NM Temme 1. Introduction the Incomplete Gamma Functions Are Defined by the Integrals 7(A,*)
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Integration in Terms of Exponential Integrals and Incomplete Gamma Functions
Integration in terms of exponential integrals and incomplete gamma functions Waldemar Hebisch Wrocªaw University [email protected] 13 July 2016 Introduction What is FriCAS? I FriCAS is an advanced computer algebra system I forked from Axiom in 2007 I about 30% of mathematical code is new compared to Axiom I about 200000 lines of mathematical code I math code written in Spad (high level strongly typed language very similar to FriCAS interactive language) I runtime system currently based on Lisp Some functionality added to FriCAS after fork: I several improvements to integrator I limits via Gruntz algorithm I knows about most classical special functions I guessing package I package for computations in quantum probability I noncommutative Groebner bases I asymptotically fast arbitrary precision computation of elliptic functions and elliptic integrals I new user interfaces (Emacs mode and Texmacs interface) FriCAS inherited from Axiom good (probably the best at that time) implementation of Risch algorithm (Bronstein, . ) I strong for elementary integration I when integral needed special functions used pattern matching Part of motivation for current work came from Rubi testsuite: Rubi showed that there is a lot of functions which are integrable in terms of relatively few special functions. I Adapting Rubi looked dicult I Previous work on adding special functions to Risch integrator was widely considered impractical My conclusion: Need new algorithmic approach. Ex post I claim that for considered here class of functions extension to Risch algorithm is much more powerful than pattern matching. Informally Ei(u)0 = u0 exp(u)=u Γ(a; u)0 = u0um=k exp(−u) for a = (m + k)=k and −k < m < 0. -
The Error Function Mathematical Physics
R. I. Badran The Error Function Mathematical Physics The Error Function and Stirling’s Formula The Error Function: x 2 The curve of the Gaussian function y e is called the bell-shaped graph. The error function is defined as the area under part of this curve: x 2 2 erf (x) et dt 1. . 0 There are other definitions of error functions. These are closely related integrals to the above one. 2. a) The normal or Gaussian distribution function. x t2 1 1 1 x P(, x) e 2 dt erf ( ) 2 2 2 2 Proof: Put t 2u and proceed, you might reach a step of x 1 2 P(0, x) eu du P(,x) P(,0) P(0,x) , where 0 1 x P(0, x) erf ( ) Here you can prove that 2 2 . This can be done by using the definition of error function in (1). 0 u2 I I e du Now you need to find P(,0) where . To find this integral you have to put u=x first, then u= y and multiply the two resulting integrals. Make the change of variables to polar coordinate you get R. I. Badran The Error Function Mathematical Physics 0 2 2 I 2 er rdr d 0 From this latter integral you get 1 I P(,0) 2 and 2 . 1 1 x P(, x) erf ( ) 2 2 2 Q. E. D. x 2 t 1 2 1 x 2.b P(0, x) e dt erf ( ) 2 0 2 2 (as proved earlier in 2.a). -
Asymptotic Estimates of Stirling Numbers
Asymptotic Estimates of Stirling Numbers By N. M. Temme New asymptotic estimates are given of the Stirling numbers s~mJ and (S)~ml, of first and second kind, respectively, as n tends to infinity. The approxima tions are uniformly valid with respect to the second parameter m. 1. Introduction The Stirling numbers of the first and second kind, denoted by s~ml and (S~~m>, respectively, are defined through the generating functions n x(x-l)···(x-n+l) = [. S~m)Xm, ( 1.1) m= 0 n L @~mlx(x -1) ··· (x - m + 1), ( 1.2) m= 0 where the left-hand side of (1.1) has the value 1 if n = 0; similarly, for the factors in the right-hand side of (1.2) if m = 0. This gives the 'boundary values' Furthermore, it is convenient to agree on s~ml = @~ml= 0 if m > n. The Stirling numbers are integers; apart from the above mentioned zero values, the numbers of the second kind are positive; those of the first kind have the sign of ( - l)n + m. Address for correspondence: Professor N. M. Temme, CWI, P.O. Box 4079, 1009 AB Amsterdam, The Netherlands. e-mail: [email protected]. STUDIES IN APPLIED MATHEMATICS 89:233-243 (1993) 233 Copyright © 1993 by the Massachusetts Institute of Technology Published by Elsevier Science Publishing Co., Inc. 0022-2526 /93 /$6.00 234 N. M. Temme Alternative generating functions are [ln(x+1)r :x n " s(ln)~ ( 1.3) m! £..,, n n!' n=m ( 1.4) The Stirling numbers play an important role in difference calculus, combina torics, and probability theory. -
Analytic Continuation of Massless Two-Loop Four-Point Functions
CERN-TH/2002-145 hep-ph/0207020 July 2002 Analytic Continuation of Massless Two-Loop Four-Point Functions T. Gehrmanna and E. Remiddib a Theory Division, CERN, CH-1211 Geneva 23, Switzerland b Dipartimento di Fisica, Universit`a di Bologna and INFN, Sezione di Bologna, I-40126 Bologna, Italy Abstract We describe the analytic continuation of two-loop four-point functions with one off-shell external leg and internal massless propagators from the Euclidean region of space-like 1 3decaytoMinkowskian regions relevant to all 1 3and2 2 reactions with one space-like or time-like! off-shell external leg. Our results can be used! to derive two-loop! master integrals and unrenormalized matrix elements for hadronic vector-boson-plus-jet production and deep inelastic two-plus-one-jet production, from results previously obtained for three-jet production in electron{positron annihilation. 1 Introduction In recent years, considerable progress has been made towards the extension of QCD calculations of jet observables towards the next-to-next-to-leading order (NNLO) in perturbation theory. One of the main ingredients in such calculations are the two-loop virtual corrections to the multi leg matrix elements relevant to jet physics, which describe either 1 3 decay or 2 2 scattering reactions: two-loop four-point functions with massless internal propagators and→ up to one off-shell→ external leg. Using dimensional regularization [1, 2] with d = 4 dimensions as regulator for ultraviolet and infrared divergences, the large number of different integrals6 appearing in the two-loop Feynman amplitudes for 2 2 scattering or 1 3 decay processes can be reduced to a small number of master integrals. -
Error Functions
Error functions Nikolai G. Lehtinen April 23, 2010 1 Error function erf x and complementary er- ror function erfc x (Gauss) error function is 2 x 2 erf x = e−t dt (1) √π Z0 and has properties erf ( )= 1, erf (+ ) = 1 −∞ − ∞ erf ( x)= erf (x), erf (x∗) = [erf(x)]∗ − − where the asterisk denotes complex conjugation. Complementary error function is defined as ∞ 2 2 erfc x = e−t dt = 1 erf x (2) √π Zx − Note also that 2 x 2 e−t dt = 1 + erf x −∞ √π Z Another useful formula: 2 x − t π x e 2σ2 dt = σ erf Z0 r 2 "√2σ # Some Russian authors (e.g., Mikhailovskiy, 1975; Bogdanov et al., 1976) call erf x a Cramp function. 1 2 Faddeeva function w(x) Faddeeva (or Fadeeva) function w(x)(Fadeeva and Terent’ev, 1954; Poppe and Wijers, 1990) does not have a name in Abramowitz and Stegun (1965, ch. 7). It is also called complex error function (or probability integral)(Weide- man, 1994; Baumjohann and Treumann, 1997, p. 310) or plasma dispersion function (Weideman, 1994). To avoid confusion, we will reserve the last name for Z(x), see below. Some Russian authors (e.g., Mikhailovskiy, 1975; Bogdanov et al., 1976) call it a (complex) Cramp function and denote as W (x). Faddeeva function is defined as 2 2i x 2 2 2 w(x)= e−x 1+ et dt = e−x [1+erf(ix)] = e−x erfc ( ix) (3) √π Z0 ! − Integral representations: 2 2 i ∞ e−t dt 2ix ∞ e−t dt w(x)= = (4) π −∞ x t π 0 x2 t2 Z − Z − where x> 0. -
An Explicit Formula for Dirichlet's L-Function
University of Tennessee at Chattanooga UTC Scholar Student Research, Creative Works, and Honors Theses Publications 5-2018 An explicit formula for Dirichlet's L-Function Shannon Michele Hyder University of Tennessee at Chattanooga, [email protected] Follow this and additional works at: https://scholar.utc.edu/honors-theses Part of the Mathematics Commons Recommended Citation Hyder, Shannon Michele, "An explicit formula for Dirichlet's L-Function" (2018). Honors Theses. This Theses is brought to you for free and open access by the Student Research, Creative Works, and Publications at UTC Scholar. It has been accepted for inclusion in Honors Theses by an authorized administrator of UTC Scholar. For more information, please contact [email protected]. An Explicit Formula for Dirichlet's L-Function Shannon M. Hyder Departmental Honors Thesis The University of Tennessee at Chattanooga Department of Mathematics Thesis Director: Dr. Andrew Ledoan Examination Date: April 9, 2018 Members of Examination Committee Dr. Andrew Ledoan Dr. Cuilan Gao Dr. Roger Nichols c 2018 Shannon M. Hyder ALL RIGHTS RESERVED i Abstract An Explicit Formula for Dirichlet's L-Function by Shannon M. Hyder The Riemann zeta function has a deep connection to the distribution of primes. In 1911 Landau proved that, for every fixed x > 1, X T xρ = − Λ(x) + O(log T ) 2π 0<γ≤T as T ! 1. Here ρ = β + iγ denotes a complex zero of the zeta function and Λ(x) is an extension of the usual von Mangoldt function, so that Λ(x) = log p if x is a positive integral power of a prime p and Λ(x) = 0 for all other real values of x. -
Global Minimax Approximations and Bounds for the Gaussian Q-Functionbysumsofexponentials 3
IEEE TRANSACTIONS ON COMMUNICATIONS 1 Global Minimax Approximations and Bounds for the Gaussian Q-Function by Sums of Exponentials Islam M. Tanash and Taneli Riihonen , Member, IEEE Abstract—This paper presents a novel systematic methodology The Gaussian Q-function has many applications in statis- to obtain new simple and tight approximations, lower bounds, tical performance analysis such as evaluating bit, symbol, and upper bounds for the Gaussian Q-function, and functions and block error probabilities for various digital modulation thereof, in the form of a weighted sum of exponential functions. They are based on minimizing the maximum absolute or relative schemes and different fading models [5]–[11], and evaluat- error, resulting in globally uniform error functions with equalized ing the performance of energy detectors for cognitive radio extrema. In particular, we construct sets of equations that applications [12], [13], whenever noise and interference or describe the behaviour of the targeted error functions and a channel can be modelled as a Gaussian random variable. solve them numerically in order to find the optimized sets of However, in many cases formulating such probabilities will coefficients for the sum of exponentials. This also allows for establishing a trade-off between absolute and relative error by result in complicated integrals of the Q-function that cannot controlling weights assigned to the error functions’ extrema. We be expressed in a closed form in terms of elementary functions. further extend the proposed procedure to derive approximations Therefore, finding tractable approximations and bounds for and bounds for any polynomial of the Q-function, which in the Q-function becomes a necessity in order to facilitate turn allows approximating and bounding many functions of the expression manipulations and enable its application over a Q-function that meet the Taylor series conditions, and consider the integer powers of the Q-function as a special case. -
Hydrology 510 Quantitative Methods in Hydrology
New Mexico Tech Hyd 510 Hydrology Program Quantitative Methods in Hydrology Hydrology 510 Quantitative Methods in Hydrology Motive Preview: Example of a function and its limits Consider the solute concentration, C [ML-3], in a confined aquifer downstream of a continuous source of solute with fixed concentration, C0, starting at time t=0. Assume that the solute advects in the aquifer while diffusing into the bounding aquitards, above and below (but which themselves have no significant flow). (A homology to this problem would be solute movement in a fracture aquitard (diffusion controlled) Flow aquifer Solute (advection controlled) aquitard (diffusion controlled) x with diffusion into the porous-matrix walls bounding the fracture: the so-called “matrix diffusion” problem. The difference with the original problem is one of spatial scale.) An approximate solution for this conceptual model, describing the space-time variation of concentration in the aquifer, is the function: 1/ 2 x x D C x D C(x,t) = C0 erfc or = erfc B vt − x vB C B v(vt − x) 0 where t is time [T] since the solute was first emitted x is the longitudinal distance [L] downstream, v is the longitudinal groundwater (seepage) velocity [L/T] in the aquifer, D is the effective molecular diffusion coefficient in the aquitard [L2/T], B is the aquifer thickness [L] and erfc is the complementary error function. Describe the behavior of this function. Pick some typical numbers for D/B2 (e.g., D ~ 10-9 m2 s-1, typical for many solutes, and B = 2m) and v (e.g., 0.1 m d-1), and graph the function vs. -
Bernstein's Analytic Continuation of Complex Powers of Polynomials
Bernsteins analytic continuation of complex p owers c Paul Garrett garrettmathumnedu version January Analytic continuation of distributions Statement of the theorems on analytic continuation Bernsteins pro ofs Pro of of the Lemma the Bernstein p olynomial Pro of of the Prop osition estimates on zeros Garrett Bernsteins analytic continuation of complex p owers Let f b e a p olynomial in x x with real co ecients For complex s let n s f b e the function dened by s s f x f x if f x s f x if f x s Certainly for s the function f is lo cally integrable For s in this range s we can dened a distribution denoted by the same symb ol f by Z s s f x x dx f n R n R the space of compactlysupp orted smo oth realvalued where is in C c n functions on R s The ob ject is to analytically continue the distribution f as a meromorphic distributionvalued function of s This typ e of question was considered in several provo cative examples in IM Gelfand and GE Shilovs Generalized Functions volume I One should also ask ab out analytic continuation as a temp ered distribution In a lecture at the Amsterdam Congress IM Gelfand rened this question to require further that one show that the p oles lie in a nite numb er of arithmetic progressions Bernstein proved the result in under a certain regularity hyp othesis on the zeroset of the p olynomial f Published in Journal of Functional Analysis and Its Applications translated from Russian The present discussion includes some background material from complex function theory and -
[Math.AG] 2 Jul 2015 Ic Oetime: Some and Since Time, of People
MONODROMY AND NORMAL FORMS FABRIZIO CATANESE Abstract. We discuss the history of the monodromy theorem, starting from Weierstraß, and the concept of monodromy group. From this viewpoint we compare then the Weierstraß, the Le- gendre and other normal forms for elliptic curves, explaining their geometric meaning and distinguishing them by their stabilizer in PSL(2, Z) and their monodromy. Then we focus on the birth of the concept of the Jacobian variety, and the geometrization of the theory of Abelian functions and integrals. We end illustrating the methods of complex analysis in the simplest issue, the difference equation f(z)= g(z + 1) g(z) on C. − Contents Introduction 1 1. The monodromy theorem 3 1.1. Riemann domain and sheaves 6 1.2. Monodromy or polydromy? 6 2. Normalformsandmonodromy 8 3. Periodic functions and Abelian varieties 16 3.1. Cohomology as difference equations 21 References 23 Introduction In Jules Verne’s novel of 1874, ‘Le Tour du monde en quatre-vingts jours’ , Phileas Fogg is led to his remarkable adventure by a bet made arXiv:1507.00711v1 [math.AG] 2 Jul 2015 in his Club: is it possible to make a tour of the world in 80 days? Idle questions and bets can be very stimulating, but very difficult to answer when they deal with the history of mathematics, and one asks how certain ideas, which have been a common knowledge for long time, did indeed evolve and mature through a long period of time, and through the contributions of many people. In short, there are three idle questions which occupy my attention since some time: Date: July 3, 2015. -
Chapter 4 the Riemann Zeta Function and L-Functions
Chapter 4 The Riemann zeta function and L-functions 4.1 Basic facts We prove some results that will be used in the proof of the Prime Number Theorem (for arithmetic progressions). The L-function of a Dirichlet character χ modulo q is defined by 1 X L(s; χ) = χ(n)n−s: n=1 P1 −s We view ζ(s) = n=1 n as the L-function of the principal character modulo 1, (1) (1) more precisely, ζ(s) = L(s; χ0 ), where χ0 (n) = 1 for all n 2 Z. We first prove that ζ(s) has an analytic continuation to fs 2 C : Re s > 0gnf1g. We use an important summation formula, due to Euler. Lemma 4.1 (Euler's summation formula). Let a; b be integers with a < b and f :[a; b] ! C a continuously differentiable function. Then b X Z b Z b f(n) = f(x)dx + f(a) + (x − [x])f 0(x)dx: n=a a a 105 Remark. This result often occurs in the more symmetric form b Z b Z b X 1 1 0 f(n) = f(x)dx + 2 (f(a) + f(b)) + (x − [x] − 2 )f (x)dx: n=a a a Proof. Let n 2 fa; a + 1; : : : ; b − 1g. Then Z n+1 Z n+1 x − [x]f 0(x)dx = (x − n)f 0(x)dx n n h in+1 Z n+1 Z n+1 = (x − n)f(x) − f(x)dx = f(n + 1) − f(x)dx: n n n By summing over n we get b Z b X Z b (x − [x])f 0(x)dx = f(n) − f(x)dx; a n=a+1 a which implies at once Lemma 4.1. -
Asymptotics of Singularly Perturbed Volterra Type Integro-Differential Equation
Konuralp Journal of Mathematics, 8 (2) (2020) 365-369 Konuralp Journal of Mathematics Journal Homepage: www.dergipark.gov.tr/konuralpjournalmath e-ISSN: 2147-625X Asymptotics of Singularly Perturbed Volterra Type Integro-Differential Equation Fatih Say1 1Department of Mathematics, Faculty of Arts and Sciences, Ordu University, Ordu, Turkey Abstract This paper addresses the asymptotic behaviors of a linear Volterra type integro-differential equation. We study a singular Volterra integro equation in the limiting case of a small parameter with proper choices of the unknown functions in the equation. We show the effectiveness of the asymptotic perturbation expansions with an instructive model equation by the methods in superasymptotics. The methods used in this study are also valid to solve some other Volterra type integral equations including linear Volterra integro-differential equations, fractional integro-differential equations, and system of singular Volterra integral equations involving small (or large) parameters. Keywords: Singular perturbation, Volterra integro-differential equations, asymptotic analysis, singularity 2010 Mathematics Subject Classification: 41A60; 45M05; 34E15 1. Introduction A systematic approach to approximation theory can find in the subject of asymptotic analysis which deals with the study of problems in the appropriate limiting regimes. Approximations of some solutions of differential equations, usually containing a small parameter e, are essential in the analysis. The subject has made tremendous growth in recent years and has a vast literature. Developed techniques of asymptotics are successfully applied to problems including the classical long-standing problems in mathematics, physics, fluid me- chanics, astrodynamics, engineering and many diverse fields, for instance, see [1, 2, 3, 4, 5, 6, 7]. There exists a plethora of examples of asymptotics which includes a wide variety of problems in rich results from the very practical to the highly theoretical analysis.