Degenerate Bernoulli Polynomials, Generalized Factorial Sums, and Their Applications
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Accessing Bernoulli-Numbers by Matrix-Operations Gottfried Helms 3'2006 Version 2.3
Accessing Bernoulli-Numbers by Matrix-Operations Gottfried Helms 3'2006 Version 2.3 Accessing Bernoulli-Numbers by Matrixoperations ........................................................................ 2 1. Introduction....................................................................................................................................................................... 2 2. A common equation of recursion (containing a significant error)..................................................................................... 3 3. Two versions B m and B p of bernoulli-numbers? ............................................................................................................... 4 4. Computation of bernoulli-numbers by matrixinversion of (P-I) ....................................................................................... 6 5. J contains the eigenvalues, and G m resp. G p contain the eigenvectors of P z resp. P s ......................................................... 7 6. The Binomial-Matrix and the Matrixexponential.............................................................................................................. 8 7. Bernoulli-vectors and the Matrixexponential.................................................................................................................... 8 8. The structure of the remaining coefficients in the matrices G m - and G p........................................................................... 9 9. The original problem of Jacob Bernoulli: "Powersums" - from G -
Notes on Euler's Work on Divergent Factorial Series and Their Associated
Indian J. Pure Appl. Math., 41(1): 39-66, February 2010 °c Indian National Science Academy NOTES ON EULER’S WORK ON DIVERGENT FACTORIAL SERIES AND THEIR ASSOCIATED CONTINUED FRACTIONS Trond Digernes¤ and V. S. Varadarajan¤¤ ¤University of Trondheim, Trondheim, Norway e-mail: [email protected] ¤¤University of California, Los Angeles, CA, USA e-mail: [email protected] Abstract Factorial series which diverge everywhere were first considered by Euler from the point of view of summing divergent series. He discovered a way to sum such series and was led to certain integrals and continued fractions. His method of summation was essentialy what we call Borel summation now. In this paper, we discuss these aspects of Euler’s work from the modern perspective. Key words Divergent series, factorial series, continued fractions, hypergeometric continued fractions, Sturmian sequences. 1. Introductory Remarks Euler was the first mathematician to develop a systematic theory of divergent se- ries. In his great 1760 paper De seriebus divergentibus [1, 2] and in his letters to Bernoulli he championed the view, which was truly revolutionary for his epoch, that one should be able to assign a numerical value to any divergent series, thus allowing the possibility of working systematically with them (see [3]). He antic- ipated by over a century the methods of summation of divergent series which are known today as the summation methods of Cesaro, Holder,¨ Abel, Euler, Borel, and so on. Eventually his views would find their proper place in the modern theory of divergent series [4]. But from the beginning Euler realized that almost none of his methods could be applied to the series X1 1 ¡ 1!x + 2!x2 ¡ 3!x3 + ::: = (¡1)nn!xn (1) n=0 40 TROND DIGERNES AND V. -
Calculus Terminology
AP Calculus BC Calculus Terminology Absolute Convergence Asymptote Continued Sum Absolute Maximum Average Rate of Change Continuous Function Absolute Minimum Average Value of a Function Continuously Differentiable Function Absolutely Convergent Axis of Rotation Converge Acceleration Boundary Value Problem Converge Absolutely Alternating Series Bounded Function Converge Conditionally Alternating Series Remainder Bounded Sequence Convergence Tests Alternating Series Test Bounds of Integration Convergent Sequence Analytic Methods Calculus Convergent Series Annulus Cartesian Form Critical Number Antiderivative of a Function Cavalieri’s Principle Critical Point Approximation by Differentials Center of Mass Formula Critical Value Arc Length of a Curve Centroid Curly d Area below a Curve Chain Rule Curve Area between Curves Comparison Test Curve Sketching Area of an Ellipse Concave Cusp Area of a Parabolic Segment Concave Down Cylindrical Shell Method Area under a Curve Concave Up Decreasing Function Area Using Parametric Equations Conditional Convergence Definite Integral Area Using Polar Coordinates Constant Term Definite Integral Rules Degenerate Divergent Series Function Operations Del Operator e Fundamental Theorem of Calculus Deleted Neighborhood Ellipsoid GLB Derivative End Behavior Global Maximum Derivative of a Power Series Essential Discontinuity Global Minimum Derivative Rules Explicit Differentiation Golden Spiral Difference Quotient Explicit Function Graphic Methods Differentiable Exponential Decay Greatest Lower Bound Differential -
Euler and His Work on Infinite Series
BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY Volume 44, Number 4, October 2007, Pages 515–539 S 0273-0979(07)01175-5 Article electronically published on June 26, 2007 EULER AND HIS WORK ON INFINITE SERIES V. S. VARADARAJAN For the 300th anniversary of Leonhard Euler’s birth Table of contents 1. Introduction 2. Zeta values 3. Divergent series 4. Summation formula 5. Concluding remarks 1. Introduction Leonhard Euler is one of the greatest and most astounding icons in the history of science. His work, dating back to the early eighteenth century, is still with us, very much alive and generating intense interest. Like Shakespeare and Mozart, he has remained fresh and captivating because of his personality as well as his ideas and achievements in mathematics. The reasons for this phenomenon lie in his universality, his uniqueness, and the immense output he left behind in papers, correspondence, diaries, and other memorabilia. Opera Omnia [E], his collected works and correspondence, is still in the process of completion, close to eighty volumes and 31,000+ pages and counting. A volume of brief summaries of his letters runs to several hundred pages. It is hard to comprehend the prodigious energy and creativity of this man who fueled such a monumental output. Even more remarkable, and in stark contrast to men like Newton and Gauss, is the sunny and equable temperament that informed all of his work, his correspondence, and his interactions with other people, both common and scientific. It was often said of him that he did mathematics as other people breathed, effortlessly and continuously. -
On the Euler Integral for the Positive and Negative Factorial
On the Euler Integral for the positive and negative Factorial Tai-Choon Yoon ∗ and Yina Yoon (Dated: Dec. 13th., 2020) Abstract We reviewed the Euler integral for the factorial, Gauss’ Pi function, Legendre’s gamma function and beta function, and found that gamma function is defective in Γ(0) and Γ( x) − because they are undefined or indefinable. And we came to a conclusion that the definition of a negative factorial, that covers the domain of the negative space, is needed to the Euler integral for the factorial, as well as the Euler Y function and the Euler Z function, that supersede Legendre’s gamma function and beta function. (Subject Class: 05A10, 11S80) A. The positive factorial and the Euler Y function Leonhard Euler (1707–1783) developed a transcendental progression in 1730[1] 1, which is read xedx (1 x)n. (1) Z − f From this, Euler transformed the above by changing e to g for generalization into f x g dx (1 x)n. (2) Z − Whence, Euler set f = 1 and g = 0, and got an integral for the factorial (!) 2, dx ( lx )n, (3) Z − where l represents logarithm . This is called the Euler integral of the second kind 3, and the equation (1) is called the Euler integral of the first kind. 4, 5 Rewriting the formula (3) as follows with limitation of domain for a positive half space, 1 1 n ln dx, n 0. (4) Z0 x ≥ ∗ Electronic address: [email protected] 1 “On Transcendental progressions that is, those whose general terms cannot be given algebraically” by Leonhard Euler p.3 2 ibid. -
Sums of Powers and the Bernoulli Numbers Laura Elizabeth S
Eastern Illinois University The Keep Masters Theses Student Theses & Publications 1996 Sums of Powers and the Bernoulli Numbers Laura Elizabeth S. Coen Eastern Illinois University This research is a product of the graduate program in Mathematics and Computer Science at Eastern Illinois University. Find out more about the program. Recommended Citation Coen, Laura Elizabeth S., "Sums of Powers and the Bernoulli Numbers" (1996). Masters Theses. 1896. https://thekeep.eiu.edu/theses/1896 This is brought to you for free and open access by the Student Theses & Publications at The Keep. It has been accepted for inclusion in Masters Theses by an authorized administrator of The Keep. For more information, please contact [email protected]. THESIS REPRODUCTION CERTIFICATE TO: Graduate Degree Candidates (who have written formal theses) SUBJECT: Permission to Reproduce Theses The University Library is rece1v1ng a number of requests from other institutions asking permission to reproduce dissertations for inclusion in their library holdings. Although no copyright laws are involved, we feel that professional courtesy demands that permission be obtained from the author before we allow theses to be copied. PLEASE SIGN ONE OF THE FOLLOWING STATEMENTS: Booth Library of Eastern Illinois University has my permission to lend my thesis to a reputable college or university for the purpose of copying it for inclusion in that institution's library or research holdings. u Author uate I respectfully request Booth Library of Eastern Illinois University not allow my thesis -
The Structure of Bernoulli Numbers
The structure of Bernoulli numbers Bernd C. Kellner Abstract We conjecture that the structure of Bernoulli numbers can be explicitly given in the closed form n 2 −1 −1 n−l −1 −1 Bn = (−1) |n|p |p (χ(p,l) − p−1 )|p p p,l ∈ irr p−1∤n ( ) Ψ1 p−1|n Y n≡l (modY p−1) Y irr where the χ(p,l) are zeros of certain p-adic zeta functions and Ψ1 is the set of irregular pairs. The more complicated but improbable case where the conjecture does not hold is also handled; we obtain an unconditional structural formula for Bernoulli numbers. Finally, applications are given which are related to classical results. Keywords: Bernoulli number, Kummer congruences, irregular prime, irregular pair of higher order, Riemann zeta function, p-adic zeta function Mathematics Subject Classification 2000: 11B68 1 Introduction The classical Bernoulli numbers Bn are defined by the power series ∞ z zn = B , |z| < 2π , ez − 1 n n! n=0 X where all numbers Bn are zero with odd index n > 1. The even-indexed rational 1 1 numbers Bn alternate in sign. First values are given by B0 = 1, B1 = − 2 , B2 = 6 , 1 arXiv:math/0411498v1 [math.NT] 22 Nov 2004 B4 = − 30 . Although the first numbers are small with |Bn| < 1 for n = 2, 4,..., 12, these numbers grow very rapidly with |Bn|→∞ for even n →∞. For now, let n be an even positive integer. An elementary property of Bernoulli numbers is the following discovered independently by T. Clausen [Cla40] and K. -
Tight Bounds on the Mutual Coherence of Sensing Matrices for Wigner D-Functions on Regular Grids
Tight bounds on the mutual coherence of sensing matrices for Wigner D-functions on regular grids Arya Bangun, Arash Behboodi, and Rudolf Mathar,∗ October 7, 2020 Abstract Many practical sampling patterns for function approximation on the rotation group utilizes regu- lar samples on the parameter axes. In this paper, we relate the mutual coherence analysis for sensing matrices that correspond to a class of regular patterns to angular momentum analysis in quantum mechanics and provide simple lower bounds for it. The products of Wigner d-functions, which ap- pear in coherence analysis, arise in angular momentum analysis in quantum mechanics. We first represent the product as a linear combination of a single Wigner d-function and angular momentum coefficients, otherwise known as the Wigner 3j symbols. Using combinatorial identities, we show that under certain conditions on the bandwidth and number of samples, the inner product of the columns of the sensing matrix at zero orders, which is equal to the inner product of two Legendre polynomials, dominates the mutual coherence term and fixes a lower bound for it. In other words, for a class of regular sampling patterns, we provide a lower bound for the inner product of the columns of the sensing matrix that can be analytically computed. We verify numerically our theoretical results and show that the lower bound for the mutual coherence is larger than Welch bound. Besides, we provide algorithms that can achieve the lower bound for spherical harmonics. 1 Introduction In many applications, the goal is to recover a function defined on a group, say on the sphere S2 and the rotation group SO(3), from only a few samples [1{5]. -
Higher Order Bernoulli and Euler Numbers
David Vella, Skidmore College [email protected] Generating Functions and Exponential Generating Functions • Given a sequence {푎푛} we can associate to it two functions determined by power series: • Its (ordinary) generating function is ∞ 풏 푓 풙 = 풂풏풙 풏=ퟏ • Its exponential generating function is ∞ 풂 품 풙 = 풏 풙풏 풏! 풏=ퟏ Examples • The o.g.f and the e.g.f of {1,1,1,1,...} are: 1 • f(x) = 1 + 푥 + 푥2 + 푥3 + ⋯ = , and 1−푥 푥 푥2 푥3 • g(x) = 1 + + + + ⋯ = 푒푥, respectively. 1! 2! 3! The second one explains the name... Operations on the functions correspond to manipulations on the sequence. For example, adding two sequences corresponds to adding the ogf’s, while to shift the index of a sequence, we multiply the ogf by x, or differentiate the egf. Thus, the functions provide a convenient way of studying the sequences. Here are a few more famous examples: Bernoulli & Euler Numbers • The Bernoulli Numbers Bn are defined by the following egf: x Bn n x x e 1 n1 n! • The Euler Numbers En are defined by the following egf: x 2e En n Sech(x) 2x x e 1 n0 n! Catalan and Bell Numbers • The Catalan Numbers Cn are known to have the ogf: ∞ 푛 1 − 1 − 4푥 2 퐶 푥 = 퐶푛푥 = = 2푥 1 + 1 − 4푥 푛=1 • Let Sn denote the number of different ways of partitioning a set with n elements into nonempty subsets. It is called a Bell number. It is known to have the egf: ∞ 푆 푥 푛 푥푛 = 푒 푒 −1 푛! 푛=1 Higher Order Bernoulli and Euler Numbers th w • The n Bernoulli Number of order w, B n is defined for positive integer w by: w x B w n xn x e 1 n1 n! th w • The n Euler Number of -
Approximation Properties of G-Bernoulli Polynomials
Approximation properties of q-Bernoulli polynomials M. Momenzadeh and I. Y. Kakangi Near East University Lefkosa, TRNC, Mersiin 10, Turkey Email: [email protected] [email protected] July 10, 2018 Abstract We study the q−analogue of Euler-Maclaurin formula and by introducing a new q-operator we drive to this form. Moreover, approximation properties of q-Bernoulli polynomials is discussed. We estimate the suitable functions as a combination of truncated series of q-Bernoulli polynomials and the error is calculated. This paper can be helpful in two different branches, first solving differential equations by estimating functions and second we may apply these techniques for operator theory. 1 Introduction The present study has sough to investigate the approximation of suitable function f(x) as a linear com- bination of q−Bernoulli polynomials. This study by using q−operators through a parallel way has achived to the kind of Euler expansion for f(x), and expanded the function in terms of q−Bernoulli polynomials. This expansion offers a proper tool to solve q-difference equations or normal differential equation as well. There are many approaches to approximate the capable functions. According to properties of q-functions many q-function have been used in order to approximate a suitable function.For example, at [28], some identities and formulae for the q-Bernstein basis function, including the partition of unity property, formulae for representing the monomials were studied. In addition, a kind of approximation of a function in terms of Bernoulli polynomials are used in several approaches for solving differential equations, such as [7, 20, 21]. -
Euler-Maclaurin Summation Formula
4 Euler-Maclaurin Summation Formula 4.1 Bernoulli Number & Bernoulli Polynomial 4.1.1 Definition of Bernoulli Number Bernoulli numbers Bk ()k =1,2,3, are defined as coefficients of the following equation. x Bk k x =Σ x e -1 k=0 k! 4.1.2 Expreesion of Bernoulli Numbers B B x 0 1 B2 2 B3 3 B4 4 = + x + x + x + x + (1,1) ex-1 0! 1! 2! 3! 4! ex-1 1 x x2 x3 x4 = + + + + + (1.2) x 1! 2! 3! 4! 5! Making the Cauchy product of (1.1) and (1.1) , B1 B0 B2 B1 B0 1 = B + + x + + + x2 + 0 1!1! 0!2! 2!1! 1!2! 0!3! In order to holds this for arbitrary x , B1 B0 B2 B1 B0 B =1 , + =0 , + + =0 , 0 1!1! 0!2! 2!1! 1!2! 0!3! n The coefficient of x is as follows. Bn Bn-1 Bn-2 B1 B0 + + + + + = 0 n!1! ()n -1 !2! ()n-2 !3! 1!n ! 0!()n +1 ! Multiplying both sides by ()n +1 ! , Bn()n +1 ! Bn-1()n+1 ! Bn-2()n +1 ! B1()n +1 ! B0 + + + + + = 0 n !1! ()n-1 !2! ()n -2 !3! 1!n ! 0! Using binomial coefficiets, n +1Cn Bn + n +1Cn-1 Bn-1 + n +1Cn-2 Bn-2 + + n +1C 1 B1 + n +1C 0 B0 = 0 Replacing n +1 with n , (1.3) nnC -1 Bn-1 + nnC -2 Bn-2 + nnC -3 Bn-3 + + nC1 B1 + nC0 B0 = 0 Substituting n =2, 3, 4, for this one by one, 1 21C B + 20C B = 0 B = - 1 0 2 2 1 32C B + 31C B + 30C B = 0 B = 2 1 0 2 6 Thus, we obtain Bernoulli numbers. -
Mathstudio Manual
MathStudio Manual Abs(z) Returns the complex modulus (or magnitude) of a complex number. abs(-3) abs(-x) abs(\im) AiryAi(z) Returns the Airy function Ai(z). AiryAi(2) AiryAi(3-\im) AiryAi(\pi/2) AiryAi(-9) Plot(AiryAi(x),x=[-10,1],numbers=0) Page 1/187 MathStudio Manual AiryBi(z) Returns the Airy function Bi(z). AiryBi(0) AiryBi(10) AiryBi(1+\im) Plot(AiryBi(x),x=[-10,1],numbers=0) AlternatingSeries(n, [terms]) Page 2/187 MathStudio Manual This function approximates the given real number in an alternating series. The result is returned in a matrix with the top row = numerator and the bottom row = denominator of the different terms. Note the alternating sign in the numerator! AlternatingSeries(\pi,7) AlternatingSeries(ln(2),10) AlternatingSeries(sqrt(2),10) AlternatingSeries(-3.23) AlternatingSeries(123456789/987654321) AlternatingSeries(.666) AlternatingSeries(.12121212) Page 3/187 MathStudio Manual AlternatingSeries(.36363) Angle(A, B) Returns the angle between the two vectors A and B. Angle([a@1,b@1,c@1],[a@2,b@2,c@2]) Angle([1,2,3],[4,5,6]) Animate(variable, start, end, [step]) This function creates an animated entry. The variable is initialized to the start value and at each frame is incremented by step and the entry is reevaluated creating animation. When the variable is greater than the value end it is set back to start. Animate(n,1,100) ImagePlot(Random(0,1,n,n)) Page 4/187 MathStudio Manual Apart(f(x), x) Performs partial fraction decomposition on the polynomial function. Apart performs the opposite operation of Together.