Problem Set 6: Solutions Math 201A: Fall a n x n,
|
|
- Colin Marshall
- 5 years ago
- Views:
Transcription
1 Problem Set 6: Solutions Math 201A: Fall 2016 Problem 1. Is (x n ) n=0 a Schauder basis of C([0, 1])? No. If f(x) = a n x n, n=0 where the series converges uniformly on [0, 1], then f has a power series expansion at x = 0 with radius of convergence at least equal to 1, and it follows from the theory of power series that f is infinitely differentiable in [0, 1). For example, f(x) = x has no such expansion. Remark. The density of polynomials in C([0, 1]) is not sufficient to imply that (x n ) is a Schauder basis because one has to use polynomials with different coefficients to obtain better uniform approximations of a non-analytic function. 1
2 Problem 2. Let A : R n R m be a linear map with matrix (a ij ), so y = Ax if y i = n j=1 a ijx j. Equip R n and R m with the one-norms x 1 = n j=1 x j, y 1 = m y i. Show that the corresponding operator norm of A is given by the maximum absolute column sum A 1 = max a ij. We have which shows that y i n a ij x j j=1 ( n m ) a ij x j j=1 m n max a ij x j, j=1 m A 1 max a ij Conversely, for some 1 j 0 n, we have m a ij0 = max a ij. Define x = (x 1,..., x n ) by x j = 1 if j = j 0 0 if j j 0 Then x 1 = 1 and Ax 1 = m a ij 0, which shows that m A 1 max a ij. 2
3 Problem 3. Suppose that (X, ) be a Banach space and M X is a closed linear subspace. Let X/M = x + M : x X denote the the quotient space of X by M, where x + M = y X : y = x + m for some m M, and define x + M = inf m M x + m. Show that : X/M R defines a norm on X/M and X/M is a Banach space with respect to this norm. It is straightforward to check that X/M is a vector space with respect to the natural operations (x + M) + (y + M) = (x + y) + M, λ(x + M) = λx + M. In particular, these operations are well-defined since, for example, if x+m = x +M and y +M = y +M, then (x+y)+m = (x +y )+M. The zero-vector in X/M is the subspace M. We show that is a norm on X/M. (i) Clearly, x + M 0. If x + M = 0, then we can choose m k M such that x m k 0 as k, and then x = lim m k M since M is closed, so x + M = M. (ii) If λ = 0, then λ(x + M) = M; and if λ R \ 0, then, writing m = λm, we have λ(x + M) = inf λx + m = λ inf x + m M m M m = λ x + M. (iii) Let x, y X. Given ɛ > 0, there exists m 1, m 2 M such that Then x + m 1 x + M + ɛ 2, y + m 2 y + M + ɛ 2. (x + M) + (y + M) = inf x + y + m m M x + m 1 + y + m 2 Since ɛ > 0 is arbitrary, x + M + y + M + ɛ. (x + M) + (y + M) x + M + y + M. 3
4 Let (x k + M) be a sequence in X/M such that x k + M <. We will show that (x k + M) converges in X/M. Then Lemma 1, proved below, implies that X/M is complete. For each k N, there exists m k M such that y k = x k + m k satisfies y k x k + M k. Then y k <, so Lemma 1 implies that n y k z as n for some z X. Moreover, x k + M = y k + M. Since 0 M, we have x + M x for every x X. It follows that ( n n ) (x k + M) (z + M) = y k z + M n y k z, which shows that n (x k + M) (z + M) in X/M as n. Lemma 1. A normed linear space (X, ) is complete if and only if every absolutely convergent series converges. That is, if (x k ) is a sequence in X and x k <, then x k converges (in norm) in X. Proof. Suppose that X is complete. If x k converges, then the sequence (s n ) of partial sums s n = n x k is Cauchy in R. Since n n x k x k, k=m+1 k=m+1 the sequence (S n ) of partial sums S n = n x k is Cauchy in X, so x k converges. Conversely, suppose that every absolutely convergent series converges. Let (x n ) be a Cauchy sequence in X. Then (x n ) converges if some subsequence converges. After extracting a subsequence, still denoted by (x n ), we may assume that x k+1 x k < 1/2 k for every k N. Let y k = x k+1 x k. Then y k < and x n = n 1 y k + x 1, so (x n ) converges, meaning that X is complete. 4
5 Problem 4. (a) Suppose that M is a proper closed subspace of a normed linear space X and 0 < r < 1. Show that there exists x X such that x = 1 and d(x, M) = inf m M x m > r. (b) Show that the closed unit ball B = x X : x 1 of an infinitedimensional Banach space X is not compact. (a) Choose x 1 X \ M. Then a = d(x 1, M) > 0 since M is closed. Given any ɛ > 0, there exists m 1 M such that a x 1 m 1 < a+ɛ. Let x = x 1 m 1 x 1 m 1. Then x = 1 and, for each m M, x m = x 1 m x 1 m 1, m = m 1 + x 1 m 1 m. Since m runs over M as m runs over M, we have inf x m = 1 m M x 1 m 1 inf x m 1 m > M which proves the result with 0 < r = a/(a + ɛ) < 1. a a + ɛ, (b) Let X be an infinite-dimensional space with closed unit ball B. We recursively define a set x n : n N B with x m x n > 1/2 for all m n as follows. Pick x 1 B. Given E = x 1,..., x n, let M be the linear span of E. Then the finite-dimensional space M is a proper, closed subspace of X, so by (a) there exists x n+1 B with d(x n+1, M) > 1/2. Any ball of radius 1/4 contains at most one of the points x n, so B does not have a finite (1/4)-net, meaning that B is not totally bounded, and therefore not compact. Remark. The result in (a) is called the Riesz Lemma. If M is a closed proper subspace of a Banach space X, there may not exist a vector x X with x = 1 and d(x, M) = 1. If X is a Hilbert space, however, we can always find such a vector by taking x M. 5
6 Problem 5. Let c be the Banach space of convergent real sequences and let c 0 c be the Banach space of real sequences that converge to 0, both equipped with the sup-norm (x n ) = sup x n. (a) Show that c and c 0 are homeomorphic. Hint. Define Φ : c c 0 by Φ(x 1, x 2, x 3, x 4,... ) = (a, x 1 a, x 2 a, x 3 a,... ), a = lim n x n. (b) For any x c 0 with x = 1, show that there exist y, z c 0 such that y z, y = z = 1, and x = 1 2 (y + z). Deduce that c 0 and c are not isometrically isomorphic. (a) Clearly, Φ is a one-to-one, onto linear map. To show that Φ is a homeomorphism, we prove that Φ and Φ 1 are bounded. If x = (x n ) c, then Φx = max a, sup x n a a + sup x n 2 x, so Φ is bounded. In fact, Φ = 2 since, for example, For y = (y n ) c 0, we have Hence, Φ( 1, 1, 1, 1,... ) = (1, 2, 0, 0,... ). Φ 1 (y 1, y 2, y 3, y 4,... ) = (y 1 + y 2, y 1 + y 3, y 1 + y 4,... ). Φ 1 y = sup y 1 + y n+1 y 1 + sup y n 2 y, so Φ 1 is bounded. In fact, Φ 1 = 2 since, for example, Φ 1 (1, 1, 0, 0, 0,... ) = (2, 1, 1, 1, 1,... ). (b) Suppose that x = (x n ) c 0 and x = 1. Then, since x n 0 as n, we have x j = 1 for some j N and x k 1/2 for some k N. Define y = (y n ) and z = (z n ) by y n = x k + 1/2 if n = k, x n if n k, 6 z n = x k 1/2 if n = k, x n if n k.
7 It follows that: y z since y k z k ; y = z = 1 since y j = z j = 1 and y n, z n 1; and x = (y + z)/2. On the other hand, consider x = (1, 1, 1, 1,... ) c with x = 1. If x = (y + z)/2, then y n + z n = 2 for every n N, and y n > 1 or z n > 1 unless y n = z n = 1. Hence, there do not exist distinct y, z c such that y = z = 1 and x = (y + z)/2. The existence of such a y, z depends only on the geometry of the unit ball, and is preserved under an isometric isomorphism (a linear map that preserves norms). Hence, c 0 and c cannot be isometrically isomorphic. Remark. The result in (a) should be surprising from a finite-dimensional perspective: dimension is a topological invariant, so a finite-dimensional vector space cannot be homeomorphic to a proper subspace. If K X is a convex subset of a linear space X, then a point x K is said to be an extreme point of K if x = ty + (1 t)z for some y, z K and 0 < t < 1 implies that y = x, z = x. That is, x is not an interior point of any line segment in K. Part (b) shows that the closed unit ball in c 0 has no extreme points, but the closed unit ball in c has extreme points. Roughly speaking, the unit ball in c 0 resembles an infinite-dimensional cube with no corners, while the unit ball in c has lots of corners. It follows that the spaces cannot be isometrically isomorphic. As another application, the Krein-Milman theorem implies that every compact, convex set K in a locally convex topological vector space has extreme points (in fact, K is the closed convex hull of its extreme points). It follows from the Banach-Alaoglu theorem that the closed unit ball in the dual of a Banach space is compact and closed in the weak* topology, so it has extreme points. Consequently, if the closed unit ball of a Banach space has no extreme points, then the space cannot be isometrically isomorphic to the dual of a Banach space. For example, c 0 is not the dual of any Banach space. 7
Analysis Preliminary Exam Workshop: Hilbert Spaces
Analysis Preliminary Exam Workshop: Hilbert Spaces 1. Hilbert spaces A Hilbert space H is a complete real or complex inner product space. Consider complex Hilbert spaces for definiteness. If (, ) : H H
More informationPROBLEMS. (b) (Polarization Identity) Show that in any inner product space
1 Professor Carl Cowen Math 54600 Fall 09 PROBLEMS 1. (Geometry in Inner Product Spaces) (a) (Parallelogram Law) Show that in any inner product space x + y 2 + x y 2 = 2( x 2 + y 2 ). (b) (Polarization
More informationLocally convex spaces, the hyperplane separation theorem, and the Krein-Milman theorem
56 Chapter 7 Locally convex spaces, the hyperplane separation theorem, and the Krein-Milman theorem Recall that C(X) is not a normed linear space when X is not compact. On the other hand we could use semi
More informationMAT 578 FUNCTIONAL ANALYSIS EXERCISES
MAT 578 FUNCTIONAL ANALYSIS EXERCISES JOHN QUIGG Exercise 1. Prove that if A is bounded in a topological vector space, then for every neighborhood V of 0 there exists c > 0 such that tv A for all t > c.
More informationAn introduction to some aspects of functional analysis
An introduction to some aspects of functional analysis Stephen Semmes Rice University Abstract These informal notes deal with some very basic objects in functional analysis, including norms and seminorms
More informationOverview of normed linear spaces
20 Chapter 2 Overview of normed linear spaces Starting from this chapter, we begin examining linear spaces with at least one extra structure (topology or geometry). We assume linearity; this is a natural
More informationCompact operators on Banach spaces
Compact operators on Banach spaces Jordan Bell jordan.bell@gmail.com Department of Mathematics, University of Toronto November 12, 2017 1 Introduction In this note I prove several things about compact
More informationCHAPTER VIII HILBERT SPACES
CHAPTER VIII HILBERT SPACES DEFINITION Let X and Y be two complex vector spaces. A map T : X Y is called a conjugate-linear transformation if it is a reallinear transformation from X into Y, and if T (λx)
More informationFUNCTIONAL ANALYSIS LECTURE NOTES: COMPACT SETS AND FINITE-DIMENSIONAL SPACES. 1. Compact Sets
FUNCTIONAL ANALYSIS LECTURE NOTES: COMPACT SETS AND FINITE-DIMENSIONAL SPACES CHRISTOPHER HEIL 1. Compact Sets Definition 1.1 (Compact and Totally Bounded Sets). Let X be a metric space, and let E X be
More informationFunctional Analysis HW #1
Functional Analysis HW #1 Sangchul Lee October 9, 2015 1 Solutions Solution of #1.1. Suppose that X
More informationApplied Analysis (APPM 5440): Final exam 1:30pm 4:00pm, Dec. 14, Closed books.
Applied Analysis APPM 44: Final exam 1:3pm 4:pm, Dec. 14, 29. Closed books. Problem 1: 2p Set I = [, 1]. Prove that there is a continuous function u on I such that 1 ux 1 x sin ut 2 dt = cosx, x I. Define
More informationCHAPTER V DUAL SPACES
CHAPTER V DUAL SPACES DEFINITION Let (X, T ) be a (real) locally convex topological vector space. By the dual space X, or (X, T ), of X we mean the set of all continuous linear functionals on X. By the
More informationFUNCTIONAL ANALYSIS-NORMED SPACE
MAT641- MSC Mathematics, MNIT Jaipur FUNCTIONAL ANALYSIS-NORMED SPACE DR. RITU AGARWAL MALAVIYA NATIONAL INSTITUTE OF TECHNOLOGY JAIPUR 1. Normed space Norm generalizes the concept of length in an arbitrary
More informationWeak Topologies, Reflexivity, Adjoint operators
Chapter 2 Weak Topologies, Reflexivity, Adjoint operators 2.1 Topological vector spaces and locally convex spaces Definition 2.1.1. [Topological Vector Spaces and Locally convex Spaces] Let E be a vector
More informationBest approximations in normed vector spaces
Best approximations in normed vector spaces Mike de Vries 5699703 a thesis submitted to the Department of Mathematics at Utrecht University in partial fulfillment of the requirements for the degree of
More informationMetric Spaces and Topology
Chapter 2 Metric Spaces and Topology From an engineering perspective, the most important way to construct a topology on a set is to define the topology in terms of a metric on the set. This approach underlies
More informationMATH 4200 HW: PROBLEM SET FOUR: METRIC SPACES
MATH 4200 HW: PROBLEM SET FOUR: METRIC SPACES PETE L. CLARK 4. Metric Spaces (no more lulz) Directions: This week, please solve any seven problems. Next week, please solve seven more. Starred parts of
More informationI teach myself... Hilbert spaces
I teach myself... Hilbert spaces by F.J.Sayas, for MATH 806 November 4, 2015 This document will be growing with the semester. Every in red is for you to justify. Even if we start with the basic definition
More informationMath 5052 Measure Theory and Functional Analysis II Homework Assignment 7
Math 5052 Measure Theory and Functional Analysis II Homework Assignment 7 Prof. Wickerhauser Due Friday, February 5th, 2016 Please do Exercises 3, 6, 14, 16*, 17, 18, 21*, 23*, 24, 27*. Exercises marked
More informationYour first day at work MATH 806 (Fall 2015)
Your first day at work MATH 806 (Fall 2015) 1. Let X be a set (with no particular algebraic structure). A function d : X X R is called a metric on X (and then X is called a metric space) when d satisfies
More informationFunctional Analysis. Franck Sueur Metric spaces Definitions Completeness Compactness Separability...
Functional Analysis Franck Sueur 2018-2019 Contents 1 Metric spaces 1 1.1 Definitions........................................ 1 1.2 Completeness...................................... 3 1.3 Compactness......................................
More informationNotions such as convergent sequence and Cauchy sequence make sense for any metric space. Convergent Sequences are Cauchy
Banach Spaces These notes provide an introduction to Banach spaces, which are complete normed vector spaces. For the purposes of these notes, all vector spaces are assumed to be over the real numbers.
More informationSelçuk Demir WS 2017 Functional Analysis Homework Sheet
Selçuk Demir WS 2017 Functional Analysis Homework Sheet 1. Let M be a metric space. If A M is non-empty, we say that A is bounded iff diam(a) = sup{d(x, y) : x.y A} exists. Show that A is bounded iff there
More informationContinuity of convex functions in normed spaces
Continuity of convex functions in normed spaces In this chapter, we consider continuity properties of real-valued convex functions defined on open convex sets in normed spaces. Recall that every infinitedimensional
More informationProblem Set 2: Solutions Math 201A: Fall 2016
Problem Set 2: s Math 201A: Fall 2016 Problem 1. (a) Prove that a closed subset of a complete metric space is complete. (b) Prove that a closed subset of a compact metric space is compact. (c) Prove that
More informationNotes for Functional Analysis
Notes for Functional Analysis Wang Zuoqin (typed by Xiyu Zhai) November 6, 2015 1 Lecture 18 1.1 The convex hull Let X be any vector space, and E X a subset. Definition 1.1. The convex hull of E is the
More informationCombinatorics in Banach space theory Lecture 12
Combinatorics in Banach space theory Lecture The next lemma considerably strengthens the assertion of Lemma.6(b). Lemma.9. For every Banach space X and any n N, either all the numbers n b n (X), c n (X)
More information1. If 1, ω, ω 2, -----, ω 9 are the 10 th roots of unity, then (1 + ω) (1 + ω 2 ) (1 + ω 9 ) is A) 1 B) 1 C) 10 D) 0
4 INUTES. If, ω, ω, -----, ω 9 are the th roots of unity, then ( + ω) ( + ω ) ----- ( + ω 9 ) is B) D) 5. i If - i = a + ib, then a =, b = B) a =, b = a =, b = D) a =, b= 3. Find the integral values for
More informationStone-Čech compactification of Tychonoff spaces
The Stone-Čech compactification of Tychonoff spaces Jordan Bell jordan.bell@gmail.com Department of Mathematics, University of Toronto June 27, 2014 1 Completely regular spaces and Tychonoff spaces A topological
More informationThe weak topology of locally convex spaces and the weak-* topology of their duals
The weak topology of locally convex spaces and the weak-* topology of their duals Jordan Bell jordan.bell@gmail.com Department of Mathematics, University of Toronto April 3, 2014 1 Introduction These notes
More informationYour first day at work MATH 806 (Fall 2015)
Your first day at work MATH 806 (Fall 2015) 1. Let X be a set (with no particular algebraic structure). A function d : X X R is called a metric on X (and then X is called a metric space) when d satisfies
More information4 Linear operators and linear functionals
4 Linear operators and linear functionals The next section is devoted to studying linear operators between normed spaces. Definition 4.1. Let V and W be normed spaces over a field F. We say that T : V
More informationChapter 1. Preliminaries. The purpose of this chapter is to provide some basic background information. Linear Space. Hilbert Space.
Chapter 1 Preliminaries The purpose of this chapter is to provide some basic background information. Linear Space Hilbert Space Basic Principles 1 2 Preliminaries Linear Space The notion of linear space
More information08a. Operators on Hilbert spaces. 1. Boundedness, continuity, operator norms
(February 24, 2017) 08a. Operators on Hilbert spaces Paul Garrett garrett@math.umn.edu http://www.math.umn.edu/ garrett/ [This document is http://www.math.umn.edu/ garrett/m/real/notes 2016-17/08a-ops
More informationREAL RENORMINGS ON COMPLEX BANACH SPACES
REAL RENORMINGS ON COMPLEX BANACH SPACES F. J. GARCÍA PACHECO AND A. MIRALLES Abstract. In this paper we provide two ways of obtaining real Banach spaces that cannot come from complex spaces. In concrete
More informationg 2 (x) (1/3)M 1 = (1/3)(2/3)M.
COMPACTNESS If C R n is closed and bounded, then by B-W it is sequentially compact: any sequence of points in C has a subsequence converging to a point in C Conversely, any sequentially compact C R n is
More informationFunctional Analysis I
Functional Analysis I Course Notes by Stefan Richter Transcribed and Annotated by Gregory Zitelli Polar Decomposition Definition. An operator W B(H) is called a partial isometry if W x = X for all x (ker
More informationEberlein-Šmulian theorem and some of its applications
Eberlein-Šmulian theorem and some of its applications Kristina Qarri Supervisors Trond Abrahamsen Associate professor, PhD University of Agder Norway Olav Nygaard Professor, PhD University of Agder Norway
More informationNUCLEAR SPACE FACTS, STRANGE AND PLAIN
NUCLEAR SPACE FACTS, STRANGE AND PLAIN JEREMY J. BECNEL AND AMBAR N. SENGUPTA Abstract. We present a scenic, but practical drive through nuclear spaces, stopping to look at unexpected results both for
More informationExtreme points of compact convex sets
Extreme points of compact convex sets In this chapter, we are going to show that compact convex sets are determined by a proper subset, the set of its extreme points. Let us start with the main definition.
More informationFunctional Analysis (H) Midterm USTC-2015F haha Your name: Solutions
Functional Analysis (H) Midterm USTC-215F haha Your name: Solutions 1.(2 ) You only need to anser 4 out of the 5 parts for this problem. Check the four problems you ant to be graded. Write don the definitions
More informationLax Solution Part 4. October 27, 2016
Lax Solution Part 4 www.mathtuition88.com October 27, 2016 Textbook: Functional Analysis by Peter D. Lax Exercises: Ch 16: Q2 4. Ch 21: Q1, 2, 9, 10. Ch 28: 1, 5, 9, 10. 1 Chapter 16 Exercise 2 Let h =
More informationTHEOREMS, ETC., FOR MATH 516
THEOREMS, ETC., FOR MATH 516 Results labeled Theorem Ea.b.c (or Proposition Ea.b.c, etc.) refer to Theorem c from section a.b of Evans book (Partial Differential Equations). Proposition 1 (=Proposition
More informationA Brief Introduction to Functional Analysis
A Brief Introduction to Functional Analysis Sungwook Lee Department of Mathematics University of Southern Mississippi sunglee@usm.edu July 5, 2007 Definition 1. An algebra A is a vector space over C with
More informationReal Analysis, 2nd Edition, G.B.Folland Elements of Functional Analysis
Real Analysis, 2nd Edition, G.B.Folland Chapter 5 Elements of Functional Analysis Yung-Hsiang Huang 5.1 Normed Vector Spaces 1. Note for any x, y X and a, b K, x+y x + y and by ax b y x + b a x. 2. It
More information4 Hilbert spaces. The proof of the Hilbert basis theorem is not mathematics, it is theology. Camille Jordan
The proof of the Hilbert basis theorem is not mathematics, it is theology. Camille Jordan Wir müssen wissen, wir werden wissen. David Hilbert We now continue to study a special class of Banach spaces,
More informationSpectral Theory, with an Introduction to Operator Means. William L. Green
Spectral Theory, with an Introduction to Operator Means William L. Green January 30, 2008 Contents Introduction............................... 1 Hilbert Space.............................. 4 Linear Maps
More informationExercise Solutions to Functional Analysis
Exercise Solutions to Functional Analysis Note: References refer to M. Schechter, Principles of Functional Analysis Exersize that. Let φ,..., φ n be an orthonormal set in a Hilbert space H. Show n f n
More informationarxiv: v1 [math.fa] 1 Nov 2017
NON-EXPANSIVE BIJECTIONS TO THE UNIT BALL OF l 1 -SUM OF STRICTLY CONVEX BANACH SPACES V. KADETS AND O. ZAVARZINA arxiv:1711.00262v1 [math.fa] 1 Nov 2017 Abstract. Extending recent results by Cascales,
More informationTHE PROBLEMS FOR THE SECOND TEST FOR BRIEF SOLUTIONS
THE PROBLEMS FOR THE SECOND TEST FOR 18.102 BRIEF SOLUTIONS RICHARD MELROSE Question.1 Show that a subset of a separable Hilbert space is compact if and only if it is closed and bounded and has the property
More information1 Topology Definition of a topology Basis (Base) of a topology The subspace topology & the product topology on X Y 3
Index Page 1 Topology 2 1.1 Definition of a topology 2 1.2 Basis (Base) of a topology 2 1.3 The subspace topology & the product topology on X Y 3 1.4 Basic topology concepts: limit points, closed sets,
More informationLectures on Analysis John Roe
Lectures on Analysis John Roe 2005 2009 1 Lecture 1 About Functional Analysis The key objects of study in functional analysis are various kinds of topological vector spaces. The simplest of these are the
More informationBiholomorphic functions on dual of Banach Space
Biholomorphic functions on dual of Banach Space Mary Lilian Lourenço University of São Paulo - Brazil Joint work with H. Carrión and P. Galindo Conference on Non Linear Functional Analysis. Workshop on
More informationE.7 Alaoglu s Theorem
E.7 Alaoglu s Theorem 359 E.7 Alaoglu s Theorem If X is a normed space, then the closed unit ball in X or X is compact if and only if X is finite-dimensional (Problem A.25). Even so, Alaoglu s Theorem
More informationSpectral theory for compact operators on Banach spaces
68 Chapter 9 Spectral theory for compact operators on Banach spaces Recall that a subset S of a metric space X is precompact if its closure is compact, or equivalently every sequence contains a Cauchy
More informationBanach Spaces II: Elementary Banach Space Theory
BS II c Gabriel Nagy Banach Spaces II: Elementary Banach Space Theory Notes from the Functional Analysis Course (Fall 07 - Spring 08) In this section we introduce Banach spaces and examine some of their
More informationCHAPTER X THE SPECTRAL THEOREM OF GELFAND
CHAPTER X THE SPECTRAL THEOREM OF GELFAND DEFINITION A Banach algebra is a complex Banach space A on which there is defined an associative multiplication for which: (1) x (y + z) = x y + x z and (y + z)
More informationFree spaces and the approximation property
Free spaces and the approximation property Gilles Godefroy Institut de Mathématiques de Jussieu Paris Rive Gauche (CNRS & UPMC-Université Paris-06) September 11, 2015 Gilles Godefroy (IMJ-PRG) Free spaces
More informationTHE RADON NIKODYM PROPERTY AND LIPSCHITZ EMBEDDINGS
THE RADON NIKODYM PROPERTY AND LIPSCHITZ EMBEDDINGS Motivation The idea here is simple. Suppose we have a Lipschitz homeomorphism f : X Y where X and Y are Banach spaces, namely c 1 x y f (x) f (y) c 2
More informationPart III. 10 Topological Space Basics. Topological Spaces
Part III 10 Topological Space Basics Topological Spaces Using the metric space results above as motivation we will axiomatize the notion of being an open set to more general settings. Definition 10.1.
More informationFunctional Analysis, Math 7320 Lecture Notes from August taken by Yaofeng Su
Functional Analysis, Math 7320 Lecture Notes from August 30 2016 taken by Yaofeng Su 1 Essentials of Topology 1.1 Continuity Next we recall a stronger notion of continuity: 1.1.1 Definition. Let (X, d
More informationChapter 3: Baire category and open mapping theorems
MA3421 2016 17 Chapter 3: Baire category and open mapping theorems A number of the major results rely on completeness via the Baire category theorem. 3.1 The Baire category theorem 3.1.1 Definition. A
More information1 Definition and Basic Properties of Compa Operator
1 Definition and Basic Properties of Compa Operator 1.1 Let X be a infinite dimensional Banach space. Show that if A C(X ), A does not have bounded inverse. Proof. Denote the unit ball of X by B and the
More informationMath 209B Homework 2
Math 29B Homework 2 Edward Burkard Note: All vector spaces are over the field F = R or C 4.6. Two Compactness Theorems. 4. Point Set Topology Exercise 6 The product of countably many sequentally compact
More informationTOPOLOGICAL VECTOR SPACES
TOPOLOGICAL VECTOR SPACES PRADIPTA BANDYOPADHYAY 1. Topological Vector Spaces Let X be a linear space over R or C. We denote the scalar field by K. Definition 1.1. A topological vector space (tvs for short)
More informationProfessor Carl Cowen Math Fall 17 PROBLEMS. (b) (Polarization Identity) Show that in any inner product space
1 Professor Carl Cowen Math 54600 Fall 17 PROBLEMS 1. (Geometry in Inner Product Spaces) (a) (Parallelogram Law) Show that in any inner product space x + y 2 + x y 2 = 2( x 2 + y 2 ). (b) (Polarization
More informationFinite-dimensional spaces. C n is the space of n-tuples x = (x 1,..., x n ) of complex numbers. It is a Hilbert space with the inner product
Chapter 4 Hilbert Spaces 4.1 Inner Product Spaces Inner Product Space. A complex vector space E is called an inner product space (or a pre-hilbert space, or a unitary space) if there is a mapping (, )
More informationFunctional Analysis HW #3
Functional Analysis HW #3 Sangchul Lee October 26, 2015 1 Solutions Exercise 2.1. Let D = { f C([0, 1]) : f C([0, 1])} and define f d = f + f. Show that D is a Banach algebra and that the Gelfand transform
More information2. Dual space is essential for the concept of gradient which, in turn, leads to the variational analysis of Lagrange multipliers.
Chapter 3 Duality in Banach Space Modern optimization theory largely centers around the interplay of a normed vector space and its corresponding dual. The notion of duality is important for the following
More informationREAL AND COMPLEX ANALYSIS
REAL AND COMPLE ANALYSIS Third Edition Walter Rudin Professor of Mathematics University of Wisconsin, Madison Version 1.1 No rights reserved. Any part of this work can be reproduced or transmitted in any
More informationRecall that any inner product space V has an associated norm defined by
Hilbert Spaces Recall that any inner product space V has an associated norm defined by v = v v. Thus an inner product space can be viewed as a special kind of normed vector space. In particular every inner
More informationNOTES ON BARNSLEY FERN
NOTES ON BARNSLEY FERN ERIC MARTIN 1. Affine transformations An affine transformation on the plane is a mapping T that preserves collinearity and ratios of distances: given two points A and B, if C is
More informationBanach Spaces V: A Closer Look at the w- and the w -Topologies
BS V c Gabriel Nagy Banach Spaces V: A Closer Look at the w- and the w -Topologies Notes from the Functional Analysis Course (Fall 07 - Spring 08) In this section we discuss two important, but highly non-trivial,
More informationat time t, in dimension d. The index i varies in a countable set I. We call configuration the family, denoted generically by Φ: U (x i (t) x j (t))
Notations In this chapter we investigate infinite systems of interacting particles subject to Newtonian dynamics Each particle is characterized by its position an velocity x i t, v i t R d R d at time
More informationChapter 2 Metric Spaces
Chapter 2 Metric Spaces The purpose of this chapter is to present a summary of some basic properties of metric and topological spaces that play an important role in the main body of the book. 2.1 Metrics
More informationSPECTRAL THEOREM FOR COMPACT SELF-ADJOINT OPERATORS
SPECTRAL THEOREM FOR COMPACT SELF-ADJOINT OPERATORS G. RAMESH Contents Introduction 1 1. Bounded Operators 1 1.3. Examples 3 2. Compact Operators 5 2.1. Properties 6 3. The Spectral Theorem 9 3.3. Self-adjoint
More informationSpectral Mapping Theorem
Spectral Mapping Theorem Dan Sievewright Definition of a Hilbert space Let H be a Hilbert space over C. 1) H is a vector space over C. 2) H has an inner product, : H H C with the following properties.
More informationAnalysis Comprehensive Exam Questions Fall F(x) = 1 x. f(t)dt. t 1 2. tf 2 (t)dt. and g(t, x) = 2 t. 2 t
Analysis Comprehensive Exam Questions Fall 2. Let f L 2 (, ) be given. (a) Prove that ( x 2 f(t) dt) 2 x x t f(t) 2 dt. (b) Given part (a), prove that F L 2 (, ) 2 f L 2 (, ), where F(x) = x (a) Using
More information(convex combination!). Use convexity of f and multiply by the common denominator to get. Interchanging the role of x and y, we obtain that f is ( 2M ε
1. Continuity of convex functions in normed spaces In this chapter, we consider continuity properties of real-valued convex functions defined on open convex sets in normed spaces. Recall that every infinitedimensional
More informationHilbert spaces. 1. Cauchy-Schwarz-Bunyakowsky inequality
(October 29, 2016) Hilbert spaces Paul Garrett garrett@math.umn.edu http://www.math.umn.edu/ garrett/ [This document is http://www.math.umn.edu/ garrett/m/fun/notes 2016-17/03 hsp.pdf] Hilbert spaces are
More informationDavid Hilbert was old and partly deaf in the nineteen thirties. Yet being a diligent
Chapter 5 ddddd dddddd dddddddd ddddddd dddddddd ddddddd Hilbert Space The Euclidean norm is special among all norms defined in R n for being induced by the Euclidean inner product (the dot product). A
More informationConvex Geometry. Carsten Schütt
Convex Geometry Carsten Schütt November 25, 2006 2 Contents 0.1 Convex sets... 4 0.2 Separation.... 9 0.3 Extreme points..... 15 0.4 Blaschke selection principle... 18 0.5 Polytopes and polyhedra.... 23
More informationContinuous Functions on Metric Spaces
Continuous Functions on Metric Spaces Math 201A, Fall 2016 1 Continuous functions Definition 1. Let (X, d X ) and (Y, d Y ) be metric spaces. A function f : X Y is continuous at a X if for every ɛ > 0
More informationQUALIFYING EXAMINATION Harvard University Department of Mathematics Tuesday September 21, 2004 (Day 1)
QUALIFYING EXAMINATION Harvard University Department of Mathematics Tuesday September 21, 2004 (Day 1) Each of the six questions is worth 10 points. 1) Let H be a (real or complex) Hilbert space. We say
More information7 Complete metric spaces and function spaces
7 Complete metric spaces and function spaces 7.1 Completeness Let (X, d) be a metric space. Definition 7.1. A sequence (x n ) n N in X is a Cauchy sequence if for any ɛ > 0, there is N N such that n, m
More informationFUNCTION BASES FOR TOPOLOGICAL VECTOR SPACES. Yılmaz Yılmaz
Topological Methods in Nonlinear Analysis Journal of the Juliusz Schauder Center Volume 33, 2009, 335 353 FUNCTION BASES FOR TOPOLOGICAL VECTOR SPACES Yılmaz Yılmaz Abstract. Our main interest in this
More informationProblem set 5, Real Analysis I, Spring, otherwise. (a) Verify that f is integrable. Solution: Compute since f is even, 1 x (log 1/ x ) 2 dx 1
Problem set 5, Real Analysis I, Spring, 25. (5) Consider the function on R defined by f(x) { x (log / x ) 2 if x /2, otherwise. (a) Verify that f is integrable. Solution: Compute since f is even, R f /2
More information(c) For each α R \ {0}, the mapping x αx is a homeomorphism of X.
A short account of topological vector spaces Normed spaces, and especially Banach spaces, are basic ambient spaces in Infinite- Dimensional Analysis. However, there are situations in which it is necessary
More informationIntroduction to Functional Analysis
Introduction to Functional Analysis Carnegie Mellon University, 21-640, Spring 2014 Acknowledgements These notes are based on the lecture course given by Irene Fonseca but may differ from the exact lecture
More informationHilbert Spaces. Hilbert space is a vector space with some extra structure. We start with formal (axiomatic) definition of a vector space.
Hilbert Spaces Hilbert space is a vector space with some extra structure. We start with formal (axiomatic) definition of a vector space. Vector Space. Vector space, ν, over the field of complex numbers,
More informationExtensions of Lipschitz functions and Grothendieck s bounded approximation property
North-Western European Journal of Mathematics Extensions of Lipschitz functions and Grothendieck s bounded approximation property Gilles Godefroy 1 Received: January 29, 2015/Accepted: March 6, 2015/Online:
More informationconverges as well if x < 1. 1 x n x n 1 1 = 2 a nx n
Solve the following 6 problems. 1. Prove that if series n=1 a nx n converges for all x such that x < 1, then the series n=1 a n xn 1 x converges as well if x < 1. n For x < 1, x n 0 as n, so there exists
More informationMAA6617 COURSE NOTES SPRING 2014
MAA6617 COURSE NOTES SPRING 2014 19. Normed vector spaces Let X be a vector space over a field K (in this course we always have either K = R or K = C). Definition 19.1. A norm on X is a function : X K
More informationFUNCTIONAL ANALYSIS HAHN-BANACH THEOREM. F (m 2 ) + α m 2 + x 0
FUNCTIONAL ANALYSIS HAHN-BANACH THEOREM If M is a linear subspace of a normal linear space X and if F is a bounded linear functional on M then F can be extended to M + [x 0 ] without changing its norm.
More informationMH 7500 THEOREMS. (iii) A = A; (iv) A B = A B. Theorem 5. If {A α : α Λ} is any collection of subsets of a space X, then
MH 7500 THEOREMS Definition. A topological space is an ordered pair (X, T ), where X is a set and T is a collection of subsets of X such that (i) T and X T ; (ii) U V T whenever U, V T ; (iii) U T whenever
More information2.2 Annihilators, complemented subspaces
34CHAPTER 2. WEAK TOPOLOGIES, REFLEXIVITY, ADJOINT OPERATORS 2.2 Annihilators, complemented subspaces Definition 2.2.1. [Annihilators, Pre-Annihilators] Assume X is a Banach space. Let M X and N X. We
More informationProblem 1: Compactness (12 points, 2 points each)
Final exam Selected Solutions APPM 5440 Fall 2014 Applied Analysis Date: Tuesday, Dec. 15 2014, 10:30 AM to 1 PM You may assume all vector spaces are over the real field unless otherwise specified. Your
More informationReal Analysis. Jesse Peterson
Real Analysis Jesse Peterson February 1, 2017 2 Contents 1 Preliminaries 7 1.1 Sets.................................. 7 1.1.1 Countability......................... 8 1.1.2 Transfinite induction.....................
More informationIntroduction to Real Analysis Alternative Chapter 1
Christopher Heil Introduction to Real Analysis Alternative Chapter 1 A Primer on Norms and Banach Spaces Last Updated: March 10, 2018 c 2018 by Christopher Heil Chapter 1 A Primer on Norms and Banach Spaces
More informationAliprantis, Border: Infinite-dimensional Analysis A Hitchhiker s Guide
aliprantis.tex May 10, 2011 Aliprantis, Border: Infinite-dimensional Analysis A Hitchhiker s Guide Notes from [AB2]. 1 Odds and Ends 2 Topology 2.1 Topological spaces Example. (2.2) A semimetric = triangle
More information