Recent Developments in the Theory of Duality in Locally Convex Vector Spaces
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Topology Proceedings
Topology Proceedings Web: http://topology.auburn.edu/tp/ Mail: Topology Proceedings Department of Mathematics & Statistics Auburn University, Alabama 36849, USA E-mail: [email protected] ISSN: 0146-4124 COPYRIGHT °c by Topology Proceedings. All rights reserved. TOPOLOGY PROCEEDINGS Volume 26, 2001{2002 Pages 695{707 WEAKLY EBERLEIN COMPACT SPACES DANIEL JARDON´ ∗ Abstract. Call a space X weakly splittable if, for each f X 2 R , there exists a σ-compact F Cp(X) such that f F (the bar denotes the closure in RX⊂). A weakly splittable com-2 pact space is called weakly Eberlein compact. We prove that weakly Eberlein compact spaces have almost the same prop- erties as Eberlein compact spaces. We show that any weakly Eberlein compact space of cardinality 6 c is Eberlein com- pact. We prove that a compact space X is weakly Eberlein compact if and only if X is splittable over the class of Eber- lein compact spaces and that every countably compact weakly splittable space has the Preiss{Simon property. 0. Introduction The first one to study weakly compact subspaces of Banach spaces was Eberlein [Eb]. His results showed that these compact spaces are very important and have numerous applications in many areas of mathematics. That is why they were called Eberlein com- pact spaces. In fact, a compact space X is Eberlein compact if and only if Cp(X) has a σ-compact dense subspace and it is a non-trivial theorem that these two definitions are equivalent. The basic results of the theory of Eberlein compact spaces have many 2000 Mathematics Subject Classification. -
Sisältö Part I: Topological Vector Spaces 4 1. General Topological
Sisalt¨ o¨ Part I: Topological vector spaces 4 1. General topological vector spaces 4 1.1. Vector space topologies 4 1.2. Neighbourhoods and filters 4 1.3. Finite dimensional topological vector spaces 9 2. Locally convex spaces 10 2.1. Seminorms and semiballs 10 2.2. Continuous linear mappings in locally convex spaces 13 3. Generalizations of theorems known from normed spaces 15 3.1. Separation theorems 15 Hahn and Banach theorem 17 Important consequences 18 Hahn-Banach separation theorem 19 4. Metrizability and completeness (Fr`echet spaces) 19 4.1. Baire's category theorem 19 4.2. Complete topological vector spaces 21 4.3. Metrizable locally convex spaces 22 4.4. Fr´echet spaces 23 4.5. Corollaries of Baire 24 5. Constructions of spaces from each other 25 5.1. Introduction 25 5.2. Subspaces 25 5.3. Factor spaces 26 5.4. Product spaces 27 5.5. Direct sums 27 5.6. The completion 27 5.7. Projektive limits 28 5.8. Inductive locally convex limits 28 5.9. Direct inductive limits 29 6. Bounded sets 29 6.1. Bounded sets 29 6.2. Bounded linear mappings 31 7. Duals, dual pairs and dual topologies 31 7.1. Duals 31 7.2. Dual pairs 32 7.3. Weak topologies in dualities 33 7.4. Polars 36 7.5. Compatible topologies 39 7.6. Polar topologies 40 PART II Distributions 42 1. The idea of distributions 42 1.1. Schwartz test functions and distributions 42 2. Schwartz's test function space 43 1 2.1. The spaces C (Ω) and DK 44 1 2 2.2. -
Duality, Part 1: Dual Bases and Dual Maps Notation
Duality, part 1: Dual Bases and Dual Maps Notation F denotes either R or C. V and W denote vector spaces over F. Define ': R3 ! R by '(x; y; z) = 4x − 5y + 2z. Then ' is a linear functional on R3. n n Fix (b1;:::; bn) 2 C . Define ': C ! C by '(z1;:::; zn) = b1z1 + ··· + bnzn: Then ' is a linear functional on Cn. Define ': P(R) ! R by '(p) = 3p00(5) + 7p(4). Then ' is a linear functional on P(R). R 1 Define ': P(R) ! R by '(p) = 0 p(x) dx. Then ' is a linear functional on P(R). Examples: Linear Functionals Definition: linear functional A linear functional on V is a linear map from V to F. In other words, a linear functional is an element of L(V; F). n n Fix (b1;:::; bn) 2 C . Define ': C ! C by '(z1;:::; zn) = b1z1 + ··· + bnzn: Then ' is a linear functional on Cn. Define ': P(R) ! R by '(p) = 3p00(5) + 7p(4). Then ' is a linear functional on P(R). R 1 Define ': P(R) ! R by '(p) = 0 p(x) dx. Then ' is a linear functional on P(R). Linear Functionals Definition: linear functional A linear functional on V is a linear map from V to F. In other words, a linear functional is an element of L(V; F). Examples: Define ': R3 ! R by '(x; y; z) = 4x − 5y + 2z. Then ' is a linear functional on R3. Define ': P(R) ! R by '(p) = 3p00(5) + 7p(4). Then ' is a linear functional on P(R). R 1 Define ': P(R) ! R by '(p) = 0 p(x) dx. -
Weak Compactness in the Space of Operator Valued Measures and Optimal Control Nasiruddin Ahmed
Weak Compactness in the Space of Operator Valued Measures and Optimal Control Nasiruddin Ahmed To cite this version: Nasiruddin Ahmed. Weak Compactness in the Space of Operator Valued Measures and Optimal Control. 25th System Modeling and Optimization (CSMO), Sep 2011, Berlin, Germany. pp.49-58, 10.1007/978-3-642-36062-6_5. hal-01347522 HAL Id: hal-01347522 https://hal.inria.fr/hal-01347522 Submitted on 21 Jul 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Distributed under a Creative Commons Attribution| 4.0 International License WEAK COMPACTNESS IN THE SPACE OF OPERATOR VALUED MEASURES AND OPTIMAL CONTROL N.U.Ahmed EECS, University of Ottawa, Ottawa, Canada Abstract. In this paper we present a brief review of some important results on weak compactness in the space of vector valued measures. We also review some recent results of the author on weak compactness of any set of operator valued measures. These results are then applied to optimal structural feedback control for deterministic systems on infinite dimensional spaces. Keywords: Space of Operator valued measures, Countably additive op- erator valued measures, Weak compactness, Semigroups of bounded lin- ear operators, Optimal Structural control. -
Approximation Boundedness Surjectivity
APPROXIMATION BOUNDEDNESS SURJECTIVITY Olav Kristian Nygaard Dr. scient. thesis, University of Bergen, 2001 Approximation, Boundedness, Surjectivity Olav Kr. Nygaard, 2001 ISBN 82-92-160-08-6 Contents 1Theframework 9 1.1 Separability, bases and the approximation property ....... 13 1.2Thecompletenessassumption................... 16 1.3Theoryofclosed,convexsets................... 19 2 Factorization of weakly compact operators and the approximation property 25 2.1Introduction............................. 25 2.2 Criteria of the approximation property in terms of the Davis- Figiel-Johnson-Pe'lczy´nskifactorization.............. 27 2.3Uniformisometricfactorization.................. 33 2.4 The approximation property and ideals of finite rank operators 36 2.5 The compact approximation property and ideals of compact operators.............................. 39 2.6 From approximation properties to metric approximation prop- erties................................. 41 3 Boundedness and surjectivity 49 3.1Introduction............................. 49 3.2Somemorepreliminaries...................... 52 3.3 The boundedness property in normed spaces . ....... 57 3.4ThesurjectivitypropertyinBanachspaces........... 59 3.5 The Seever property and the Nikod´ymproperty......... 63 3.6 Some results on thickness in L(X, Y )∗ .............. 63 3.7Somequestionsandremarks.................... 65 4 Slices in the unit ball of a uniform algebra 69 4.1Introduction............................. 69 4.2Thesliceshavediameter2..................... 70 4.3Someremarks........................... -
Multilinear Algebra
Appendix A Multilinear Algebra This chapter presents concepts from multilinear algebra based on the basic properties of finite dimensional vector spaces and linear maps. The primary aim of the chapter is to give a concise introduction to alternating tensors which are necessary to define differential forms on manifolds. Many of the stated definitions and propositions can be found in Lee [1], Chaps. 11, 12 and 14. Some definitions and propositions are complemented by short and simple examples. First, in Sect. A.1 dual and bidual vector spaces are discussed. Subsequently, in Sects. A.2–A.4, tensors and alternating tensors together with operations such as the tensor and wedge product are introduced. Lastly, in Sect. A.5, the concepts which are necessary to introduce the wedge product are summarized in eight steps. A.1 The Dual Space Let V be a real vector space of finite dimension dim V = n.Let(e1,...,en) be a basis of V . Then every v ∈ V can be uniquely represented as a linear combination i v = v ei , (A.1) where summation convention over repeated indices is applied. The coefficients vi ∈ R arereferredtoascomponents of the vector v. Throughout the whole chapter, only finite dimensional real vector spaces, typically denoted by V , are treated. When not stated differently, summation convention is applied. Definition A.1 (Dual Space)Thedual space of V is the set of real-valued linear functionals ∗ V := {ω : V → R : ω linear} . (A.2) The elements of the dual space V ∗ are called linear forms on V . © Springer International Publishing Switzerland 2015 123 S.R. -
Arxiv:1702.07867V1 [Math.FA]
TOPOLOGICAL PROPERTIES OF STRICT (LF )-SPACES AND STRONG DUALS OF MONTEL STRICT (LF )-SPACES SAAK GABRIYELYAN Abstract. Following [2], a Tychonoff space X is Ascoli if every compact subset of Ck(X) is equicontinuous. By the classical Ascoli theorem every k- space is Ascoli. We show that a strict (LF )-space E is Ascoli iff E is a Fr´echet ′ space or E = ϕ. We prove that the strong dual Eβ of a Montel strict (LF )- space E is an Ascoli space iff one of the following assertions holds: (i) E is a ′ Fr´echet–Montel space, so Eβ is a sequential non-Fr´echet–Urysohn space, or (ii) ′ ω D E = ϕ, so Eβ = R . Consequently, the space (Ω) of test functions and the space of distributions D′(Ω) are not Ascoli that strengthens results of Shirai [20] and Dudley [5], respectively. 1. Introduction. The class of strict (LF )-spaces was intensively studied in the classic paper of Dieudonn´eand Schwartz [3]. It turns out that many of strict (LF )-spaces, in particular a lot of linear spaces considered in Schwartz’s theory of distributions [18], are not metrizable. Even the simplest ℵ0-dimensional strict (LF )-space ϕ, n the inductive limit of the sequence {R }n∈ω, is not metrizable. Nyikos [16] showed that ϕ is a sequential non-Fr´echet–Urysohn space (all relevant definitions are given in the next section). On the other hand, Shirai [20] proved the space D(Ω) of test functions over an open subset Ω of Rn, which is one of the most famous example of strict (LF )-spaces, is not sequential. -
Grothendieck Spaces with the Dunford–Pettis Property
GROTHENDIECK SPACES WITH THE DUNFORD–PETTIS PROPERTY ANGELA A. ALBANESE*, JOSÉ BONET+ AND WERNER J. RICKER Abstract. Banach spaces which are Grothendieck spaces with the Dunford– Pettis property (briefly, GDP) are classical. A systematic treatment of GDP– Fréchet spaces occurs in [12]. This investigation is continued here for locally convex Hausdorff spaces. The product and (most) inductive limits of GDP– space are again GDP–spaces. Also, every complete injective space is a GDP– space. For p ∈ {0} ∪ [1, ∞) it is shown that the classical co–echelon spaces kp(V ) and Kp(V ) are GDP–spaces if and only if they are Montel. On the other hand, K∞(V ) is always a GDP–space and k∞(V ) is a GDP–space whenever its (Fréchet) predual, i.e., the Köthe echelon space λ1(A), is distinguished. 1. Introduction. Grothendieck spaces with the Dunford–Pettis property (briefly, GDP) play a prominent role in the theory of Banach spaces and vector measures; see Ch.VI of [17], especially the Notes and Remarks, and [18]. Known examples include L∞, ∞ ∞ H (D), injective Banach spaces (e.g. ` ) and certain C(K) spaces. D. Dean showed in [14] that a GDP–space does not admit any Schauder decomposition; see also [26, Corollary 8]. This has serious consequences for spectral measures in such spaces, [31]. For non–normable spaces the situation changes dramatically. Every Fréchet Montel space X is a GDP–space, [12, Remark 2.2]. Other than Montel spaces, the only known non–normable Fréchet space which is a GDP–space is the Köthe echelon space λ∞(A), for an arbitrary Köthe matrix A, [12, Proposition 3.1]. -
S-Barrelled Topological Vector Spaces*
Canad. Math. Bull. Vol. 21 (2), 1978 S-BARRELLED TOPOLOGICAL VECTOR SPACES* BY RAY F. SNIPES N. Bourbaki [1] was the first to introduce the class of locally convex topological vector spaces called "espaces tonnelés" or "barrelled spaces." These spaces have some of the important properties of Banach spaces and Fréchet spaces. Indeed, a generalized Banach-Steinhaus theorem is valid for them, although barrelled spaces are not necessarily metrizable. Extensive accounts of the properties of barrelled locally convex topological vector spaces are found in [5] and [8]. In the last few years, many new classes of locally convex spaces having various types of barrelledness properties have been defined (see [6] and [7]). In this paper, using simple notions of sequential convergence, we introduce several new classes of topological vector spaces which are similar to Bourbaki's barrelled spaces. The most important of these we call S-barrelled topological vector spaces. A topological vector space (X, 2P) is S-barrelled if every sequen tially closed, convex, balanced, and absorbing subset of X is a sequential neighborhood of the zero vector 0 in X Examples are given of spaces which are S-barrelled but not barrelled. Then some of the properties of S-barrelled spaces are given—including permanence properties, and a form of the Banach- Steinhaus theorem valid for them. S-barrelled spaces are useful in the study of sequentially continuous linear transformations and sequentially continuous bilinear functions. For the most part, we use the notations and definitions of [5]. Proofs which closely follow the standard patterns are omitted. 1. Definitions and Examples. -
Calculus on a Normed Linear Space
Calculus on a Normed Linear Space James S. Cook Liberty University Department of Mathematics Fall 2017 2 introduction and scope These notes are intended for someone who has completed the introductory calculus sequence and has some experience with matrices or linear algebra. This set of notes covers the first month or so of Math 332 at Liberty University. I intend this to serve as a supplement to our required text: First Steps in Differential Geometry: Riemannian, Contact, Symplectic by Andrew McInerney. Once we've covered these notes then we begin studying Chapter 3 of McInerney's text. This course is primarily concerned with abstractions of calculus and geometry which are accessible to the undergraduate. This is not a course in real analysis and it does not have a prerequisite of real analysis so my typical students are not prepared for topology or measure theory. We defer the topology of manifolds and exposition of abstract integration in the measure theoretic sense to another course. Our focus for course as a whole is on what you might call the linear algebra of abstract calculus. Indeed, McInerney essentially declares the same philosophy so his text is the natural extension of what I share in these notes. So, what do we study here? In these notes: How to generalize calculus to the context of a normed linear space In particular, we study: basic linear algebra, spanning, linear independennce, basis, coordinates, norms, distance functions, inner products, metric topology, limits and their laws in a NLS, conti- nuity of mappings on NLS's, -
On Nonbornological Barrelled Spaces Annales De L’Institut Fourier, Tome 22, No 2 (1972), P
ANNALES DE L’INSTITUT FOURIER MANUEL VALDIVIA On nonbornological barrelled spaces Annales de l’institut Fourier, tome 22, no 2 (1972), p. 27-30 <http://www.numdam.org/item?id=AIF_1972__22_2_27_0> © Annales de l’institut Fourier, 1972, tous droits réservés. L’accès aux archives de la revue « Annales de l’institut Fourier » (http://annalif.ujf-grenoble.fr/) implique l’accord avec les conditions gé- nérales d’utilisation (http://www.numdam.org/conditions). Toute utilisa- tion commerciale ou impression systématique est constitutive d’une in- fraction pénale. Toute copie ou impression de ce fichier doit conte- nir la présente mention de copyright. Article numérisé dans le cadre du programme Numérisation de documents anciens mathématiques http://www.numdam.org/ Ann. Inst. Fourier, Grenoble 22, 2 (1972), 27-30. ON NONBORNOLOGICAL BARRELLED SPACES 0 by Manuel VALDIVIA L. Nachbin [5] and T. Shirota [6], give an answer to a problem proposed by N. Bourbaki [1] and J. Dieudonne [2], giving an example of a barrelled space, which is not bornological. Posteriorly some examples of nonbornological barrelled spaces have been given, e.g. Y. Komura, [4], has constructed a Montel space which is not bornological. In this paper we prove that if E is the topological product of an uncountable family of barrelled spaces, of nonzero dimension, there exists an infinite number of barrelled subspaces of E, which are not bornological.We obtain also an analogous result replacing « barrelled » by « quasi-barrelled ». We use here nonzero vector spaces on the field K of real or complex number. The topologies on these spaces are sepa- rated. -
Characterizations of the Reflexive Spaces in the Spirit of James' Theorem
Characterizations of the reflexive spaces in the spirit of James' Theorem Mar¶³aD. Acosta, Julio Becerra Guerrero, and Manuel Ruiz Gal¶an Since the famous result by James appeared, several authors have given char- acterizations of reflexivity in terms of the set of norm-attaining functionals. Here, we o®er a survey of results along these lines. Section 1 contains a brief history of the classical results. In Section 2 we assume some topological properties on the size of the set of norm-attaining functionals in order to obtain reflexivity of the space or some weaker conditions. Finally, in Section 3, we consider other functions, such as polynomials or multilinear mappings instead of functionals, and state analogous versions of James' Theorem. Hereinafter, we will denote by BX and SX the closed unit ball and the unit sphere, respectively, of a Banach space X. The stated results are valid in the complex case. However, for the sake of simplicity, we will only consider real normed spaces. 1. James' Theorem In 1950 Klee proved that a Banach space X is reflexive provided that for every space isomorphic to X, each functional attains its norm [Kl]. James showed in 1957 that a separable Banach space allowing every functional to attain its norm has to be reflexive [Ja1]. This result was generalized to the non-separable case in [Ja2, Theorem 5]. After that, a general characterization of the bounded, closed and convex subsets of a Banach space that are weakly compact was obtained: Theorem 1.1. ([Ja3, Theorem 4]) In order that a bounded, closed and convex subset K of a Banach space be weakly compact, it su±ces that every functional attain its supremum on K: See also [Ja3, Theorem 6] for a version in locally convex spaces.