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Informal Lecture Notes for Complex Analysis
Informal lecture notes for complex analysis Robert Neel I'll assume you're familiar with the review of complex numbers and their algebra as contained in Appendix G of Stewart's book, so we'll pick up where that leaves off. 1 Elementary complex functions In one-variable real calculus, we have a collection of basic functions, like poly- nomials, rational functions, the exponential and log functions, and the trig functions, which we understand well and which serve as the building blocks for more general functions. The same is true in one complex variable; in fact, the real functions we just listed can be extended to complex functions. 1.1 Polynomials and rational functions We start with polynomials and rational functions. We know how to multiply and add complex numbers, and thus we understand polynomial functions. To be specific, a degree n polynomial, for some non-negative integer n, is a function of the form n n−1 f(z) = cnz + cn−1z + ··· + c1z + c0; 3 where the ci are complex numbers with cn 6= 0. For example, f(z) = 2z + (1 − i)z + 2i is a degree three (complex) polynomial. Polynomials are clearly defined on all of C. A rational function is the quotient of two polynomials, and it is defined everywhere where the denominator is non-zero. z2+1 Example: The function f(z) = z2−1 is a rational function. The denomina- tor will be zero precisely when z2 = 1. We know that every non-zero complex number has n distinct nth roots, and thus there will be two points at which the denominator is zero. -
Bounded Holomorphic Functions on Finite Riemann Surfaces
BOUNDED HOLOMORPHIC FUNCTIONS ON FINITE RIEMANN SURFACES BY E. L. STOUT(i) 1. Introduction. This paper is devoted to the study of some problems concerning bounded holomorphic functions on finite Riemann surfaces. Our work has its origin in a pair of theorems due to Lennart Carleson. The first of the theorems of Carleson we shall be concerned with is the following [7] : Theorem 1.1. Let fy,---,f„ be bounded holomorphic functions on U, the open unit disc, such that \fy(z) + — + \f„(z) | su <5> 0 holds for some ô and all z in U. Then there exist bounded holomorphic function gy,---,g„ on U such that ftEi + - +/A-1. In §2, we use this theorem to establish an analogous result in the setting of finite open Riemann surfaces. §§3 and 4 consider certain questions which arise naturally in the course of the proof of this generalization. We mention that the chief result of §2, Theorem 2.6, has been obtained independently by N. L. Ailing [3] who has used methods more highly algebraic than ours. The second matter we shall be concerned with is that of interpolation. If R is a Riemann surface and if £ is a subset of R, call £ an interpolation set for R if for every bounded complex-valued function a on £, there is a bounded holo- morphic function f on R such that /1 £ = a. Carleson [6] has characterized interpolation sets in the unit disc: Theorem 1.2. The set {zt}™=1of points in U is an interpolation set for U if and only if there exists ô > 0 such that for all n ** n00 k = l;ktn 1 — Z.Zl An alternative proof is to be found in [12, p. -
Complex-Differentiability
Complex-Differentiability Sébastien Boisgérault, Mines ParisTech, under CC BY-NC-SA 4.0 April 25, 2017 Contents Core Definitions 1 Derivative and Complex-Differential 3 Calculus 5 Cauchy-Riemann Equations 7 Appendix – Terminology and Notation 10 References 11 Core Definitions Definition – Complex-Differentiability & Derivative. Let f : A ⊂ C → C. The function f is complex-differentiable at an interior point z of A if the derivative of f at z, defined as the limit of the difference quotient f(z + h) − f(z) f 0(z) = lim h→0 h exists in C. Remark – Why Interior Points? The point z is an interior point of A if ∃ r > 0, ∀ h ∈ C, |h| < r → z + h ∈ A. In the definition above, this assumption ensures that f(z + h) – and therefore the difference quotient – are well defined when |h| is (nonzero and) small enough. Therefore, the derivative of f at z is defined as the limit in “all directions at once” of the difference quotient of f at z. To question the existence of the derivative of f : A ⊂ C → C at every point of its domain, we therefore require that every point of A is an interior point, or in other words, that A is open. 1 Definition – Holomorphic Function. Let Ω be an open subset of C. A function f :Ω → C is complex-differentiable – or holomorphic – in Ω if it is complex-differentiable at every point z ∈ Ω. If additionally Ω = C, the function is entire. Examples – Elementary Functions. 1. Every constant function f : z ∈ C 7→ λ ∈ C is holomorphic as 0 λ − λ ∀ z ∈ C, f (z) = lim = 0. -
Complex Manifolds
Complex Manifolds Lecture notes based on the course by Lambertus van Geemen A.A. 2012/2013 Author: Michele Ferrari. For any improvement suggestion, please email me at: [email protected] Contents n 1 Some preliminaries about C 3 2 Basic theory of complex manifolds 6 2.1 Complex charts and atlases . 6 2.2 Holomorphic functions . 8 2.3 The complex tangent space and cotangent space . 10 2.4 Differential forms . 12 2.5 Complex submanifolds . 14 n 2.6 Submanifolds of P ............................... 16 2.6.1 Complete intersections . 18 2 3 The Weierstrass }-function; complex tori and cubics in P 21 3.1 Complex tori . 21 3.2 Elliptic functions . 22 3.3 The Weierstrass }-function . 24 3.4 Tori and cubic curves . 26 3.4.1 Addition law on cubic curves . 28 3.4.2 Isomorphisms between tori . 30 2 Chapter 1 n Some preliminaries about C We assume that the reader has some familiarity with the notion of a holomorphic function in one complex variable. We extend that notion with the following n n Definition 1.1. Let f : C ! C, U ⊆ C open with a 2 U, and let z = (z1; : : : ; zn) be n the coordinates in C . f is holomorphic in a = (a1; : : : ; an) 2 U if f has a convergent power series expansion: +1 X k1 kn f(z) = ak1;:::;kn (z1 − a1) ··· (zn − an) k1;:::;kn=0 This means, in particular, that f is holomorphic in each variable. Moreover, we define OCn (U) := ff : U ! C j f is holomorphicg m A map F = (F1;:::;Fm): U ! C is holomorphic if each Fj is holomorphic. -
Why Wirtinger Derivatives Behave So Well
Why Wirtinger derivatives behave so well Bart Michels∗ April 14, 2019 Contents 1 Introduction 2 2 Partial derivatives revisited 2 3 Complexification 3 3.1 Complexified differentials: two variables . .4 3.2 Complexified differentials: multiple variables . .4 3.3 Conjugation . .5 4 Chain rule 7 5 Holomorphic functions 10 6 Power series 11 7 Concluding remarks 12 ∗Universit´eParis 13, LAGA, CNRS, UMR 7539, F-93430, Villetaneuse, France. Email: [email protected] 1 1 Introduction Given a smooth function f : C ! C, it makes a priori no sense to talk about @f @f the Wirtinger derivatives and . We could define them by @z @z¯ @f 1 @f @f = − i @z 2 @x @y (1) @f 1 @f @f = + i @z¯ 2 @x @y but that does not explain why we denote them like partial derivatives, where the confusing sign convention comes from, why they behave like partial derivatives, and why they act on power series in z and z in the way they should. Here follows a construction of Wirtinger derivatives that avoids the explicit formula (1). The reader may be interested in the definitions in section 3, in the sanity check in Proposition 3.2, the chain rule from Proposition 4.3 and the results from section 6. 2 Partial derivatives revisited It is worthwhile to take a second look at what a partial derivative is. Con- sider finite-dimensional real vector spaces V and W .1 They carry a canonical smooth structure. Consider a differentiable function f : V ! W . At every point p 2 V , f has a differential Dpf : V ! W , an R-linear map. -
Wirtinger Kalman Overdrive
Wirtinger Kalman Overdrive O. Smirnov (Rhodes & SKA SA) C. Tasse (Obs. Paris Meudon & Rhodes) The 3GC Culture Wars Two approaches to dealing with DD effects The “NRAO School”: Represent everything by the A-term Correct during imaging (convolutional gridding) Solve for pointing offsets Sky models are images The “ASTRON School”: Solve for DD gains towards (clusters of) sources Make component sky models, subtract sources in uv-plane while accounting for DD gains O. Smirnov & C. Tasse - Wirtinger Kalman Overdrive - SPARCS 2015 2 Why DD Gains Cons: non-physical, slow & expensive But, DD+MeqTrees have consistently delivered the goods with all major pathfinders Early LOFAR maps and LOFAR EoR (S. Yatawatta) Beautiful ASKAP/BETA maps (I. Heywood) JVLA 5M+ DR (M. Mitra earlier) Fair bet that we'll still be using them come MeerKAT and SKA O. Smirnov & C. Tasse - Wirtinger Kalman Overdrive - SPARCS 2015 3 DD Gains Are Like Whiskey The smoother the better Make everything look more attractive If you overindulge, you wake in in the morning wondering where your {polarized foregrounds, weak sources, science signal} have gotten to differential source gain & bandpass gain beam coherency (s) (s) (s)H (s)H H Vpq= G⏞p ∑ ⏞Δ Ep E⏞p ⏞Xpq Eq Δ Eq Gq ⏟( s ) sum over sources O. Smirnov & C. Tasse - Wirtinger Kalman Overdrive - SPARCS 2015 4 The One True Way O. Smirnov & C. Tasse - Wirtinger Kalman Overdrive - SPARCS 2015 5 The Middle Way DR limited by how well we can subtract the brighter source population thus bigger problem for small dish/WF Subtract the first two-three orders of magnitude in the uv-plane good source modelling and (deconvolution and/or Bayesian) PB models, pointing solutions, +solvable DD gains Image and deconvolve the rest really well A-term and/or faceting O. -
Introduction to Holomorphic Functions of Several Variables, by Robert C
BOOK REVIEWS 205 BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY Volume 25, Number 1, July 1991 ©1991 American Mathematical Society 0273-0979/91 $1.00+ $.25 per page Introduction to holomorphic functions of several variables, by Robert C. Gunning. Wadsworth & Brooks/Cole, vol. 1, Function the ory, 202 pp. ISBN 0-534-13308-8; vol. 2, Local theory, 215 pp. ISBN 0-534-13309-6; vol. 3, Homological theory, 194 pp. ISBN 0-534-13310-X What is several complex variables? The answer depends on whom you ask. Some will speak of coherent analytic sheaves, commutative al gebra, and Cousin problems (see for instance [GRR1, GRR2]). Some will speak of Kàhler manifolds and uniformization—how many topologically trivial complex manifolds are there of strictly negative (bounded from zero) curvature (see [KOW])? (In one complex variable the important answer is one,) Some will speak of positive line bundles (see [GRA]). Some will speak of partial differential equations, subelliptic es timates, and noncoercive boundary value problems (see [FOK]). Some will speak of intersection theory, orders of contact of va rieties with real manifolds, and algebraic geometry (see [JPDA]). Some will speak of geometric function theory (see [KRA]). Some will speak of integral operators and harmonic analysis (see [STE1, STE2, KRA]). Some will speak of questions of hard analysis inspired by results in one complex variable (see [RUD1, RUD2]). As with any lively and diverse field, there are many points of view, and many different tools that may be used to obtain useful results. Several complex variables, perhaps more than most fields, seems to be a meeting ground for an especially rich array of tech niques. -
Lecture Note for Math 220A Complex Analysis of One Variable
Lecture Note for Math 220A Complex Analysis of One Variable Song-Ying Li University of California, Irvine Contents 1 Complex numbers and geometry 2 1.1 Complex number field . 2 1.2 Geometry of the complex numbers . 3 1.2.1 Euler's Formula . 3 1.3 Holomorphic linear factional maps . 6 1.3.1 Self-maps of unit circle and the unit disc. 6 1.3.2 Maps from line to circle and upper half plane to disc. 7 2 Smooth functions on domains in C 8 2.1 Notation and definitions . 8 2.2 Polynomial of degree n ...................... 9 2.3 Rules of differentiations . 11 3 Holomorphic, harmonic functions 14 3.1 Holomorphic functions and C-R equations . 14 3.2 Harmonic functions . 15 3.3 Translation formula for Laplacian . 17 4 Line integral and cohomology group 18 4.1 Line integrals . 18 4.2 Cohomology group . 19 4.3 Harmonic conjugate . 21 1 5 Complex line integrals 23 5.1 Definition and examples . 23 5.2 Green's theorem for complex line integral . 25 6 Complex differentiation 26 6.1 Definition of complex differentiation . 26 6.2 Properties of complex derivatives . 26 6.3 Complex anti-derivative . 27 7 Cauchy's theorem and Morera's theorem 31 7.1 Cauchy's theorems . 31 7.2 Morera's theorem . 33 8 Cauchy integral formula 34 8.1 Integral formula for C1 and holomorphic functions . 34 8.2 Examples of evaluating line integrals . 35 8.3 Cauchy integral for kth derivative f (k)(z) . 36 9 Application of the Cauchy integral formula 36 9.1 Mean value properties . -
1 Holomorphic Functions
MM Vercelli. L2: Holomorphic and analytic functions. Contents: ² Holomorphic functions. ² Cauchy-Riemann conditions. ² Complex di®erentials and complex partial derivatives. ² Analytic functions. ² The exponential function. 1 Holomorphic functions A complex function f(x; y) = u(x; y) + i v(x; y) can be also regarded as a function of z = x + i y and its conjugated z because we can write z + z z ¡ z z + z z ¡ z z + z z ¡ z f( ; ) = u( ; ) + i v( ; ) 2 2 i 2 2 i 2 2 i Classically a holomorphic function f was de¯ned as a function f such that the expres- z+z z¡z z+z z¡z sion u( 2 ; 2 i )+i v( 2 ; 2 i ) does not contain, after simpli¯cation, the letter z or what is the same f does not depend upon z. It is standard to denote O(D) the set of holomorphic functions on D. From calculus we know that a given function f do not depends on a variable, say w @f if the partial derivative @w is identically zero. So a simpler way of saying that a function f does not depend on z is as follows: @f = 0 (1) @z The problem is that we have no de¯nition of the partial derivative with respect to z. n n¡1 Example 1.1. Any polynomial f(z) = anz + an¡1z + ¢ ¢ ¢ + a0 gives an holomorphic P1 k function. Moreover, a convergent power series f(z) = k=0 ckz gives a holomorphic function in his disc of convergence. The function f(x; y) = x2 + y2 is not holomorphic. -
Math 372: Fall 2015: Solutions to Homework
Math 372: Fall 2015: Solutions to Homework Steven Miller December 7, 2015 Abstract Below are detailed solutions to the homeworkproblemsfrom Math 372 Complex Analysis (Williams College, Fall 2015, Professor Steven J. Miller, [email protected]). The course homepage is http://www.williams.edu/Mathematics/sjmiller/public_html/372Fa15 and the textbook is Complex Analysis by Stein and Shakarchi (ISBN13: 978-0-691-11385-2). Note to students: it’s nice to include the statement of the problems, but I leave that up to you. I am only skimming the solutions. I will occasionally add some comments or mention alternate solutions. If you find an error in these notes, let me know for extra credit. Contents 1 Math 372: Homework #1: Yuzhong (Jeff) Meng and Liyang Zhang (2010) 3 1.1 Problems for HW#1: Due September 21, 2015 . ................ 3 1.2 SolutionsforHW#1: ............................... ........... 3 2 Math 372: Homework #2: Solutions by Nick Arnosti and Thomas Crawford (2010) 8 3 Math 372: Homework #3: Carlos Dominguez, Carson Eisenach, David Gold 12 4 Math 372: Homework #4: Due Friday, October 12, 2015: Pham, Jensen, Kolo˘glu 16 4.1 Chapter3,Exercise1 .............................. ............ 16 4.2 Chapter3,Exercise2 .............................. ............ 17 4.3 Chapter3,Exercise5 .............................. ............ 19 4.4 Chapter3Exercise15d ..... ..... ...... ..... ...... .. ............ 22 4.5 Chapter3Exercise17a ..... ..... ...... ..... ...... .. ............ 22 4.6 AdditionalProblem1 .............................. ............ 22 5 Math 372: Homework #5: Due Monday October 26: Pegado, Vu 24 6 Math 372: Homework #6: Kung, Lin, Waters 34 7 Math 372: Homework #7: Due Monday, November 9: Thompson, Schrock, Tosteson 42 7.1 Problems. ....................................... ......... 46 1 8 Math 372: Homework #8: Thompson, Schrock, Tosteson 47 8.1 Problems. -
Zeroes of Holomorphic Functions
LECTURE-19 : ZEROES OF HOLOMORPHIC FUNCTIONS VED V. DATAR∗ A complex number a is called a zero of a holomorphic function f :Ω ! C if f(a) = 0. A basic fact is that zeroes of holomorphic functions are isolated. This follows from the following theorem. Theorem 0.1. Let f :Ω ! C be a holomorphic function that is not identi- cally zero, and let a 2 Ω be a zero of f. Then there exists a disc D around a, a non vanishing holomorphic function g : D ! C (that is, g(z) 6= 0 for all z 2 D), and a unique positive integer n such that f(z) = (z − a)ng(z): The positive integer n is called the order of the zero at a. The main tool that we need in order to prove this is the strong principle of analytic continuation. Lemma 0.1. Let Ω ⊂ C be a connected domain, and f be holomorphic on Ω. If there is a p 2 Ω such that f k(p) = 0 for all k = 0; 1; 2 ··· , then f(z) = 0 for all z 2 Ω. Proof. Let E ⊂ Ω defined by E = fz 2 Ω j f (n)(z) = 0; 8 n = 0; 1; 2; · · · g: Then by hypothesis p 2 E, and hence E is non-empty. It is enough to show that E = Ω. The proof is completed by proving three claims. Claim 1. E is an open subset. To see this, let a 2 E. Since Ω is open, there exists a disc D"(a) such that D"(a) ⊂ Ω. -
Blind Demixing Via Wirtinger Flow with Random Initialization
Blind Demixing via Wirtinger Flow with Random Initialization Jialin Dong Yuanming Shi [email protected] [email protected] ShanghaiTech University ShanghaiTech University Abstract i = 1; ··· ; s, i.e., s This paper concerns the problem of demixing X \ \ a series of source signals from the sum of bi- yj = bj∗hixi∗aij; 1 ≤ j ≤ m; (1) linear measurements. This problem spans di- i=1 verse areas such as communication, imaging N K processing, machine learning, etc. However, where faijg 2 C , fbjg 2 C are design vectors. semidefinite programming for blind demixing Here, the first K columns of the matrix F form the ma- m K m m is prohibitive to large-scale problems due to trix B := [b1; ··· ; bm]∗ 2 C × , where F 2 C × high computational complexity and storage is the unitary discrete Fourier transform (DFT) ma- cost. Although several efficient algorithms \ trix with FF ∗ = Im. Our goal is to recover fxig and have been developed recently that enjoy the \ fhig from the sum of bilinear measurements, which is benefits of fast convergence rates and even known as blind demixing [1, 2]. regularization free, they still call for spec- tral initialization. To find simple initial- This problem has spanned a wide scope of applications ization approach that works equally well as ranging from imaging processing [3, 4] and machine spectral initialization, we propose to solve learning [5, 6] to communication [7, 8]. Specifically, blind demixing problem via Wirtinger flow by solving the blind demixing problem, both original with random initialization, which yields a images and corresponding convolutional kernels can be natural implementation.