Tom Copeland, Nov. 16, e trx 1 = A(t) x t = e tψ.(x) = n 0 n!

Size: px
Start display at page:

Download "Tom Copeland, Nov. 16, e trx 1 = A(t) x t = e tψ.(x) = n 0 n!"

Transcription

1 The Creation / Raising Operators for Appell Sequences Tom Copelan, tcjpn@msn.com Nov. 6, 5 Part I Raising ops for logarithmic Appell sequences Dene the raising op for the logarithmic Appell sequence R x by e trx = At x t = e tψ.x = n ψ n x tn with A =. Then, with n t n t= At = D n t=at = a n, i.e., At = e a.t, D n t= e trx = R n x = ψ n x = lnx + a. n = = lnx n a, an clearly R x ψ n x = ψ n+ x. Acting on the top equation with the shift op e sdt ft = fs + t gives e sdt e trx = e s+trx = e sdt At x t = As + t x s+t = e s+tψ.x. implying the evolution equation evaluate D s at s = D t Atx t = R x e trx = R x Atx t an so e srx e trx = e srx At x t = As + t x s+t, e trx x s t As + t = x x s = x t AxD x + t As AxD x x s.

2 This can be rewritten in terms of the reciprocal Âs= As as a generalize fractional integro-erivative, or shift, operator acting on a particular basis : e trx Extracting the ops gives xs e trx = x t AxD x + t AxD x A,x Âs = D t x s Âs = xs+t Âs + t. = x t Aφ.: xd x : +t Aφ.: xd x : = x t e c.:xdx: = D t A,x = xt ÂxD x ÂxD x + t = xt Âφ: xd x : Âφ: xd x : + t = xt e ĉ.:xdx: with c n = An+t An, ĉ = Ân, φx equal to the Bell / Touchar / exponential Ân+t polynomials Stirling polynomials of the secon in, OEIS A877, an by enition : xd x : n = x n Dx. n The nite ierence expressions incorporating b. n = follow from the umbral relations AxD x + t AxD x fx = n An + t An b = n b = f n x n = e c.:xdx: fx = f[x c.x] = fc.x. Careful! From the binomial expansion b. = b, which nee not be equal in general to unity; however, it is unity for Appell sequences. Evaluating the erivative w.r.t. t at the origin of the exponentiate raising op gives xd R x = lnx + A x AxD x = lnx + xd x ln[axd x]. The associate lowering operator is ene as Lψ n x = n ψ n x = n lnx + a. n = xd x lnx + a. n = xd x ψ n x, so the commutator for the operators acting on any ψ n x is [L x, R x ] = L x R x R x L x = Ientity. An, from the properties of the Pincherle erivative, Note also that lnx + [ln AL x, R x ] = lnx + e trx e srx = e Rx L x ln AL x = R x.

3 implies x t At + xd x x s As + xd x = x At + s + xd x AxD x AxD x AxD x = x s As + xd x x t At + xd x AxD x AxD x an the same relations for the operator x t ÂxD x At + xd x = x t At+xD x AxD. x For example, with Ax = x!, this implies x t t + xdx t x s s + xdx s t + s + = x xdx. t + s Part II Recursion relations an integral reps for the raising op The raising op can be expresse several ways as in the entry Bernoulli Appells here. The most convenient for binomial relations is, with a change variables to lnx = z, R z = z + D z ln [MD z ] = z + D z ln [ e m.dz] = z + D z e c.dz = z + c. e c.dz with c n regare as the formal cumulants an m n as the formal moments of OEIS A767 ene by with M =. Then e c.t = ln [ e m.t] = ln[mt] R n z = z + m. n = p n z, an a recursion relation follows from the Appell binomial property p n z + h = z +m.+h n = p.z+h n as in the Appell Polynomials, Cumulants,... entry : R z p n z = p n+ z = z + c. e c.dz p n z = z p n z + c. p n c. + z = z p n z + c. c. + p.z n = z p n z + = z + c p n z + = = n c + p n z. These polynomials are precisely the general Bell polynomials c n+ p z p n z = B n z + c, c,..., c n = B n p z, c,..., c n = B n x[],..., x[n], 3

4 or partition polynomials for the rene Stirling numbers of the secon in, of OEIS A364, which are an Appell sequence in the istinguishe ineterminate c, i.e., c B n c,..., c n = n B n c,..., c n. They can also be expresse as the cycle inex polynomials of the symmetric groups, or the partition polynomials for the rene Stirling numbers of the rst in, p n z = CIP n z + b, b,.., b n = CIP n p z, b,.., b n = CIP n x[],..., x[n], of A3639 with x[] = b = p z = z + c an x[n] = b n = c n /n! for b. n > with raising op R = = b + b n+ Db n b.d, which are an Appell b n sequence in the istinguishe ineterminate b, i.e., b CIP n b,..., b n = n CIP n b,..., b n. The recursion relation leas to an integral representation for the raising op. Compare p n z p.z ω n = p n z p n z ω = + ω p n z = with the recursion relation. If we can n a istribution µω such that its moments are the cumulants c + for >, we have our integral rep ˆ ˆ c + = + ω µω ω = α e ωα µω ω α=, or = ˆ c. e c.α = e ωα µω ω. If this is essentially a Laplace transform, then the inverse Lapace transform in an appropriate region of evaluation gives µω. Uner suitable conitions, the coecients can be regare as iscrete samples c + = +! C + of a Mellin transform of the istribution: Cs = ˆ µω ω s s! ω. The istribution may nee to be moie the integral regularize over strips of s to obtain an invariant Cs over the Mellin ual space, just as for Cs =. 4

5 Since p n z p.z ω n = p n z p n z ω, the recursion relation can be expresse as R z p n z = p n+ z = z + c p n z + = z + c p n z + ˆ l Or, with the change of variables ω = z t, Now let then R z p n z = p n+ z = z + c p n z + l = c + p n z. [p n z p n z ω] µω ω. ˆ z l z l [p n z p n t] µz t t. z = lnx, t = lnv, an p n z = p n lnx = ψ n x, R x ψ n x = ψ n+ x = lnx + c ψ n x + So, for functions analytic about the origin, e l x e l [ψ n x ψ n v] µ[lnx/v] v v. an R z fz = z + c fz + ˆ z l z l [fz ft] µz t t, e l R x gx = lnx + c gx + [gx gt] µ[lnx/t] t t. x e l EXAMPLES: As gleane from the Riemann zeta Appell sequence of the MathOverow question Riemann zeta function at positive integers an an Appell sequence of polynomials relate to fractional calculus an the entry here On the Mellin interpolation of ierential ops an associate innigens an Appell polynomials..., the istributions for the Riemann zeta Appell sequences are signe an unsigne µω = e ω, an the cumulants within an overall sign for n > are ˆ c n = n n! ζn = n ω n e ω ω 5

6 with c. e c.α = n n+ ζn + α n = Ψ + α + γ = α ec.α c = α ln [em.α ] c = α ln[α!] + γ for α <, where Ψ is the igamma, or Psi, function with c = α lnα! α= = γ = Ψ = , the negate Euler-Mascheroni constant. Also, l =, l =, an ˆ z R z fz = z γ fz + [fz ft] e z t t, an R x gx = lnx γ gx + = lnx gx + πi = lnx gx + π ˆ π π z x =x = lnx γ gx π gx gt x t lnz x γ z x t gz z iθ lnx γ gx + e iϑ θ. ˆ π π iθ gx + e iϑ θ. Specically, for this choice of overall sign for the cumulants, we have obtaine the raising operator or innigen associate to the shifte Laguerre operator xd x x, iscusse in the earlier entry: R x x s = lnx γ x s x s t s ˆ + t = R x x s = [lnx γ+ x t = [lnx + Ψ s] x s = [lnx + Ψ + xd x ] x s = lnxd x x x s = [ lnx + lnd x ] x s. Then acting on functions analytic at the origin, R x = lnx + Ψ + xd x = lnx γ + n ˆ = lnx γ + = lnx γ + n n + n + + xd x t xdx t t H n x n D n x= t s t t] x s 6

7 = lnx γ + n H. n xn Dx n n = lnx γ + n x n Dx n n n = lnx γ + n xdx n n n = lnx γ + b. xdx, where b = H = note that b. = b =, in this case, an b n = /n otherwise an the harmonic numbers H n are ene for n > by so H n = = b. n = = = ˆ = n b = u n u = γ + Ψn + u n n =, R x fx = [lnx γ + b. xdx ] fx = lnx γ fx + f [ b. x] = lnx γ fx + n H n f n xn = lnx γ fx + fx ft x t The operator can also be expresse in terms of the entire function exponential integral ˆ z e t Einz = t = n z n t n, n with : xd x : n = x n D n x by enition, as R x = lnx γ + Ein: xd x :. t. For the Bernoulli polynomials iscusse in the Bernoulli Appells entry, the raisng op for the logarithmic Appell sequence is R x = lnx + n B n+ n + n xd x n = lnx + n ζn π n xd x n n = lnx + xd x e xdx 7

8 = lnx = lnx + xd x coth xdx + i xd x Ψ π = lnx + i [ Ψ π i xd x π = lnx + πin xd x πin + xd x n [ˆ ] = lnx + i ω i xdx xdx π i ω π ω π ω = lnx ˆ ωxdx sin π π e ω ω = lnx ˆ lnu xdx sin π π u u [ sinh xd x xd x ln ] [ xd x e xdx = lnx + xd x ln [ = lnx sini xd x xd x ln e xdx i xdx = lnx + {ˆ π π Im { = lnx + π Im πi We then obtain, for t about the origin, e trx x s = = x t e t As + t As x s+t = s + t s ] sinh xdx xdx x sinh s = x t e t xdx+t xdx+t i t+xd x = x t t e t = x t e t π i t π x π i xd x ] = lnx+ [ xd x ln i xd x } iθ + γ + e iθ i xdx π θ π z = lnz + γ z e s e s+t xs+t = e t[lnx + i i t sin i t x s = x t e t : Dx x : i t π i t+xd x π i t π z i xdx π z }. π [Ψ+ i xdx π xd x e xdx ]! i xd x i t+xd x π i t x s π i t+xd x π! i s! π x s x i π xd x x s. ]! e xdx Ψ i xdx π ]] x s In the last equality, the last factor from the left in the moulus transforms x s to x i s π an the rst factor reverses the transformation as x q xd x x s = x s x q s = x qs = n x q n : xd x : n x s. 8 n

9 Recall that by enition : AB : n = A n B n so that : xd x : n = x n D n an : D x x : n = Dxx n n. The mile factor is a generalize Laguerre operator giving : D x x : i t n x i s i π = D t π x x i t π x i s π = i t + s! D i t x i π π i x π! π i = π! i s x i s π π! with one convolution rep of the fractional integro-erivative being the Haamar nite part of D i t π x x i π ˆ = x i s π = x u i t π i t π u i u i t π π u =! i t π! u i t π i t π ui π u = x i s π! = i t! π i π i t π i t! π n x i s π, i π n x ui π u sinπn i t π πn i t π with the summation vali for Real i π >. Other reps are given in other notes at this site an are reecte in the integral reps above. The last expression of the exponentiate raising op may also be expane out an the mile two factors reuce as e trx x s = x t e t x π i xd x : Dx x : i t π x xd x : Dx x : i t π x i π xd x. Part III Convolution rep for D t A,x = exptr x from the Mellin transform Acting on a function representable as an inverse Mellin transform, e trx fx = πi ˆ σ+i σ i f M se trx x s s = πi ˆ σ+i σ i f M s x t AxD x + t x s s AxD x with = ˆ σ+i f M s πi σ i A s + t x s+t s A s ˆ = x t σ+i f M s πi K M s; t x s s σ i K M s; t = As + t As = Âs Âs + t. 9

10 Then from the Mellin convolution theorem, ˆ ˆ e trx fx = x t Ku; t fxuu = x t x Ku ; t fuu x = x t n An + t x n f n An = xt e c.:xdx=: fx = x t e c.:xdx: fx where Kx; t is the inverse Mellin transform of KM s; t an f n = D n x= fx. For example, let As = /s!, corresponing to the innigen R x = lnx Ψ + xd x = lnd x for the fractional integro-erivatives Dx t. Then for σ > an t non-integral, Kx; t = ˆ σ+i K M s; t x s s = ˆ σ+i s! πi σ i πi σ i s + t! x s s = ˆ σ+i πi σ i π sinπs s + t! x s s! s = H x n t n! xn = H x n where Hx is the Heavisie step function, so xα βrx e α! = x α D β A,x α! = xα+β α + β! ˆ = x β x Ku uα ; β u = xβ x α! = x u β β! ˆ u x β x β! u α α! u. xt t! u α α! u As another illustration note that if Ax =, then K M s; t =, an the inverse Mellin transform gives Kx; t = δ x; therefore, D t A,x = xt, consistent with R x = lnx an e trx = x t.,

NOTES ON EULER-BOOLE SUMMATION (1) f (l 1) (n) f (l 1) (m) + ( 1)k 1 k! B k (y) f (k) (y) dy,

NOTES ON EULER-BOOLE SUMMATION (1) f (l 1) (n) f (l 1) (m) + ( 1)k 1 k! B k (y) f (k) (y) dy, NOTES ON EULER-BOOLE SUMMATION JONATHAN M BORWEIN, NEIL J CALKIN, AND DANTE MANNA Abstract We stuy a connection between Euler-MacLaurin Summation an Boole Summation suggeste in an AMM note from 196, which

More information

Final Exam Study Guide and Practice Problems Solutions

Final Exam Study Guide and Practice Problems Solutions Final Exam Stuy Guie an Practice Problems Solutions Note: These problems are just some of the types of problems that might appear on the exam. However, to fully prepare for the exam, in aition to making

More information

Bernoulli Polynomials

Bernoulli Polynomials Chapter 4 Bernoulli Polynomials 4. Bernoulli Numbers The generating function for the Bernoulli numbers is x e x = n= B n n! xn. (4.) That is, we are to expand the left-hand side of this equation in powers

More information

Math 251 Notes. Part I.

Math 251 Notes. Part I. Math 251 Notes. Part I. F. Patricia Meina May 6, 2013 Growth Moel.Consumer price inex. [Problem 20, page 172] The U.S. consumer price inex (CPI) measures the cost of living base on a value of 100 in the

More information

Dr. Abdulla Eid. Section 3.8 Derivative of the inverse function and logarithms 3 Lecture. Dr. Abdulla Eid. MATHS 101: Calculus I. College of Science

Dr. Abdulla Eid. Section 3.8 Derivative of the inverse function and logarithms 3 Lecture. Dr. Abdulla Eid. MATHS 101: Calculus I. College of Science Section 3.8 Derivative of the inverse function and logarithms 3 Lecture College of Science MATHS 101: Calculus I (University of Bahrain) Logarithmic Differentiation 1 / 19 Topics 1 Inverse Functions (1

More information

Differentiation Rules Derivatives of Polynomials and Exponential Functions

Differentiation Rules Derivatives of Polynomials and Exponential Functions Derivatives of Polynomials an Exponential Functions Differentiation Rules Derivatives of Polynomials an Exponential Functions Let s start with the simplest of all functions, the constant function f(x)

More information

Lagrange à la Lah. Tom Copeland Tsukuba, Japan April 11, 2011

Lagrange à la Lah. Tom Copeland Tsukuba, Japan April 11, 2011 Lagrange à la Lah Lagrange Lanscapes Part II: Umbral Operator Trees for Partition Polynomials Tom Copelan Tsukuba, Japan tcjpn@msn.com April 11, 2011 Abstract Partition polynomials associate through umbral

More information

Lecture 32: Taylor Series and McLaurin series We saw last day that some functions are equal to a power series on part of their domain.

Lecture 32: Taylor Series and McLaurin series We saw last day that some functions are equal to a power series on part of their domain. Lecture 32: Taylor Series and McLaurin series We saw last day that some functions are equal to a power series on part of their domain. For example f(x) = 1 1 x = 1 + x + x2 + x 3 + = ln(1 + x) = x x2 2

More information

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x)

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x) Y. D. Chong (2016) MH2801: Complex Methos for the Sciences 1. Derivatives The erivative of a function f(x) is another function, efine in terms of a limiting expression: f (x) f (x) lim x δx 0 f(x + δx)

More information

A Symbolic Operator Approach to Power Series Transformation-Expansion Formulas

A Symbolic Operator Approach to Power Series Transformation-Expansion Formulas A Symbolic Operator Approach to Power Series Transformation-Expansion Formulas Tian- Xiao He Department of Mathematics and Computer Science Illinois Wesleyan University Bloomington, IL 61702-2900, USA

More information

Some Fun with Divergent Series

Some Fun with Divergent Series Some Fun with Divergent Series 1. Preliminary Results We begin by examining the (divergent) infinite series S 1 = 1 + 2 + 3 + 4 + 5 + 6 + = k=1 k S 2 = 1 2 + 2 2 + 3 2 + 4 2 + 5 2 + 6 2 + = k=1 k 2 (i)

More information

Linearization coefficients for orthogonal polynomials. Michael Anshelevich

Linearization coefficients for orthogonal polynomials. Michael Anshelevich Linearization coefficients for orthogonal polynomials Michael Anshelevich February 26, 2003 P n = monic polynomials of degree n = 0, 1,.... {P n } = basis for the polynomials in 1 variable. Linearization

More information

C. Complex Numbers. 1. Complex arithmetic.

C. Complex Numbers. 1. Complex arithmetic. C. Complex Numbers. Complex arithmetic. Most people think that complex numbers arose from attempts to solve quadratic equations, but actually it was in connection with cubic equations they first appeared.

More information

Some functions and their derivatives

Some functions and their derivatives Chapter Some functions an their erivatives. Derivative of x n for integer n Recall, from eqn (.6), for y = f (x), Also recall that, for integer n, Hence, if y = x n then y x = lim δx 0 (a + b) n = a n

More information

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson JUST THE MATHS UNIT NUMBER 10.2 DIFFERENTIATION 2 (Rates of change) by A.J.Hobson 10.2.1 Introuction 10.2.2 Average rates of change 10.2.3 Instantaneous rates of change 10.2.4 Derivatives 10.2.5 Exercises

More information

Students need encouragement. So if a student gets an answer right, tell them it was a lucky guess. That way, they develop a good, lucky feeling.

Students need encouragement. So if a student gets an answer right, tell them it was a lucky guess. That way, they develop a good, lucky feeling. Chapter 8 Analytic Functions Stuents nee encouragement. So if a stuent gets an answer right, tell them it was a lucky guess. That way, they evelop a goo, lucky feeling. 1 8.1 Complex Derivatives -Jack

More information

Taylor and Maclaurin Series

Taylor and Maclaurin Series Taylor and Maclaurin Series MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Background We have seen that some power series converge. When they do, we can think of them as

More information

and the compositional inverse when it exists is A.

and the compositional inverse when it exists is A. Lecture B jacques@ucsd.edu Notation: R denotes a ring, N denotes the set of sequences of natural numbers with finite support, is a generic element of N, is the infinite zero sequence, n 0 R[[ X]] denotes

More information

TMA4120, Matematikk 4K, Fall Date Section Topic HW Textbook problems Suppl. Answers. Sept 12 Aug 31/

TMA4120, Matematikk 4K, Fall Date Section Topic HW Textbook problems Suppl. Answers. Sept 12 Aug 31/ TMA420, Matematikk 4K, Fall 206 LECTURE SCHEDULE AND ASSIGNMENTS Date Section Topic HW Textbook problems Suppl Answers Aug 22 6 Laplace transform 6:,7,2,2,22,23,25,26,4 A Sept 5 Aug 24/25 62-3 ODE, Heaviside

More information

17 The functional equation

17 The functional equation 18.785 Number theory I Fall 16 Lecture #17 11/8/16 17 The functional equation In the previous lecture we proved that the iemann zeta function ζ(s) has an Euler product and an analytic continuation to the

More information

Sec 4.1 Limits, Informally. When we calculated f (x), we first started with the difference quotient. f(x + h) f(x) h

Sec 4.1 Limits, Informally. When we calculated f (x), we first started with the difference quotient. f(x + h) f(x) h 1 Sec 4.1 Limits, Informally When we calculated f (x), we first started with the difference quotient f(x + h) f(x) h and made h small. In other words, f (x) is the number f(x+h) f(x) approaches as h gets

More information

Final Exam Study Guide

Final Exam Study Guide Final Exam Study Guide Final Exam Coverage: Sections 10.1-10.2, 10.4-10.5, 10.7, 11.2-11.4, 12.1-12.6, 13.1-13.2, 13.4-13.5, and 14.1 Sections/topics NOT on the exam: Sections 10.3 (Continuity, it definition

More information

Section Taylor and Maclaurin Series

Section Taylor and Maclaurin Series Section.0 Taylor and Maclaurin Series Ruipeng Shen Feb 5 Taylor and Maclaurin Series Main Goal: How to find a power series representation for a smooth function us assume that a smooth function has a power

More information

Math 0230 Calculus 2 Lectures

Math 0230 Calculus 2 Lectures Math 00 Calculus Lectures Chapter 8 Series Numeration of sections corresponds to the text James Stewart, Essential Calculus, Early Transcendentals, Second edition. Section 8. Sequences A sequence is a

More information

Solution: f( 1) = 3 1)

Solution: f( 1) = 3 1) Gateway Questions How to Evaluate Functions at a Value Using the Rules Identify the independent variable in the rule of function. Replace the independent variable with big parenthesis. Plug in the input

More information

Mathematics Notes for Class 12 chapter 7. Integrals

Mathematics Notes for Class 12 chapter 7. Integrals 1 P a g e Mathematics Notes for Class 12 chapter 7. Integrals Let f(x) be a function. Then, the collection of all its primitives is called the indefinite integral of f(x) and is denoted by f(x)dx. Integration

More information

Convergence of sequences and series

Convergence of sequences and series Convergence of sequences and series A sequence f is a map from N the positive integers to a set. We often write the map outputs as f n rather than f(n). Often we just list the outputs in order and leave

More information

A Symbolic Operator Approach to Power Series Transformation-Expansion Formulas

A Symbolic Operator Approach to Power Series Transformation-Expansion Formulas 1 2 3 47 6 23 11 Journal of Integer Sequences, Vol. 11 2008, Article 08.2.7 A Symbolic Operator Approach to Power Series Transformation-Expansion Formulas Tian-Xiao He 1 Department of Mathematics and Computer

More information

Chapter 2: Differentiation

Chapter 2: Differentiation Chapter 2: Differentiation Winter 2016 Department of Mathematics Hong Kong Baptist University 1 / 75 2.1 Tangent Lines and Their Slopes This section deals with the problem of finding a straight line L

More information

Conformal maps. Lent 2019 COMPLEX METHODS G. Taylor. A star means optional and not necessarily harder.

Conformal maps. Lent 2019 COMPLEX METHODS G. Taylor. A star means optional and not necessarily harder. Lent 29 COMPLEX METHODS G. Taylor A star means optional and not necessarily harder. Conformal maps. (i) Let f(z) = az + b, with ad bc. Where in C is f conformal? cz + d (ii) Let f(z) = z +. What are the

More information

Is Analysis Necessary?

Is Analysis Necessary? Is Analysis Necessary? Ira M. Gessel Brandeis University Waltham, MA gessel@brandeis.edu Special Session on Algebraic and Analytic Combinatorics AMS Fall Eastern Meeting University of Connecticut, Storrs

More information

MOMENTS OF HYPERGEOMETRIC HURWITZ ZETA FUNCTIONS

MOMENTS OF HYPERGEOMETRIC HURWITZ ZETA FUNCTIONS MOMENTS OF HYPERGEOMETRIC HURWITZ ZETA FUNCTIONS ABDUL HASSEN AND HIEU D. NGUYEN Abstract. This paper investigates a generalization the classical Hurwitz zeta function. It is shown that many of the properties

More information

MATH 31BH Homework 5 Solutions

MATH 31BH Homework 5 Solutions MATH 3BH Homework 5 Solutions February 4, 204 Problem.8.2 (a) Let x t f y = x 2 + y 2 + 2z 2 and g(t) = t 2. z t 3 Then by the chain rule a a a D(g f) b = Dg f b Df b c c c = [Dg(a 2 + b 2 + 2c 2 )] [

More information

2.5 SOME APPLICATIONS OF THE CHAIN RULE

2.5 SOME APPLICATIONS OF THE CHAIN RULE 2.5 SOME APPLICATIONS OF THE CHAIN RULE The Chain Rule will help us etermine the erivatives of logarithms an exponential functions a x. We will also use it to answer some applie questions an to fin slopes

More information

Lecture 9. = 1+z + 2! + z3. 1 = 0, it follows that the radius of convergence of (1) is.

Lecture 9. = 1+z + 2! + z3. 1 = 0, it follows that the radius of convergence of (1) is. The Exponential Function Lecture 9 The exponential function 1 plays a central role in analysis, more so in the case of complex analysis and is going to be our first example using the power series method.

More information

Advanced Mathematics Support Programme Edexcel Year 2 Core Pure Suggested Scheme of Work ( )

Advanced Mathematics Support Programme Edexcel Year 2 Core Pure Suggested Scheme of Work ( ) Edexcel Year 2 Core Pure Suggested Scheme of Work (2018-2019) This template shows how Integral Resources and AMSP FM videos can be used to support Further Mathematics students and teachers. This template

More information

Section 7.4: Inverse Laplace Transform

Section 7.4: Inverse Laplace Transform Section 74: Inverse Laplace Transform A natural question to ask about any function is whether it has an inverse function We now ask this question about the Laplace transform: given a function F (s), will

More information

AP Calculus Chapter 9: Infinite Series

AP Calculus Chapter 9: Infinite Series AP Calculus Chapter 9: Infinite Series 9. Sequences a, a 2, a 3, a 4, a 5,... Sequence: A function whose domain is the set of positive integers n = 2 3 4 a n = a a 2 a 3 a 4 terms of the sequence Begin

More information

Chapter 2: Differentiation

Chapter 2: Differentiation Chapter 2: Differentiation Spring 2018 Department of Mathematics Hong Kong Baptist University 1 / 82 2.1 Tangent Lines and Their Slopes This section deals with the problem of finding a straight line L

More information

Math 115 Section 018 Course Note

Math 115 Section 018 Course Note Course Note 1 General Functions Definition 1.1. A function is a rule that takes certain numbers as inputs an assigns to each a efinite output number. The set of all input numbers is calle the omain of

More information

Formulas for probability theory and linear models SF2941

Formulas for probability theory and linear models SF2941 Formulas for probability theory and linear models SF2941 These pages + Appendix 2 of Gut) are permitted as assistance at the exam. 11 maj 2008 Selected formulae of probability Bivariate probability Transforms

More information

Transformations and Expectations

Transformations and Expectations Transformations and Expectations 1 Distributions of Functions of a Random Variable If is a random variable with cdf F (x), then any function of, say g(), is also a random variable. Sine Y = g() is a function

More information

Pure Further Mathematics 1. Revision Notes

Pure Further Mathematics 1. Revision Notes Pure Further Mathematics Revision Notes June 20 2 FP JUNE 20 SDB Further Pure Complex Numbers... 3 Definitions an arithmetical operations... 3 Complex conjugate... 3 Properties... 3 Complex number plane,

More information

MATH : Calculus II (42809) SYLLABUS, Spring 2010 MW 4-5:50PM, JB- 138

MATH : Calculus II (42809) SYLLABUS, Spring 2010 MW 4-5:50PM, JB- 138 MATH -: Calculus II (489) SYLLABUS, Spring MW 4-5:5PM, JB- 38 John Sarli, JB-36 O ce Hours: MTW 3-4PM, and by appointment (99) 537-5374 jsarli@csusb.edu Text: Calculus of a Single Variable, Larson/Hostetler/Edwards

More information

CHAPTER 3 ELEMENTARY FUNCTIONS 28. THE EXPONENTIAL FUNCTION. Definition: The exponential function: The exponential function e z by writing

CHAPTER 3 ELEMENTARY FUNCTIONS 28. THE EXPONENTIAL FUNCTION. Definition: The exponential function: The exponential function e z by writing CHAPTER 3 ELEMENTARY FUNCTIONS We consider here various elementary functions studied in calculus and define corresponding functions of a complex variable. To be specific, we define analytic functions of

More information

Math 341: Probability Seventeenth Lecture (11/10/09)

Math 341: Probability Seventeenth Lecture (11/10/09) Math 341: Probability Seventeenth Lecture (11/10/09) Steven J Miller Williams College Steven.J.Miller@williams.edu http://www.williams.edu/go/math/sjmiller/ public html/341/ Bronfman Science Center Williams

More information

Contents. 2.1 Motivation: Rates and Tangent Lines. Calculus I (part 2): Introduction to Dierentiation (by Evan Dummit, 2016, v. 2.

Contents. 2.1 Motivation: Rates and Tangent Lines. Calculus I (part 2): Introduction to Dierentiation (by Evan Dummit, 2016, v. 2. Calculus I (part 2): Introuction to Dierentiation (by Evan Dummit, 2016, v 250) Contents 2 Introuction to Dierentiation 1 21 Motivation: Rates an Tangent Lines 1 22 Formal Denition of the Derivative 3

More information

P(x) = 1 + x n. (20.11) n n φ n(x) = exp(x) = lim φ (x) (20.8) Our first task for the chain rule is to find the derivative of the exponential

P(x) = 1 + x n. (20.11) n n φ n(x) = exp(x) = lim φ (x) (20.8) Our first task for the chain rule is to find the derivative of the exponential 20. Derivatives of compositions: the chain rule At the en of the last lecture we iscovere a nee for the erivative of a composition. In this lecture we show how to calculate it. Accoringly, let P have omain

More information

Topic 7: Convergence of Random Variables

Topic 7: Convergence of Random Variables Topic 7: Convergence of Ranom Variables Course 003, 2016 Page 0 The Inference Problem So far, our starting point has been a given probability space (S, F, P). We now look at how to generate information

More information

d dx [xn ] = nx n 1. (1) dy dx = 4x4 1 = 4x 3. Theorem 1.3 (Derivative of a constant function). If f(x) = k and k is a constant, then f (x) = 0.

d dx [xn ] = nx n 1. (1) dy dx = 4x4 1 = 4x 3. Theorem 1.3 (Derivative of a constant function). If f(x) = k and k is a constant, then f (x) = 0. Calculus refresher Disclaimer: I claim no original content on this ocument, which is mostly a summary-rewrite of what any stanar college calculus book offers. (Here I ve use Calculus by Dennis Zill.) I

More information

Rules of Differentiation

Rules of Differentiation LECTURE 2 Rules of Differentiation At te en of Capter 2, we finally arrive at te following efinition of te erivative of a function f f x + f x x := x 0 oing so only after an extene iscussion as wat te

More information

Synopsis of Complex Analysis. Ryan D. Reece

Synopsis of Complex Analysis. Ryan D. Reece Synopsis of Complex Analysis Ryan D. Reece December 7, 2006 Chapter Complex Numbers. The Parts of a Complex Number A complex number, z, is an ordered pair of real numbers similar to the points in the real

More information

Complex Variables & Integral Transforms

Complex Variables & Integral Transforms Complex Variables & Integral Transforms Notes taken by J.Pearson, from a S4 course at the U.Manchester. Lecture delivered by Dr.W.Parnell July 9, 007 Contents 1 Complex Variables 3 1.1 General Relations

More information

e x = 1 + x + x2 2! + x3 If the function f(x) can be written as a power series on an interval I, then the power series is of the form

e x = 1 + x + x2 2! + x3 If the function f(x) can be written as a power series on an interval I, then the power series is of the form Taylor Series Given a function f(x), we would like to be able to find a power series that represents the function. For example, in the last section we noted that we can represent e x by the power series

More information

Chapter 1. Functions, Graphs, and Limits

Chapter 1. Functions, Graphs, and Limits Review for Final Exam Lecturer: Sangwook Kim Office : Science & Tech I, 226D math.gmu.eu/ skim22 Chapter 1. Functions, Graphs, an Limits A function is a rule that assigns to each objects in a set A exactly

More information

ELEC3114 Control Systems 1

ELEC3114 Control Systems 1 ELEC34 Control Systems Linear Systems - Moelling - Some Issues Session 2, 2007 Introuction Linear systems may be represente in a number of ifferent ways. Figure shows the relationship between various representations.

More information

Power series solutions for 2nd order linear ODE s (not necessarily with constant coefficients) a n z n. n=0

Power series solutions for 2nd order linear ODE s (not necessarily with constant coefficients) a n z n. n=0 Lecture 22 Power series solutions for 2nd order linear ODE s (not necessarily with constant coefficients) Recall a few facts about power series: a n z n This series in z is centered at z 0. Here z can

More information

SECTION A. f(x) = ln(x). Sketch the graph of y = f(x), indicating the coordinates of any points where the graph crosses the axes.

SECTION A. f(x) = ln(x). Sketch the graph of y = f(x), indicating the coordinates of any points where the graph crosses the axes. SECTION A 1. State the maximal domain and range of the function f(x) = ln(x). Sketch the graph of y = f(x), indicating the coordinates of any points where the graph crosses the axes. 2. By evaluating f(0),

More information

Completion Date: Monday February 11, 2008

Completion Date: Monday February 11, 2008 MATH 4 (R) Winter 8 Intermediate Calculus I Solutions to Problem Set #4 Completion Date: Monday February, 8 Department of Mathematical and Statistical Sciences University of Alberta Question. [Sec..9,

More information

1 Review of di erential calculus

1 Review of di erential calculus Review of di erential calculus This chapter presents the main elements of di erential calculus needed in probability theory. Often, students taking a course on probability theory have problems with concepts

More information

February 21 Math 1190 sec. 63 Spring 2017

February 21 Math 1190 sec. 63 Spring 2017 February 21 Math 1190 sec. 63 Spring 2017 Chapter 2: Derivatives Let s recall the efinitions an erivative rules we have so far: Let s assume that y = f (x) is a function with c in it s omain. The erivative

More information

The Perrin Conjugate and the Laguerre Orthogonal Polynomial

The Perrin Conjugate and the Laguerre Orthogonal Polynomial The Perrin Conjugate and the Laguerre Orthogonal Polynomial In a previous chapter I defined the conjugate of a cubic polynomial G(x) = x 3 - Bx Cx - D as G(x)c = x 3 + Bx Cx + D. By multiplying the polynomial

More information

Here are brief notes about topics covered in class on complex numbers, focusing on what is not covered in the textbook.

Here are brief notes about topics covered in class on complex numbers, focusing on what is not covered in the textbook. Phys374, Spring 2008, Prof. Ted Jacobson Department of Physics, University of Maryland Complex numbers version 5/21/08 Here are brief notes about topics covered in class on complex numbers, focusing on

More information

Differentiation ( , 9.5)

Differentiation ( , 9.5) Chapter 2 Differentiation (8.1 8.3, 9.5) 2.1 Rate of Change (8.2.1 5) Recall that the equation of a straight line can be written as y = mx + c, where m is the slope or graient of the line, an c is the

More information

1 The functional equation for ζ

1 The functional equation for ζ 18.785: Analytic Number Theory, MIT, spring 27 (K.S. Kedlaya) The functional equation for the Riemann zeta function In this unit, we establish the functional equation property for the Riemann zeta function,

More information

Integration by Substitution

Integration by Substitution November 22, 2013 Introduction 7x 2 cos(3x 3 )dx =? 2xe x2 +5 dx =? Chain rule The chain rule: d dx (f (g(x))) = f (g(x)) g (x). Use the chain rule to find f (x) and then write the corresponding anti-differentiation

More information

CALCULUS JIA-MING (FRANK) LIOU

CALCULUS JIA-MING (FRANK) LIOU CALCULUS JIA-MING (FRANK) LIOU Abstract. Contents. Power Series.. Polynomials and Formal Power Series.2. Radius of Convergence 2.3. Derivative and Antiderivative of Power Series 4.4. Power Series Expansion

More information

NEERAJ KUMAR AND K. SENTHIL KUMAR. 1. Introduction. Theorem 1 motivate us to ask the following:

NEERAJ KUMAR AND K. SENTHIL KUMAR. 1. Introduction. Theorem 1 motivate us to ask the following: NOTE ON VANISHING POWER SUMS OF ROOTS OF UNITY NEERAJ KUMAR AND K. SENTHIL KUMAR Abstract. For xe positive integers m an l, we give a complete list of integers n for which their exist mth complex roots

More information

INTEGRATION WORKSHOP 2003 COMPLEX ANALYSIS EXERCISES

INTEGRATION WORKSHOP 2003 COMPLEX ANALYSIS EXERCISES INTEGRATION WORKSHOP 23 COMPLEX ANALYSIS EXERCISES DOUGLAS ULMER 1. Meromorphic functions on the Riemann sphere It s often useful to allow functions to take the value. This exercise outlines one way to

More information

CHAPTER 1 : DIFFERENTIABLE MANIFOLDS. 1.1 The definition of a differentiable manifold

CHAPTER 1 : DIFFERENTIABLE MANIFOLDS. 1.1 The definition of a differentiable manifold CHAPTER 1 : DIFFERENTIABLE MANIFOLDS 1.1 The efinition of a ifferentiable manifol Let M be a topological space. This means that we have a family Ω of open sets efine on M. These satisfy (1), M Ω (2) the

More information

Extreme Values by Resnick

Extreme Values by Resnick 1 Extreme Values by Resnick 1 Preliminaries 1.1 Uniform Convergence We will evelop the iea of something calle continuous convergence which will be useful to us later on. Denition 1. Let X an Y be metric

More information

Math 4263 Homework Set 1

Math 4263 Homework Set 1 Homework Set 1 1. Solve the following PDE/BVP 2. Solve the following PDE/BVP 2u t + 3u x = 0 u (x, 0) = sin (x) u x + e x u y = 0 u (0, y) = y 2 3. (a) Find the curves γ : t (x (t), y (t)) such that that

More information

Section x7 +

Section x7 + Difference Equations to Differential Equations Section 5. Polynomial Approximations In Chapter 3 we discussed the problem of finding the affine function which best approximates a given function about some

More information

Science One Math. January

Science One Math. January Science One Math January 10 2018 (last time) The Fundamental Theorem of Calculus (FTC) Let f be continuous on an interval I containing a. 1. Define F(x) = f t dt with F (x) = f(x). on I. Then F is differentiable

More information

MATH 56A: STOCHASTIC PROCESSES CHAPTER 3

MATH 56A: STOCHASTIC PROCESSES CHAPTER 3 MATH 56A: STOCHASTIC PROCESSES CHAPTER 3 Plan for rest of semester (1) st week (8/31, 9/6, 9/7) Chap 0: Diff eq s an linear recursion (2) n week (9/11...) Chap 1: Finite Markov chains (3) r week (9/18...)

More information

1 Assignment 1: Nonlinear dynamics (due September

1 Assignment 1: Nonlinear dynamics (due September Assignment : Nonlinear dynamics (due September 4, 28). Consider the ordinary differential equation du/dt = cos(u). Sketch the equilibria and indicate by arrows the increase or decrease of the solutions.

More information

2.6 Logarithmic Functions. Inverse Functions. Question: What is the relationship between f(x) = x 2 and g(x) = x?

2.6 Logarithmic Functions. Inverse Functions. Question: What is the relationship between f(x) = x 2 and g(x) = x? Inverse Functions Question: What is the relationship between f(x) = x 3 and g(x) = 3 x? Question: What is the relationship between f(x) = x 2 and g(x) = x? Definition (One-to-One Function) A function f

More information

Syllabus: for Complex variables

Syllabus: for Complex variables EE-2020, Spring 2009 p. 1/42 Syllabus: for omplex variables 1. Midterm, (4/27). 2. Introduction to Numerical PDE (4/30): [Ref.num]. 3. omplex variables: [Textbook]h.13-h.18. omplex numbers and functions,

More information

Review of Differentiation and Integration for Ordinary Differential Equations

Review of Differentiation and Integration for Ordinary Differential Equations Schreyer Fall 208 Review of Differentiation an Integration for Orinary Differential Equations In this course you will be expecte to be able to ifferentiate an integrate quickly an accurately. Many stuents

More information

8 Singular Integral Operators and L p -Regularity Theory

8 Singular Integral Operators and L p -Regularity Theory 8 Singular Integral Operators and L p -Regularity Theory 8. Motivation See hand-written notes! 8.2 Mikhlin Multiplier Theorem Recall that the Fourier transformation F and the inverse Fourier transformation

More information

You should also review L Hôpital s Rule, section 3.6; follow the homework link above for exercises.

You should also review L Hôpital s Rule, section 3.6; follow the homework link above for exercises. BEFORE You Begin Calculus II If it has been awhile since you ha Calculus, I strongly suggest that you refresh both your ifferentiation an integration skills. I woul also like to remin you that in Calculus,

More information

Science One Integral Calculus. January 9, 2019

Science One Integral Calculus. January 9, 2019 Science One Integral Calculus January 9, 2019 Recap: What have we learned so far? The definite integral is defined as a limit of Riemann sums Riemann sums can be constructed using any point in a subinterval

More information

Summary: Primer on Integral Calculus:

Summary: Primer on Integral Calculus: Physics 2460 Electricity and Magnetism I, Fall 2006, Primer on Integration: Part I 1 Summary: Primer on Integral Calculus: Part I 1. Integrating over a single variable: Area under a curve Properties of

More information

4 Differential Equations

4 Differential Equations Advanced Calculus Chapter 4 Differential Equations 65 4 Differential Equations 4.1 Terminology Let U R n, and let y : U R. A differential equation in y is an equation involving y and its (partial) derivatives.

More information

Northwestern University Department of Electrical Engineering and Computer Science

Northwestern University Department of Electrical Engineering and Computer Science Northwestern University Department of Electrical Engineering and Computer Science EECS 454: Modeling and Analysis of Communication Networks Spring 2008 Probability Review As discussed in Lecture 1, probability

More information

2.12: Derivatives of Exp/Log (cont d) and 2.15: Antiderivatives and Initial Value Problems

2.12: Derivatives of Exp/Log (cont d) and 2.15: Antiderivatives and Initial Value Problems 2.12: Derivatives of Exp/Log (cont d) and 2.15: Antiderivatives and Initial Value Problems Mathematics 3 Lecture 14 Dartmouth College February 03, 2010 Derivatives of the Exponential and Logarithmic Functions

More information

Math 421 Homework 1. Paul Hacking. September 22, 2015

Math 421 Homework 1. Paul Hacking. September 22, 2015 Math 421 Homework 1 Paul Hacking September 22, 2015 (1) Compute the following products of complex numbers. Express your answer in the form x + yi where x and y are real numbers. (a) (2 + i)(5 + 3i) (b)

More information

For more information visit

For more information visit If the integrand is a derivative of a known function, then the corresponding indefinite integral can be directly evaluated. If the integrand is not a derivative of a known function, the integral may be

More information

Section 3.1. Best Affine Approximations. Difference Equations to Differential Equations

Section 3.1. Best Affine Approximations. Difference Equations to Differential Equations Difference Equations to Differential Equations Section 3.1 Best Affine Approximations We are now in a position to discuss the two central problems of calculus as mentioned in Section 1.1. In this chapter

More information

DIFFERENTIAL EQUATIONS

DIFFERENTIAL EQUATIONS DIFFERENTIAL EQUATIONS 1. Basic Terminology A differential equation is an equation that contains an unknown function together with one or more of its derivatives. 1 Examples: 1. y = 2x + cos x 2. dy dt

More information

INTEGRATION WORKSHOP 2004 COMPLEX ANALYSIS EXERCISES

INTEGRATION WORKSHOP 2004 COMPLEX ANALYSIS EXERCISES INTEGRATION WORKSHOP 2004 COMPLEX ANALYSIS EXERCISES PHILIP FOTH 1. Cauchy s Formula and Cauchy s Theorem 1. Suppose that γ is a piecewise smooth positively ( counterclockwise ) oriented simple closed

More information

Konkretna matematika

Konkretna matematika ITT9131 Konkreetne Matemaatika Concrete mathematics Konkretna matematika Jaan Penjam Silvio Capobianco TTÜ arvutiteaduse instituut, teoreetilise informaatika õppetool Küberneetika Instituudi tarkvarateaduse

More information

Calculus Favorite: Stirling s Approximation, Approximately

Calculus Favorite: Stirling s Approximation, Approximately Calculus Favorite: Stirling s Approximation, Approximately Robert Sachs Department of Mathematical Sciences George Mason University Fairfax, Virginia 22030 rsachs@gmu.edu August 6, 2011 Introduction Stirling

More information

MATH 120 Theorem List

MATH 120 Theorem List December 11, 2016 Disclaimer: Many of the theorems covere in class were not name, so most of the names on this sheet are not efinitive (they are escriptive names rather than given names). Lecture Theorems

More information

Infinite Series. 1 Introduction. 2 General discussion on convergence

Infinite Series. 1 Introduction. 2 General discussion on convergence Infinite Series 1 Introduction I will only cover a few topics in this lecture, choosing to discuss those which I have used over the years. The text covers substantially more material and is available for

More information

DIFFERENTIAL EQUATIONS

DIFFERENTIAL EQUATIONS DIFFERENTIAL EQUATIONS Basic Terminology A differential equation is an equation that contains an unknown function together with one or more of its derivatives. 1 Examples: 1. y = 2x + cos x 2. dy dt =

More information

Assignment 1. g i (x 1,..., x n ) dx i = 0. i=1

Assignment 1. g i (x 1,..., x n ) dx i = 0. i=1 Assignment 1 Golstein 1.4 The equations of motion for the rolling isk are special cases of general linear ifferential equations of constraint of the form g i (x 1,..., x n x i = 0. i=1 A constraint conition

More information

f (n) (z 0 ) Theorem [Morera s Theorem] Suppose f is continuous on a domain U, and satisfies that for any closed curve γ in U, γ

f (n) (z 0 ) Theorem [Morera s Theorem] Suppose f is continuous on a domain U, and satisfies that for any closed curve γ in U, γ Remarks. 1. So far we have seen that holomorphic is equivalent to analytic. Thus, if f is complex differentiable in an open set, then it is infinitely many times complex differentiable in that set. This

More information

(e) (i) Prove that C(x) = C( x) for all x. (2)

(e) (i) Prove that C(x) = C( x) for all x. (2) Revision - chapters and 3 part two. (a) Sketch the graph of f (x) = sin 3x + sin 6x, 0 x. Write down the exact period of the function f. (Total 3 marks). (a) Sketch the graph of the function C ( x) cos

More information

Calculus & Analytic Geometry I

Calculus & Analytic Geometry I TQS 124 Autumn 2008 Quinn Calculus & Analytic Geometry I The Derivative: Analytic Viewpoint Derivative of a Constant Function. For c a constant, the derivative of f(x) = c equals f (x) = Derivative of

More information