s + ::: be elements of R[[s]]. Then 2 the sum A(s) + B(s) is defined to be C(s) = c0 + c1s + c2s + :::, where ci = ai + bi for all i ≥ 0. -
Section 6-3 Arithmetic and Geometric Sequences
466 6 SEQUENCES, SERIES, AND PROBABILITY Section 6-3 Arithmetic and Geometric Sequences Arithmetic and Geometric Sequences nth-Term Formulas Sum Formulas for Finite Arithmetic Series Sum Formulas for Finite Geometric Series Sum Formula for Infinite Geometric Series For most sequences it is difficult to sum an arbitrary number of terms of the sequence without adding term by term. But particular types of sequences, arith- metic sequences and geometric sequences, have certain properties that lead to con- venient and useful formulas for the sums of the corresponding arithmetic series and geometric series. Arithmetic and Geometric Sequences The sequence 5, 7, 9, 11, 13,..., 5 ϩ 2(n Ϫ 1),..., where each term after the first is obtained by adding 2 to the preceding term, is an example of an arithmetic sequence. The sequence 5, 10, 20, 40, 80,..., 5 (2)nϪ1,..., where each term after the first is obtained by multiplying the preceding term by 2, is an example of a geometric sequence. ARITHMETIC SEQUENCE DEFINITION A sequence a , a , a ,..., a ,... 1 1 2 3 n is called an arithmetic sequence, or arithmetic progression, if there exists a constant d, called the common difference, such that Ϫ ϭ an anϪ1 d That is, ϭ ϩ Ͼ an anϪ1 d for every n 1 GEOMETRIC SEQUENCE DEFINITION A sequence a , a , a ,..., a ,... 2 1 2 3 n is called a geometric sequence, or geometric progression, if there exists a nonzero constant r, called the common ratio, such that 6-3 Arithmetic and Geometric Sequences 467 a n ϭ r DEFINITION anϪ1 2 That is, continued ϭ Ͼ an ranϪ1 for every n 1 Explore/Discuss (A) Graph the arithmetic sequence 5, 7, 9, ... -
A Mathematical Example: Factorial Example: Fibonnaci Sequence Fibonacci As a Recursive Function Fibonacci: # of Frames Vs. # Of
10/14/15 A Mathematical Example: Factorial Example: Fibonnaci Sequence • Non-recursive definition: • Sequence of numbers: 1, 1, 2, 3, 5, 8, 13, ... a0 a1 a2 a3 a4 a5 a6 n! = n × n-1 × … × 2 × 1 § Get the next number by adding previous two = n (n-1 × … × 2 × 1) § What is a8? • Recursive definition: • Recursive definition: § a = a + a Recursive Case n! = n (n-1)! for n ≥ 0 Recursive case n n-1 n-2 § a0 = 1 Base Case 0! = 1 Base case § a1 = 1 (another) Base Case What happens if there is no base case? Why did we need two base cases this time? Fibonacci as a Recursive Function Fibonacci: # of Frames vs. # of Calls def fibonacci(n): • Function that calls itself • Fibonacci is very inefficient. """Returns: Fibonacci no. an § Each call is new frame § fib(n) has a stack that is always ≤ n Precondition: n ≥ 0 an int""" § Frames require memory § But fib(n) makes a lot of redundant calls if n <= 1: § ∞ calls = ∞ memo ry return 1 fib(5) fibonacci 3 Path to end = fib(4) fib(3) return (fibonacci(n-1)+ n 5 the call stack fibonacci(n-2)) fib(3) fib(2) fib(2) fib(1) fibonacci 1 fibonacci 1 fib(2) fib(1) fib(1) fib(0) fib(1) fib(0) n 4 n 3 fib(1) fib(0) How to Think About Recursive Functions Understanding the String Example 1. Have a precise function specification. def num_es(s): • Break problem into parts """Returns: # of 'e's in s""" 2. Base case(s): # s is empty number of e’s in s = § When the parameter values are as small as possible if s == '': Base case number of e’s in s[0] § When the answer is determined with little calculation.