Linear First-Order Equations
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Notes on Calculus II Integral Calculus Miguel A. Lerma
Notes on Calculus II Integral Calculus Miguel A. Lerma November 22, 2002 Contents Introduction 5 Chapter 1. Integrals 6 1.1. Areas and Distances. The Definite Integral 6 1.2. The Evaluation Theorem 11 1.3. The Fundamental Theorem of Calculus 14 1.4. The Substitution Rule 16 1.5. Integration by Parts 21 1.6. Trigonometric Integrals and Trigonometric Substitutions 26 1.7. Partial Fractions 32 1.8. Integration using Tables and CAS 39 1.9. Numerical Integration 41 1.10. Improper Integrals 46 Chapter 2. Applications of Integration 50 2.1. More about Areas 50 2.2. Volumes 52 2.3. Arc Length, Parametric Curves 57 2.4. Average Value of a Function (Mean Value Theorem) 61 2.5. Applications to Physics and Engineering 63 2.6. Probability 69 Chapter 3. Differential Equations 74 3.1. Differential Equations and Separable Equations 74 3.2. Directional Fields and Euler’s Method 78 3.3. Exponential Growth and Decay 80 Chapter 4. Infinite Sequences and Series 83 4.1. Sequences 83 4.2. Series 88 4.3. The Integral and Comparison Tests 92 4.4. Other Convergence Tests 96 4.5. Power Series 98 4.6. Representation of Functions as Power Series 100 4.7. Taylor and MacLaurin Series 103 3 CONTENTS 4 4.8. Applications of Taylor Polynomials 109 Appendix A. Hyperbolic Functions 113 A.1. Hyperbolic Functions 113 Appendix B. Various Formulas 118 B.1. Summation Formulas 118 Appendix C. Table of Integrals 119 Introduction These notes are intended to be a summary of the main ideas in course MATH 214-2: Integral Calculus. -
Ordinary Differential Equations
Ordinary Differential Equations for Engineers and Scientists Gregg Waterman Oregon Institute of Technology c 2017 Gregg Waterman This work is licensed under the Creative Commons Attribution 4.0 International license. The essence of the license is that You are free to: Share copy and redistribute the material in any medium or format • Adapt remix, transform, and build upon the material for any purpose, even commercially. • The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution You must give appropriate credit, provide a link to the license, and indicate if changes • were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. No additional restrictions You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits. Notices: You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation. No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material. For any reuse or distribution, you must make clear to others the license terms of this work. The best way to do this is with a link to the web page below. To view a full copy of this license, visit https://creativecommons.org/licenses/by/4.0/legalcode. -
New Dirac Delta Function Based Methods with Applications To
New Dirac Delta function based methods with applications to perturbative expansions in quantum field theory Achim Kempf1, David M. Jackson2, Alejandro H. Morales3 1Departments of Applied Mathematics and Physics 2Department of Combinatorics and Optimization University of Waterloo, Ontario N2L 3G1, Canada, 3Laboratoire de Combinatoire et d’Informatique Math´ematique (LaCIM) Universit´edu Qu´ebec `aMontr´eal, Canada Abstract. We derive new all-purpose methods that involve the Dirac Delta distribution. Some of the new methods use derivatives in the argument of the Dirac Delta. We highlight potential avenues for applications to quantum field theory and we also exhibit a connection to the problem of blurring/deblurring in signal processing. We find that blurring, which can be thought of as a result of multi-path evolution, is, in Euclidean quantum field theory without spontaneous symmetry breaking, the strong coupling dual of the usual small coupling expansion in terms of the sum over Feynman graphs. arXiv:1404.0747v3 [math-ph] 23 Sep 2014 2 1. A method for generating new representations of the Dirac Delta The Dirac Delta distribution, see e.g., [1, 2, 3], serves as a useful tool from physics to engineering. Our aim here is to develop new all-purpose methods involving the Dirac Delta distribution and to show possible avenues for applications, in particular, to quantum field theory. We begin by fixing the conventions for the Fourier transform: 1 1 g(y) := g(x) eixy dx, g(x)= g(y) e−ixy dy (1) √2π √2π Z Z To simplify the notation we denote integration over the real line by the absence of e e integration delimiters. -
Notes Chapter 4(Integration) Definition of an Antiderivative
1 Notes Chapter 4(Integration) Definition of an Antiderivative: A function F is an antiderivative of f on an interval I if for all x in I. Representation of Antiderivatives: If F is an antiderivative of f on an interval I, then G is an antiderivative of f on the interval I if and only if G is of the form G(x) = F(x) + C, for all x in I where C is a constant. Sigma Notation: The sum of n terms a1,a2,a3,…,an is written as where I is the index of summation, ai is the ith term of the sum, and the upper and lower bounds of summation are n and 1. Summation Formulas: 1. 2. 3. 4. Limits of the Lower and Upper Sums: Let f be continuous and nonnegative on the interval [a,b]. The limits as n of both the lower and upper sums exist and are equal to each other. That is, where are the minimum and maximum values of f on the subinterval. Definition of the Area of a Region in the Plane: Let f be continuous and nonnegative on the interval [a,b]. The area if a region bounded by the graph of f, the x-axis and the vertical lines x=a and x=b is Area = where . Definition of a Riemann Sum: Let f be defined on the closed interval [a,b], and let be a partition of [a,b] given by a =x0<x1<x2<…<xn-1<xn=b where xi is the width of the ith subinterval. -
Calculus Formulas and Theorems
Formulas and Theorems for Reference I. Tbigonometric Formulas l. sin2d+c,cis2d:1 sec2d l*cot20:<:sc:20 +.I sin(-d) : -sitt0 t,rs(-//) = t r1sl/ : -tallH 7. sin(A* B) :sitrAcosB*silBcosA 8. : siri A cos B - siu B <:os,;l 9. cos(A+ B) - cos,4cos B - siuA siriB 10. cos(A- B) : cosA cosB + silrA sirrB 11. 2 sirrd t:osd 12. <'os20- coS2(i - siu20 : 2<'os2o - I - 1 - 2sin20 I 13. tan d : <.rft0 (:ost/ I 14. <:ol0 : sirrd tattH 1 15. (:OS I/ 1 16. cscd - ri" 6i /F tl r(. cos[I ^ -el : sitt d \l 18. -01 : COSA 215 216 Formulas and Theorems II. Differentiation Formulas !(r") - trr:"-1 Q,:I' ]tra-fg'+gf' gJ'-,f g' - * (i) ,l' ,I - (tt(.r))9'(.,') ,i;.[tyt.rt) l'' d, \ (sttt rrJ .* ('oqI' .7, tJ, \ . ./ stll lr dr. l('os J { 1a,,,t,:r) - .,' o.t "11'2 1(<,ot.r') - (,.(,2.r' Q:T rl , (sc'c:.r'J: sPl'.r tall 11 ,7, d, - (<:s<t.r,; - (ls(].]'(rot;.r fr("'),t -.'' ,1 - fr(u") o,'ltrc ,l ,, 1 ' tlll ri - (l.t' .f d,^ --: I -iAl'CSllLl'l t!.r' J1 - rz 1(Arcsi' r) : oT Il12 Formulas and Theorems 2I7 III. Integration Formulas 1. ,f "or:artC 2. [\0,-trrlrl *(' .t "r 3. [,' ,t.,: r^x| (' ,I 4. In' a,,: lL , ,' .l 111Q 5. In., a.r: .rhr.r' .r r (' ,l f 6. sirr.r d.r' - ( os.r'-t C ./ 7. /.,,.r' dr : sitr.i'| (' .t 8. tl:r:hr sec,rl+ C or ln Jccrsrl+ C ,f'r^rr f 9. -
Second Order Linear Differential Equations Y
Second Order Linear Differential Equations Second order linear equations with constant coefficients; Fundamental solutions; Wronskian; Existence and Uniqueness of solutions; the characteristic equation; solutions of homogeneous linear equations; reduction of order; Euler equations In this chapter we will study ordinary differential equations of the standard form below, known as the second order linear equations : y″ + p(t) y′ + q(t) y = g(t). Homogeneous Equations : If g(t) = 0, then the equation above becomes y″ + p(t) y′ + q(t) y = 0. It is called a homogeneous equation. Otherwise, the equation is nonhomogeneous (or inhomogeneous ). Trivial Solution : For the homogeneous equation above, note that the function y(t) = 0 always satisfies the given equation, regardless what p(t) and q(t) are. This constant zero solution is called the trivial solution of such an equation. © 2008, 2016 Zachary S Tseng B-1 - 1 Second Order Linear Homogeneous Differential Equations with Constant Coefficients For the most part, we will only learn how to solve second order linear equation with constant coefficients (that is, when p(t) and q(t) are constants). Since a homogeneous equation is easier to solve compares to its nonhomogeneous counterpart, we start with second order linear homogeneous equations that contain constant coefficients only: a y″ + b y′ + c y = 0. Where a, b, and c are constants, a ≠ 0. A very simple instance of such type of equations is y″ − y = 0 . The equation’s solution is any function satisfying the equality t y″ = y. Obviously y1 = e is a solution, and so is any constant multiple t −t of it, C1 e . -
5 Mar 2009 a Survey on the Inverse Integrating Factor
A survey on the inverse integrating factor.∗ Isaac A. Garc´ıa (1) & Maite Grau (1) Abstract The relation between limit cycles of planar differential systems and the inverse integrating factor was first shown in an article of Giacomini, Llibre and Viano appeared in 1996. From that moment on, many research articles are devoted to the study of the properties of the inverse integrating factor and its relation with limit cycles and their bifurcations. This paper is a summary of all the results about this topic. We include a list of references together with the corresponding related results aiming at being as much exhaustive as possible. The paper is, nonetheless, self-contained in such a way that all the main results on the inverse integrating factor are stated and a complete overview of the subject is given. Each section contains a different issue to which the inverse integrating factor plays a role: the integrability problem, relation with Lie symmetries, the center problem, vanishing set of an inverse integrating factor, bifurcation of limit cycles from either a period annulus or from a monodromic ω-limit set and some generalizations. 2000 AMS Subject Classification: 34C07, 37G15, 34-02. Key words and phrases: inverse integrating factor, bifurcation, Poincar´emap, limit cycle, Lie symmetry, integrability, monodromic graphic. arXiv:0903.0941v1 [math.DS] 5 Mar 2009 1 The Euler integrating factor The method of integrating factors is, in principle, a means for solving ordinary differential equations of first order and it is theoretically important. The use of integrating factors goes back to Leonhard Euler. Let us consider a first order differential equation and write the equation in the Pfaffian form ω = P (x, y) dy Q(x, y) dx =0 . -
Handbook of Mathematics, Physics and Astronomy Data
Handbook of Mathematics, Physics and Astronomy Data School of Chemical and Physical Sciences c 2017 Contents 1 Reference Data 1 1.1 PhysicalConstants ............................... .... 2 1.2 AstrophysicalQuantities. ....... 3 1.3 PeriodicTable ................................... 4 1.4 ElectronConfigurationsoftheElements . ......... 5 1.5 GreekAlphabetandSIPrefixes. ..... 6 2 Mathematics 7 2.1 MathematicalConstantsandNotation . ........ 8 2.2 Algebra ......................................... 9 2.3 TrigonometricalIdentities . ........ 10 2.4 HyperbolicFunctions. ..... 12 2.5 Differentiation .................................. 13 2.6 StandardDerivatives. ..... 14 2.7 Integration ..................................... 15 2.8 StandardIndefiniteIntegrals . ....... 16 2.9 DefiniteIntegrals ................................ 18 2.10 CurvilinearCoordinateSystems. ......... 19 2.11 VectorsandVectorAlgebra . ...... 22 2.12ComplexNumbers ................................. 25 2.13Series ......................................... 27 2.14 OrdinaryDifferentialEquations . ......... 30 2.15 PartialDifferentiation . ....... 33 2.16 PartialDifferentialEquations . ......... 35 2.17 DeterminantsandMatrices . ...... 36 2.18VectorCalculus................................. 39 2.19FourierSeries .................................. 42 2.20Statistics ..................................... 45 3 Selected Physics Formulae 47 3.1 EquationsofElectromagnetism . ....... 48 3.2 Equations of Relativistic Kinematics and Mechanics . ............. 49 3.3 Thermodynamics and Statistical Physics -
13.1 Antiderivatives and Indefinite Integrals
ANTIDERIVATIVES Definition: reverse operation of finding a derivative Notice that F is called AN antiderivative and not THE antiderivative. This is easily understood by looking at the example above. Some antiderivatives of 푓 푥 = 4푥3 are 퐹 푥 = 푥4, 퐹 푥 = 푥4 + 2, 퐹 푥 = 푥4 − 52 Because in each case 푑 퐹(푥) = 4푥3 푑푥 Theorem 1: If a function has more than one antiderivative, then the antiderivatives differ by a constant. • The graphs of antiderivatives are vertical translations of each other. • For example: 푓(푥) = 2푥 Find several functions that are the antiderivatives for 푓(푥) Answer: 푥2, 푥2 + 1, 푥2 + 3, 푥2 − 2, 푥2 + 푐 (푐 푖푠 푎푛푦 푟푒푎푙 푛푢푚푏푒푟) INDEFINITE INTEGRALS Let f (x) be a function. The family of all functions that are antiderivatives of f (x) is called the indefinite integral and has the symbol f (x) dx The symbol is called an integral sign, The function 푓 (푥) is called the integrand. The symbol 푑푥 indicates that anti-differentiation is performed with respect to the variable 푥. By the previous theorem, if 퐹(푥) is any antiderivative of 푓, then f (x) dx F(x) C The arbitrary constant C is called the constant of integration. Indefinite Integral Formulas and Properties Vocabulary: The indefinite integral of a function 푓(푥) is the family of all functions that are antiderivatives of 푓 (푥). It is a function 퐹(푥) whose derivative is 푓(푥). The definite integral of 푓(푥) between two limits 푎 and 푏 is the area under the curve from 푥 = 푎 to 푥 = 푏. -
Antiderivatives Math 121 Calculus II D Joyce, Spring 2013
Antiderivatives Math 121 Calculus II D Joyce, Spring 2013 Antiderivatives and the constant of integration. We'll start out this semester talking about antiderivatives. If the derivative of a function F isf, that is, F 0 = f, then we say F is an antiderivative of f. Of course, antiderivatives are important in solving problems when you know a derivative but not the function, but we'll soon see that lots of questions involving areas, volumes, and other things also come down to finding antiderivatives. That connection we'll see soon when we study the Fundamental Theorem of Calculus (FTC). For now, we'll just stick to the basic concept of antiderivatives. We can find antiderivatives of polynomials pretty easily. Suppose that we want to find an antiderivative F (x) of the polynomial f(x) = 4x3 + 5x2 − 3x + 8: We can find one by finding an antiderivative of each term and adding the results together. Since the derivative of x4 is 4x3, therefore an antiderivative of 4x3 is x4. It's not much harder to find an antiderivative of 5x2. Since the derivative of x3 is 3x2, an antiderivative of 5x2 is 5 3 3 x . Continue on and soon you see that an antiderivative of f(x) is 4 5 3 3 2 F (x) = x + 3 x − 2 x + 8x: There are, however, other antiderivatives of f(x). Since the derivative of a constant is 0, 4 5 3 3 2 we can add any constant to F (x) to find another antiderivative. Thus, x + 3 x − 2 x +8x+7 4 5 3 3 2 is another antiderivative of f(x). -
FIRST-ORDER ORDINARY DIFFERENTIAL EQUATIONS III: Numerical and More Analytic Methods
FIRST-ORDER ORDINARY DIFFERENTIAL EQUATIONS III: Numerical and More Analytic Methods David Levermore Department of Mathematics University of Maryland 30 September 2012 Because the presentation of this material in lecture will differ from that in the book, I felt that notes that closely follow the lecture presentation might be appreciated. Contents 8. First-Order Equations: Numerical Methods 8.1. Numerical Approximations 2 8.2. Explicit and Implicit Euler Methods 3 8.3. Explicit One-Step Methods Based on Taylor Approximation 4 8.3.1. Explicit Euler Method Revisited 4 8.3.2. Local and Global Errors 4 8.3.3. Higher-Order Taylor-Based Methods (not covered) 5 8.4. Explicit One-Step Methods Based on Quadrature 6 8.4.1. Explicit Euler Method Revisited Again 6 8.4.2. Runge-Trapezoidal Method 7 8.4.3. Runge-Midpoint Method 9 8.4.4. Runge-Kutta Method 10 8.4.5. General Runge-Kutta Methods (not covered) 12 9. Exact Differential Forms and Integrating Factors 9.1. Implicit General Solutions 15 9.2. Exact Differential Forms 16 9.3. Integrating Factors 20 10. Special First-Order Equations and Substitution 10.1. Linear Argument Equations (not covered) 25 10.2. Dilation Invariant Equations (not covered) 26 10.3. Bernoulli Equations (not covered) 27 10.4. Substitution (not covered) 29 1 2 8. First-Order Equations: Numerical Methods 8.1. Numerical Approximations. Analytic methods are either difficult or impossible to apply to many first-order differential equations. In such cases direction fields might be the only graphical method that we have covered that can be applied. -
Appendix: TABLE of INTEGRALS
-~.I-- Appendix: TABLE OF INTEGRALS 148. In the following table, the constant of integration, C, is omitted but should be added to the result of every integration. The letter x represents any variable; u represents any function of x; the remaining letters represent arbitrary constants, unless otherwise indicated; all angles are in radians. Unless otherwise mentioned, loge u = log u. Expressions Containing ax + b 1. I(ax+ b)ndx= 1 (ax+ b)n+l, n=l=-1. a(n + 1) dx 1 2. = -loge<ax + b). Iax+ b a 3 I dx =_ 1 • (ax+b)2 a(ax+b)· 4 I dx =_ 1 • (ax + b)3 2a(ax + b)2· 5. Ix(ax + b)n dx = 1 (ax + b)n+2 a2 (n + 2) b ---,,---(ax + b)n+l n =1= -1, -2. a2 (n + 1) , xdx x b 6. = - - -2 log(ax + b). I ax+ b a a 7 I xdx = b 1 I ( b) • (ax + b)2 a2(ax + b) + -;}i og ax + . 369 370 • Appendix: Table of Integrals 8 I xdx = b _ 1 • (ax + b)3 2a2(ax + b)2 a2(ax + b) . 1 (ax+ b)n+3 (ax+ b)n+2 9. x2(ax + b)n dx = - - 2b--'------'-- I a2 n + 3 n + 2 2 b (ax + b) n+ 1 ) + , ni=-I,-2,-3. n+l 2 10. I x dx = ~ (.!..(ax + b)2 - 2b(ax + b) + b2 10g(ax + b)). ax+ b a 2 2 2 11. I x dx 2 =~(ax+ b) - 2blog(ax+ b) _ b ). (ax + b) a ax + b 2 2 12 I x dx = _1(10 (ax + b) + 2b _ b ) • (ax + b) 3 a3 g ax + b 2(ax + b) 2 .