Advanced Complex Analysis

Total Page:16

File Type:pdf, Size:1020Kb

Advanced Complex Analysis Advanced Complex Analysis Course Notes | Harvard University | Math 213a C. McMullen January 8, 2021 Contents 1 Basic complex analysis . 2 2 The simply-connected Riemann surfaces . 39 3 Entire and meromorphic functions . 59 4 Conformal mapping . 81 5 Elliptic functions and elliptic curves . 109 Forward Complex analysis is a nexus for many mathematical fields, including: 1. Algebra (theory of fields and equations); 2. Algebraic geometry and complex manifolds; 3. Geometry (Platonic solids; flat tori; hyperbolic manifolds of dimen- sions two and three); 4. Lie groups, discrete subgroups and homogeneous spaces (e.g. H= SL2(Z); 5. Dynamics (iterated rational maps); 6. Number theory and automorphic forms (elliptic functions, zeta func- tions); 7. Theory of Riemann surfaces (Teichm¨ullertheory, curves and their Ja- cobians); 8. Several complex variables and complex manifolds; 9. Real analysis and PDE (harmonic functions, elliptic equations and distributions). This course covers some basic material on both the geometric and analytic aspects of complex analysis in one variable. Prerequisites: Background in real analysis and basic differential topology (such as covering spaces and differential forms), and a first course in complex analysis. Exercises (These exercises are review.) 3 2 2 2 1. Let T ⊂ R be the spherical triangle defined by x + y + z = 1 and x; y; z ≥ 0. Let α = z dx dz. 3 (a) Find a smooth 1-form β on R such that α = dβ. (b) Define consistent orientations for T and @T . R R (c) Using your choices in (ii), compute T α and @T β directly, and check that they agree. (Why should they agree?) 1 2. Let f(z) = (az + b)=(cz + d) be a M¨obius transformation. Show the number of rational maps g : Cb ! Cb such that g(g(g(g(g(z))))) = f(z) is 1, 5 or 1. Explain how to determine which alternative holds for a given f. P n 3. Let anz be the Taylor series for tanh(z) at z = 0. (a) What is the radius of convergence of this power series? (b) Show that a5 = 2=15. PN (c) Give an explicit value of N such that tanh(1) and 0 an agree to 1000 decimal places. Justify your answer. 4. Let f : U ! V be a proper local homeomorphism between a pair of open sets U; V ⊂ C. Prove that f is a covering map. (Here proper means that f −1(K) is compact whenever K ⊂ V is compact.) 5. Let f : C ! C be given by a polynomial of degree 2 or more. Let 0 V1 = ff(z): f (z) = 0g ⊂ C −1 be the set of critical values of f, let V0 = f (V1), and let Ui = C − Vi for i = 0; 1. Prove that f : U0 ! U1 is a covering map. 6. Give an example where U0=U1 is a normal (or Galois) covering, i.e. where f∗(π1(U0)) is a normal subgroup of π1(U1). 1 Basic complex analysis We begin with an overview of basic facts about the complex plane and analytic functions. Some notation. The complex numbers will be denoted C. We let ∆; H and Cb denote the unit disk jzj < 1, the upper half plane Im(z) > 0, and the 1 1 Riemann sphere C [ f1g. We write S (r) for the circle jzj = r, and S for the unit circle, each oriented counter-clockwise. We also set ∆∗ = ∆ − f0g ∗ and C = C − f0g. 2 1.1 Algebraic and analytic functions The complex numbers are formally defined as the field C = R[i], where i2 = −1. They are represented in the Euclidean plane by z = (x; y) = x+iy. There are two square-roots of −1 in C; the number i is the one with positive imaginary part. An important role is played by the Galois involution z 7! z. We define 2 2 2 jzj = N(z) =pzz = x + y . (Compare the case of a real quadratic field, where N(a + b d) = a2 − db2 gives an indefinite form.) Compatibility of jzj 2 with the Euclidean metric justifies the identification of C and R . We also see that z is a field: 1=z = z=jzj. It is also convenient to describe complex numbers by polar coordinates z = [r; θ] = r(cos θ + i sin θ): Here r = jzj and θ = arg z 2 R=2πZ. (The multivaluedness of arg z requires care but is also the ultimate source of powerful results such as Cauchy's integral formula.) We then have [r1; θ1][r2; θ2] = [r1r2; θ1 + θ2]: In particular, the linear maps f(z) = az + b, a 6= 0, of C to itself, preserve angles and orientations. This formula should be proved geometrically: in fact, it is a consequence of the formula jabj = jajjbj and properties of similar triangles. It can then be used to derive the addition formulas for sine and cosine (in Ahflors the reverse logic is applied). Algebraic closure. A critical feature of the complex numbers is that they are algebraically closed; every polynomial has a root. (A proof will be reviewed below). Classically, the complex numbers were introducing in the course of solv- ing real cubic equations. Staring with x3 + ax + b = 0 one can make a Tschirnhaus transformation so a = 0. This is done by introducing a new 2 P P 2 variable y = cx + d such that yi = yi = 0; even when a and b are real, it may be necessary to choose c complex (the discriminant of the equation for c is 27b2 + 4a3.) It is negative when the cubic has only one real root; this can be checked by looking at the product of the values of the cubic at its max and min. Analytic functions. Let U be an open set in C and f : U ! C a function. We say f is analytic if f(z + t) − f(z) f 0(z) = lim t!0 t 3 exists for all z 2 U. It is crucial here that t approaches zero through arbitrary 1 values in C. Remarkably, this condition implies that f is a smooth (C ) function. For example, polynomials are analytic, as are rational functions away from their poles. Note that any real linear function φ : C ! C has the form φ(v) = av+bv. 0 The condition of analytic says that Dfz(v) = f (z)v; in other words, the v part is absent. 1 To make this point systematically, for a general C function F : U ! C we define dF 1 dF 1 dF dF 1 dF 1 dF = + and = − · dz 2 dx i dy dz 2 dx i dy We then have dF DF DF (v) = v + v: z dz dz We can also write complex-valued 1-form dF as dF dF dF = @F + @F = dz + dz dz dz Thus F is analytic iff @F = 0; these are the Cauchy-Riemann equations. We note that (d=dz)zn = nzn−1; a polynomial p(z; z) behaves as if these variables are independent. Sources of analytic functions. 1. Polynomials and rational functions. Using addition and multipli- Pn n cation we obtain naturally the polynomial functions f(z) = 0 anz : C ! C. The ring of polynomials C[z] is an integral domain and a unique factorization domain, since C is a field. Indeed, since C is algebraically closed, fact every polynomial factors into linear terms. It is useful to add the allowed value 1 to obtain the Riemann sphere Cb = C [ f1g. Then rational functions (ratios f(z) = p(z)=q(z) of rel- atively prime polynomials, with the denominator not identically zero) determine rational maps f : C ! C. The rational functions C(z) are the same as the field of fractions for the domain C[z]. We set f(z) = 1 if q(z) = 0; these points are called the poles of f. 2. Algebraic functions. Beyond the rational and polynomial functions, pthe analytic functions include algebraic functions such that f(z) = 2 PN n z + 1. A general algebraic function f(z) satisfies P (f) = 0 an(z)f(z) = 0 for some rational functions an(z); these arise, at least formally, when 4 one forms algebraic extension of C(z). Such functions are generally multivalued, so we must choose a particular branch to obtain an ana- lytic function. 3. Differential equations. Analytic functions also arise when one solves differential equations. Even equations with constant coefficients, like y00 + y = 0, can give rise to transcendental functions such as sin(z), cos(z) and ez. Here are some useful facts about these familiar functions when extended to C: j exp(z)j = exp Re z cos(iz) = cosh(z) sin(iz) = i sinh(z) cos(x + iy) = cos(x) cosh(y) − i sin(x) sinh(y) sin(x + iy) = sin(x) cosh(y) + i cos(x) sinh(y): In particular, the apparent boundedness of sin(z) and cos(z) fails badly as we move away from the real axis, while jezj is actually very small in the halfplane Re z 0. 4. Integration. A special case of course is integration. While R (x2+ax+ b)−1=2 dx can be given explicitly in terms of trigonometric functions, already R (x3 + ax + b)−1=2 dx leads one into elliptic functions; and higher degree polynomials lead one to hyperelliptic surfaces of higher genus. Note that the `periodicity' of the function in increases from Z 2 1 (trigonometric) to Z (elliptic) to H (Σg; Z) (hyperelliptic). 5. Power series. Analytic functions can be given concretely, locally, by P n power series such as anz . Conversely, suitable coefficients deter- mine analytic functions; for example, ez = P zn=n!.
Recommended publications
  • Avoiding the Undefined by Underspecification
    Avoiding the Undefined by Underspecification David Gries* and Fred B. Schneider** Computer Science Department, Cornell University Ithaca, New York 14853 USA Abstract. We use the appeal of simplicity and an aversion to com- plexity in selecting a method for handling partial functions in logic. We conclude that avoiding the undefined by using underspecification is the preferred choice. 1 Introduction Everything should be made as simple as possible, but not any simpler. --Albert Einstein The first volume of Springer-Verlag's Lecture Notes in Computer Science ap- peared in 1973, almost 22 years ago. The field has learned a lot about computing since then, and in doing so it has leaned on and supported advances in other fields. In this paper, we discuss an aspect of one of these fields that has been explored by computer scientists, handling undefined terms in formal logic. Logicians are concerned mainly with studying logic --not using it. Some computer scientists have discovered, by necessity, that logic is actually a useful tool. Their attempts to use logic have led to new insights --new axiomatizations, new proof formats, new meta-logical notions like relative completeness, and new concerns. We, the authors, are computer scientists whose interests have forced us to become users of formal logic. We use it in our work on language definition and in the formal development of programs. This paper is born of that experience. The operation of a computer is nothing more than uninterpreted symbol ma- nipulation. Bits are moved and altered electronically, without regard for what they denote. It iswe who provide the interpretation, saying that one bit string represents money and another someone's name, or that one transformation rep- resents addition and another alphabetization.
    [Show full text]
  • A Property of the Derivative of an Entire Function
    A property of the derivative of an entire function Walter Bergweiler∗ and Alexandre Eremenko† July 21, 2011 Abstract We prove that the derivative of a non-linear entire function is un- bounded on the preimage of an unbounded set. MSC 2010: 30D30. Keywords: entire function, normal family. 1 Introduction and results The main result of this paper is the following theorem conjectured by Allen Weitsman (private communication): Theorem 1. Let f be a non-linear entire function and M an unbounded set in C. Then f ′(f −1(M)) is unbounded. We note that there exist entire functions f such that f ′(f −1(M)) is bounded for every bounded set M, for example, f(z)= ez or f(z) = cos z. Theorem 1 is a consequence of the following stronger result: Theorem 2. Let f be a transcendental entire function and ε > 0. Then there exists R> 0 such that for every w C satisfying w >R there exists ∈ | | z C with f(z)= w and f ′(z) w 1−ε. ∈ | | ≥ | | ∗Supported by the Deutsche Forschungsgemeinschaft, Be 1508/7-1, and the ESF Net- working Programme HCAA. †Supported by NSF grant DMS-1067886. 1 The example f(z)= √z sin √z shows that that the exponent 1 ε in the − last inequality cannot be replaced by 1. The function f(z) = cos √z has the property that for every w C we have f ′(z) 0 as z , z f −1(w). ∈ → → ∞ ∈ We note that the Wiman–Valiron theory [20, 12, 4] says that there exists a set F [1, ) of finite logarithmic measure such that if ⊂ ∞ zr = r / F and f(zr) = max f(z) , | | ∈ | | |z|=r | | then ν(r,f) z ′ ν(r, f) f(z) f(zr) and f (z) f(z) ∼ zr ∼ r −1/2−δ for z zr rν(r, f) as r .
    [Show full text]
  • Field Theory Pete L. Clark
    Field Theory Pete L. Clark Thanks to Asvin Gothandaraman and David Krumm for pointing out errors in these notes. Contents About These Notes 7 Some Conventions 9 Chapter 1. Introduction to Fields 11 Chapter 2. Some Examples of Fields 13 1. Examples From Undergraduate Mathematics 13 2. Fields of Fractions 14 3. Fields of Functions 17 4. Completion 18 Chapter 3. Field Extensions 23 1. Introduction 23 2. Some Impossible Constructions 26 3. Subfields of Algebraic Numbers 27 4. Distinguished Classes 29 Chapter 4. Normal Extensions 31 1. Algebraically closed fields 31 2. Existence of algebraic closures 32 3. The Magic Mapping Theorem 35 4. Conjugates 36 5. Splitting Fields 37 6. Normal Extensions 37 7. The Extension Theorem 40 8. Isaacs' Theorem 40 Chapter 5. Separable Algebraic Extensions 41 1. Separable Polynomials 41 2. Separable Algebraic Field Extensions 44 3. Purely Inseparable Extensions 46 4. Structural Results on Algebraic Extensions 47 Chapter 6. Norms, Traces and Discriminants 51 1. Dedekind's Lemma on Linear Independence of Characters 51 2. The Characteristic Polynomial, the Trace and the Norm 51 3. The Trace Form and the Discriminant 54 Chapter 7. The Primitive Element Theorem 57 1. The Alon-Tarsi Lemma 57 2. The Primitive Element Theorem and its Corollary 57 3 4 CONTENTS Chapter 8. Galois Extensions 61 1. Introduction 61 2. Finite Galois Extensions 63 3. An Abstract Galois Correspondence 65 4. The Finite Galois Correspondence 68 5. The Normal Basis Theorem 70 6. Hilbert's Theorem 90 72 7. Infinite Algebraic Galois Theory 74 8. A Characterization of Normal Extensions 75 Chapter 9.
    [Show full text]
  • Topic 7 Notes 7 Taylor and Laurent Series
    Topic 7 Notes Jeremy Orloff 7 Taylor and Laurent series 7.1 Introduction We originally defined an analytic function as one where the derivative, defined as a limit of ratios, existed. We went on to prove Cauchy's theorem and Cauchy's integral formula. These revealed some deep properties of analytic functions, e.g. the existence of derivatives of all orders. Our goal in this topic is to express analytic functions as infinite power series. This will lead us to Taylor series. When a complex function has an isolated singularity at a point we will replace Taylor series by Laurent series. Not surprisingly we will derive these series from Cauchy's integral formula. Although we come to power series representations after exploring other properties of analytic functions, they will be one of our main tools in understanding and computing with analytic functions. 7.2 Geometric series Having a detailed understanding of geometric series will enable us to use Cauchy's integral formula to understand power series representations of analytic functions. We start with the definition: Definition. A finite geometric series has one of the following (all equivalent) forms. 2 3 n Sn = a(1 + r + r + r + ::: + r ) = a + ar + ar2 + ar3 + ::: + arn n X = arj j=0 n X = a rj j=0 The number r is called the ratio of the geometric series because it is the ratio of consecutive terms of the series. Theorem. The sum of a finite geometric series is given by a(1 − rn+1) S = a(1 + r + r2 + r3 + ::: + rn) = : (1) n 1 − r Proof.
    [Show full text]
  • A Quick Algebra Review
    A Quick Algebra Review 1. Simplifying Expressions 2. Solving Equations 3. Problem Solving 4. Inequalities 5. Absolute Values 6. Linear Equations 7. Systems of Equations 8. Laws of Exponents 9. Quadratics 10. Rationals 11. Radicals Simplifying Expressions An expression is a mathematical “phrase.” Expressions contain numbers and variables, but not an equal sign. An equation has an “equal” sign. For example: Expression: Equation: 5 + 3 5 + 3 = 8 x + 3 x + 3 = 8 (x + 4)(x – 2) (x + 4)(x – 2) = 10 x² + 5x + 6 x² + 5x + 6 = 0 x – 8 x – 8 > 3 When we simplify an expression, we work until there are as few terms as possible. This process makes the expression easier to use, (that’s why it’s called “simplify”). The first thing we want to do when simplifying an expression is to combine like terms. For example: There are many terms to look at! Let’s start with x². There Simplify: are no other terms with x² in them, so we move on. 10x x² + 10x – 6 – 5x + 4 and 5x are like terms, so we add their coefficients = x² + 5x – 6 + 4 together. 10 + (-5) = 5, so we write 5x. -6 and 4 are also = x² + 5x – 2 like terms, so we can combine them to get -2. Isn’t the simplified expression much nicer? Now you try: x² + 5x + 3x² + x³ - 5 + 3 [You should get x³ + 4x² + 5x – 2] Order of Operations PEMDAS – Please Excuse My Dear Aunt Sally, remember that from Algebra class? It tells the order in which we can complete operations when solving an equation.
    [Show full text]
  • Which Moments of a Logarithmic Derivative Imply Quasiinvariance?
    Doc Math J DMV Which Moments of a Logarithmic Derivative Imply Quasi invariance Michael Scheutzow Heinrich v Weizsacker Received June Communicated by Friedrich Gotze Abstract In many sp ecial contexts quasiinvariance of a measure under a oneparameter group of transformations has b een established A remarkable classical general result of AV Skorokhod states that a measure on a Hilb ert space is quasiinvariant in a given direction if it has a logarithmic aj j derivative in this direction such that e is integrable for some a In this note we use the techniques of to extend this result to general oneparameter families of measures and moreover we give a complete char acterization of all functions for which the integrability of j j implies quasiinvariance of If is convex then a necessary and sucient condition is that log xx is not integrable at Mathematics Sub ject Classication A C G Overview The pap er is divided into two parts The rst part do es not mention quasiinvariance at all It treats only onedimensional functions and implicitly onedimensional measures The reason is as follows A measure on R has a logarithmic derivative if and only if has an absolutely continuous Leb esgue density f and is given by 0 f x ae Then the integrability of jj is equivalent to the Leb esgue x f 0 f jf The quasiinvariance of is equivalent to the statement integrability of j f that f x Leb esgueae Therefore in the case of onedimensional measures a function allows a quasiinvariance criterion as indicated in the abstract
    [Show full text]
  • Applications of Entire Function Theory to the Spectral Synthesis of Diagonal Operators
    APPLICATIONS OF ENTIRE FUNCTION THEORY TO THE SPECTRAL SYNTHESIS OF DIAGONAL OPERATORS Kate Overmoyer A Dissertation Submitted to the Graduate College of Bowling Green State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY August 2011 Committee: Steven M. Seubert, Advisor Kyoo Kim, Graduate Faculty Representative Kit C. Chan J. Gordon Wade ii ABSTRACT Steven M. Seubert, Advisor A diagonal operator acting on the space H(B(0;R)) of functions analytic on the disk B(0;R) where 0 < R ≤ 1 is defined to be any continuous linear map on H(B(0;R)) having the monomials zn as eigenvectors. In this dissertation, examples of diagonal operators D acting on the spaces H(B(0;R)) where 0 < R < 1, are constructed which fail to admit spectral synthesis; that is, which have invariant subspaces that are not spanned by collec- tions of eigenvectors. Examples include diagonal operators whose eigenvalues are the points fnae2πij=b : 0 ≤ j < bg lying on finitely many rays for suitably chosen a 2 (0; 1) and b 2 N, and more generally whose eigenvalues are the integer lattice points Z×iZ. Conditions for re- moving or perturbing countably many of the eigenvalues of a non-synthetic operator which yield another non-synthetic operator are also given. In addition, sufficient conditions are given for a diagonal operator on the space H(B(0;R)) of entire functions (for which R = 1) to admit spectral synthesis. iii This dissertation is dedicated to my family who believed in me even when I did not believe in myself.
    [Show full text]
  • Complex Analysis Class 24: Wednesday April 2
    Complex Analysis Math 214 Spring 2014 Fowler 307 MWF 3:00pm - 3:55pm c 2014 Ron Buckmire http://faculty.oxy.edu/ron/math/312/14/ Class 24: Wednesday April 2 TITLE Classifying Singularities using Laurent Series CURRENT READING Zill & Shanahan, §6.2-6.3 HOMEWORK Zill & Shanahan, §6.2 3, 15, 20, 24 33*. §6.3 7, 8, 9, 10. SUMMARY We shall be introduced to Laurent Series and learn how to use them to classify different various kinds of singularities (locations where complex functions are no longer analytic). Classifying Singularities There are basically three types of singularities (points where f(z) is not analytic) in the complex plane. Isolated Singularity An isolated singularity of a function f(z) is a point z0 such that f(z) is analytic on the punctured disc 0 < |z − z0| <rbut is undefined at z = z0. We usually call isolated singularities poles. An example is z = i for the function z/(z − i). Removable Singularity A removable singularity is a point z0 where the function f(z0) appears to be undefined but if we assign f(z0) the value w0 with the knowledge that lim f(z)=w0 then we can say that we z→z0 have “removed” the singularity. An example would be the point z = 0 for f(z) = sin(z)/z. Branch Singularity A branch singularity is a point z0 through which all possible branch cuts of a multi-valued function can be drawn to produce a single-valued function. An example of such a point would be the point z = 0 for Log (z).
    [Show full text]
  • Section 1.2 – Mathematical Models: a Catalog of Essential Functions
    Section 1-2 © Sandra Nite Math 131 Lecture Notes Section 1.2 – Mathematical Models: A Catalog of Essential Functions A mathematical model is a mathematical description of a real-world situation. Often the model is a function rule or equation of some type. Modeling Process Real-world Formulate Test/Check problem Real-world Mathematical predictions model Interpret Mathematical Solve conclusions Linear Models Characteristics: • The graph is a line. • In the form y = f(x) = mx + b, m is the slope of the line, and b is the y-intercept. • The rate of change (slope) is constant. • When the independent variable ( x) in a table of values is sequential (same differences), the dependent variable has successive differences that are the same. • The linear parent function is f(x) = x, with D = ℜ = (-∞, ∞) and R = ℜ = (-∞, ∞). • The direct variation function is a linear function with b = 0 (goes through the origin). • In a direct variation function, it can be said that f(x) varies directly with x, or f(x) is directly proportional to x. Example: See pp. 26-28 of the text. 1 Section 1-2 © Sandra Nite Polynomial Functions = n + n−1 +⋅⋅⋅+ 2 + + A function P is called a polynomial if P(x) an x an−1 x a2 x a1 x a0 where n is a nonnegative integer and a0 , a1 , a2 ,..., an are constants called the coefficients of the polynomial. If the leading coefficient an ≠ 0, then the degree of the polynomial is n. Characteristics: • The domain is the set of all real numbers D = (-∞, ∞). • If the degree is odd, the range R = (-∞, ∞).
    [Show full text]
  • Real Proofs of Complex Theorems (And Vice Versa)
    REAL PROOFS OF COMPLEX THEOREMS (AND VICE VERSA) LAWRENCE ZALCMAN Introduction. It has become fashionable recently to argue that real and complex variables should be taught together as a unified curriculum in analysis. Now this is hardly a novel idea, as a quick perusal of Whittaker and Watson's Course of Modern Analysis or either Littlewood's or Titchmarsh's Theory of Functions (not to mention any number of cours d'analyse of the nineteenth or twentieth century) will indicate. And, while some persuasive arguments can be advanced in favor of this approach, it is by no means obvious that the advantages outweigh the disadvantages or, for that matter, that a unified treatment offers any substantial benefit to the student. What is obvious is that the two subjects do interact, and interact substantially, often in a surprising fashion. These points of tangency present an instructor the opportunity to pose (and answer) natural and important questions on basic material by applying real analysis to complex function theory, and vice versa. This article is devoted to several such applications. My own experience in teaching suggests that the subject matter discussed below is particularly well-suited for presentation in a year-long first graduate course in complex analysis. While most of this material is (perhaps by definition) well known to the experts, it is not, unfortunately, a part of the common culture of professional mathematicians. In fact, several of the examples arose in response to questions from friends and colleagues. The mathematics involved is too pretty to be the private preserve of specialists.
    [Show full text]
  • A Logarithmic Derivative Lemma in Several Complex Variables and Its Applications
    TRANSACTIONS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 363, Number 12, December 2011, Pages 6257–6267 S 0002-9947(2011)05226-8 Article electronically published on June 27, 2011 A LOGARITHMIC DERIVATIVE LEMMA IN SEVERAL COMPLEX VARIABLES AND ITS APPLICATIONS BAO QIN LI Abstract. We give a logarithmic derivative lemma in several complex vari- ables and its applications to meromorphic solutions of partial differential equa- tions. 1. Introduction The logarithmic derivative lemma of Nevanlinna is an important tool in the value distribution theory of meromorphic functions and its applications. It has two main forms (see [13, 1.3.3 and 4.2.1], [9, p. 115], [4, p. 36], etc.): Estimate (1) and its consequence, Estimate (2) below. Theorem A. Let f be a non-zero meromorphic function in |z| <R≤ +∞ in the complex plane with f(0) =0 , ∞. Then for 0 <r<ρ<R, 1 2π f (k)(reiθ) log+ | |dθ 2π f(reiθ) (1) 0 1 1 1 ≤ c{log+ T (ρ, f) + log+ log+ +log+ ρ +log+ +log+ +1}, |f(0)| ρ − r r where k is a positive integer and c is a positive constant depending only on k. Estimate (1) with k = 1 was originally due to Nevanlinna, which easily implies the following version of the lemma with exceptional intervals of r for meromorphic functions in the plane: 1 2π f (reiθ) (2) + | | { } log iθ dθ = O log(rT(r, f )) , 2π 0 f(re ) for all r outside a countable union of intervals of finite Lebesgue measure, by using the Borel lemma in a standard way (see e.g.
    [Show full text]
  • Half-Plane Capacity and Conformal Radius
    PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 142, Number 3, March 2014, Pages 931–938 S 0002-9939(2013)11811-3 Article electronically published on December 4, 2013 HALF-PLANE CAPACITY AND CONFORMAL RADIUS STEFFEN ROHDE AND CARTO WONG (Communicated by Jeremy Tyson) Abstract. In this note, we show that the half-plane capacity of a subset of the upper half-plane is comparable to a simple geometric quantity, namely the euclidean area of the hyperbolic neighborhood of radius one of this set. This is achieved by proving a similar estimate for the conformal radius of a subdomain of the unit disc and by establishing a simple relation between these two quantities. 1. Introduction and results Let H = {z ∈ C:Imz>0} be the upper half-plane. A bounded subset A ⊂ H is called a hull if H \ A is a simply connected region. The half-plane capacity of a hull A is the quantity hcap(A) := lim z [gA(z) − z] , z→∞ where gA : H \ A → H is the unique conformal map satisfying the hydrodynamic 1 →∞ normalization g(z)=z + O( z )asz . It appears frequently in connection with the Schramm-Loewner Evolution SLE, since it serves as the conformally natural parameter in the chordal Loewner equation; see [1]. In the study of SLE, one often needs estimates of hcap(A) in terms of geometric properties of A. The definition of hcap in terms of conformal maps (or in terms of Brownian motion as in [1]) does not immediately yield such estimates. The purpose of this note is to provide a geometric quantity that is comparable to hcap(A), via a simple relation between half-plane capacity and conformal radius.
    [Show full text]