Weak Compactness in the Space of Operator Valued Measures and Optimal Control Nasiruddin Ahmed
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
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. -
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........................... -
Math 259A Lecture 7 Notes
Math 259A Lecture 7 Notes Daniel Raban October 11, 2019 1 WO and SO Continuity of Linear Functionals and The Pre-Dual of B 1.1 Weak operator and strong operator continuity of linear functionals Lemma 1.1. Let X be a vector space with seminorms p1; : : : ; pn. Let ' : X ! C be a Pn linear functional such that j'(x)j ≤ i=1 pi(x) for all x 2 X. Then there exist linear P functionals '1;:::;'n : X ! C such that ' = i 'i with j'i(x)j ≤ pi(x) for all x 2 X and for all i. Proof. Let D = fx~ = (x; : : : ; x): x 2 Xg ⊆ Xn, which is a vector subspace. On Xn, n P take p((xi)i=1) = i pi(xi). We also have a linear map' ~ : D ! C given by' ~(~x) = '(x). This map satisfies j~(~x)j ≤ p(~x). By the Hahn-Banach theorem, there exists an n ∗ extension 2 (X ) of' ~ such that j (x1; : : : ; xn)j ≤ p(x1; : : : ; xn). Now define 'k(x) := (0; : : : ; x; 0;::: ), where the x is in the k-th position. Theorem 1.1. Let ' : B! C be linear. ' is weak operator continuous if and only if it is it is strong operator continuous. Proof. We only need to show that if ' is strong operator continuous, then it is weak Pn operator continuous. So assume there exist ξ1; : : : ; ξn 2 X such that j'(x)j ≤ i=1 kxξik P for all x 2 B. By the lemma, we can split ' = 'k, such that j'k(x)j ≤ kxξkk for all x and k. -
Derivations on Metric Measure Spaces
Derivations on Metric Measure Spaces by Jasun Gong A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy (Mathematics) in The University of Michigan 2008 Doctoral Committee: Professor Mario Bonk, Chair Professor Alexander I. Barvinok Professor Juha Heinonen (Deceased) Associate Professor James P. Tappenden Assistant Professor Pekka J. Pankka “Or se’ tu quel Virgilio e quella fonte che spandi di parlar si largo fiume?” rispuos’io lui con vergognosa fronte. “O de li altri poeti onore e lume, vagliami ’l lungo studio e ’l grande amore che m’ha fatto cercar lo tuo volume. Tu se’ lo mio maestro e ’l mio autore, tu se’ solo colui da cu’ io tolsi lo bello stilo che m’ha fatto onore.” [“And are you then that Virgil, you the fountain that freely pours so rich a stream of speech?” I answered him with shame upon my brow. “O light and honor of all other poets, may my long study and the intense love that made me search your volume serve me now. You are my master and my author, you– the only one from whom my writing drew the noble style for which I have been honored.”] from the Divine Comedy by Dante Alighieri, as translated by Allen Mandelbaum [Man82]. In memory of Juha Heinonen, my advisor, teacher, and friend. ii ACKNOWLEDGEMENTS This work was inspired and influenced by many people. I first thank my parents, Ping Po Gong and Chau Sim Gong for all their love and support. They are my first teachers, and from them I learned the value of education and hard work. -
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]. -
Recent Developments in the Theory of Duality in Locally Convex Vector Spaces
[ VOLUME 6 I ISSUE 2 I APRIL– JUNE 2019] E ISSN 2348 –1269, PRINT ISSN 2349-5138 RECENT DEVELOPMENTS IN THE THEORY OF DUALITY IN LOCALLY CONVEX VECTOR SPACES CHETNA KUMARI1 & RABISH KUMAR2* 1Research Scholar, University Department of Mathematics, B. R. A. Bihar University, Muzaffarpur 2*Research Scholar, University Department of Mathematics T. M. B. University, Bhagalpur Received: February 19, 2019 Accepted: April 01, 2019 ABSTRACT: : The present paper concerned with vector spaces over the real field: the passage to complex spaces offers no difficulty. We shall assume that the definition and properties of convex sets are known. A locally convex space is a topological vector space in which there is a fundamental system of neighborhoods of 0 which are convex; these neighborhoods can always be supposed to be symmetric and absorbing. Key Words: LOCALLY CONVEX SPACES We shall be exclusively concerned with vector spaces over the real field: the passage to complex spaces offers no difficulty. We shall assume that the definition and properties of convex sets are known. A convex set A in a vector space E is symmetric if —A=A; then 0ЄA if A is not empty. A convex set A is absorbing if for every X≠0 in E), there exists a number α≠0 such that λxЄA for |λ| ≤ α ; this implies that A generates E. A locally convex space is a topological vector space in which there is a fundamental system of neighborhoods of 0 which are convex; these neighborhoods can always be supposed to be symmetric and absorbing. Conversely, if any filter base is given on a vector space E, and consists of convex, symmetric, and absorbing sets, then it defines one and only one topology on E for which x+y and λx are continuous functions of both their arguments. -
Course Structure for M.Sc. in Mathematics (Academic Year 2019 − 2020)
Course Structure for M.Sc. in Mathematics (Academic Year 2019 − 2020) School of Physical Sciences, Jawaharlal Nehru University 1 Contents 1 Preamble 3 1.1 Minimum eligibility criteria for admission . .3 1.2 Selection procedure . .3 2 Programme structure 4 2.1 Overview . .4 2.2 Semester wise course distribution . .4 3 Courses: core and elective 5 4 Details of the core courses 6 4.1 Algebra I .........................................6 4.2 Real Analysis .......................................8 4.3 Complex Analysis ....................................9 4.4 Basic Topology ...................................... 10 4.5 Algebra II ......................................... 11 4.6 Measure Theory .................................... 12 4.7 Functional Analysis ................................... 13 4.8 Discrete Mathematics ................................. 14 4.9 Probability and Statistics ............................... 15 4.10 Computational Mathematics ............................. 16 4.11 Ordinary Differential Equations ........................... 18 4.12 Partial Differential Equations ............................. 19 4.13 Project ........................................... 20 5 Details of the elective courses 21 5.1 Number Theory ..................................... 21 5.2 Differential Topology .................................. 23 5.3 Harmonic Analysis ................................... 24 5.4 Analytic Number Theory ............................... 25 5.5 Proofs ........................................... 26 5.6 Advanced Algebra ................................... -
Spectral Radii of Bounded Operators on Topological Vector Spaces
SPECTRAL RADII OF BOUNDED OPERATORS ON TOPOLOGICAL VECTOR SPACES VLADIMIR G. TROITSKY Abstract. In this paper we develop a version of spectral theory for bounded linear operators on topological vector spaces. We show that the Gelfand formula for spectral radius and Neumann series can still be naturally interpreted for operators on topological vector spaces. Of course, the resulting theory has many similarities to the conventional spectral theory of bounded operators on Banach spaces, though there are several im- portant differences. The main difference is that an operator on a topological vector space has several spectra and several spectral radii, which fit a well-organized pattern. 0. Introduction The spectral radius of a bounded linear operator T on a Banach space is defined by the Gelfand formula r(T ) = lim n T n . It is well known that r(T ) equals the n k k actual radius of the spectrum σ(T ) p= sup λ : λ σ(T ) . Further, it is known −1 {| | ∈ } ∞ T i that the resolvent R =(λI T ) is given by the Neumann series +1 whenever λ − i=0 λi λ > r(T ). It is natural to ask if similar results are valid in a moreP general setting, | | e.g., for a bounded linear operator on an arbitrary topological vector space. The author arrived to these questions when generalizing some results on Invariant Subspace Problem from Banach lattices to ordered topological vector spaces. One major difficulty is that it is not clear which class of operators should be considered, because there are several non-equivalent ways of defining bounded operators on topological vector spaces. -
Grothendieck Spaces, Operators, and Beyond
Grothendieck spaces, operators, and beyond Tomasz Kania Academy of Sciences of the Czech Republic, Praha Zimní škola z abstraktní analýzy Svratka, 13 leden 2019 joint work with K. Beanland & N. J. Laustsen 1 I closed under surjective linear images (hence complemented subspaces) –just apply Hahn–Banach! I not closed under taking subspaces (c0 ⊂ `1), I closed under forming `p-sums with p 2 (1; 1) but not for p = 1! I call such spaces Grothendieck. This class is I A separable space is G. if and only if it is reflexive–use Eberlein–Šmulian. s I Ergodic theory of op on G. spaces works rather well. So is it one of those ‘non-separable’ talks? Well... Overview ∗ I Grothendieck’s motivation: measure-theoretic as `1(Γ) comprises finitely additive measures on }(Γ); strengthening certain measure theoretic principles. Background Theorem (Grothendieck, 1953). Every weak* convergent sequence (fn) in the dual of `1(Γ) converges with respect to the weak topology. 2 I closed under surjective linear images (hence complemented subspaces) –just apply Hahn–Banach! I not closed under taking subspaces (c0 ⊂ `1), I closed under forming `p-sums with p 2 (1; 1) but not for p = 1! I call such spaces Grothendieck. This class is I A separable space is G. if and only if it is reflexive–use Eberlein–Šmulian. s I Ergodic theory of op on G. spaces works rather well. So is it one of those ‘non-separable’ talks? Well... Background Theorem (Grothendieck, 1953). Every weak* convergent sequence (fn) in the dual of `1(Γ) converges with respect to the weak topology. -
Weak Operator Topology, Operator Ranges and Operator Equations Via Kolmogorov Widths
Weak operator topology, operator ranges and operator equations via Kolmogorov widths M. I. Ostrovskii and V. S. Shulman Abstract. Let K be an absolutely convex infinite-dimensional compact in a Banach space X . The set of all bounded linear operators T on X satisfying TK ⊃ K is denoted by G(K). Our starting point is the study of the closure WG(K) of G(K) in the weak operator topology. We prove that WG(K) contains the algebra of all operators leaving lin(K) invariant. More precise results are obtained in terms of the Kolmogorov n-widths of the compact K. The obtained results are used in the study of operator ranges and operator equations. Mathematics Subject Classification (2000). Primary 47A05; Secondary 41A46, 47A30, 47A62. Keywords. Banach space, bounded linear operator, Hilbert space, Kolmogorov width, operator equation, operator range, strong operator topology, weak op- erator topology. 1. Introduction Let K be a subset in a Banach space X . We say (with some abuse of the language) that an operator D 2 L(X ) covers K, if DK ⊃ K. The set of all operators covering K will be denoted by G(K). It is a semigroup with a unit since the identity operator is in G(K). It is easy to check that if K is compact then G(K) is closed in the norm topology and, moreover, sequentially closed in the weak operator topology (WOT). It is somewhat surprising that for each absolutely convex infinite- dimensional compact K the WOT-closure of G(K) is much larger than G(K) itself, and in many cases it coincides with the algebra L(X ) of all operators on X . -
Spaces of Compact Operators N
Math. Ann. 208, 267--278 (1974) Q by Springer-Verlag 1974 Spaces of Compact Operators N. J. Kalton 1. Introduction In this paper we study the structure of the Banach space K(E, F) of all compact linear operators between two Banach spaces E and F. We study three distinct problems: weak compactness in K(E, F), subspaces isomorphic to l~ and complementation of K(E, F) in L(E, F), the space of bounded linear operators. In § 2 we derive a simple characterization of the weakly compact subsets of K(E, F) using a criterion of Grothendieck. This enables us to study reflexivity and weak sequential convergence. In § 3 a rather dif- ferent problem is investigated from the same angle. Recent results of Tong [20] indicate that we should consider when K(E, F) may have a subspace isomorphic to l~. Although L(E, F) often has this property (e.g. take E = F =/2) it turns out that K(E, F) can only contain a copy of l~o if it inherits one from either E* or F. In § 4 these results are applied to improve the results obtained by Tong and also to approach the problem investigated by Tong and Wilken [21] of whether K(E, F) can be non-trivially complemented in L(E,F) (see also Thorp [19] and Arterburn and Whitley [2]). It should be pointed out that the general trend of this paper is to indicate that K(E, F) accurately reflects the structure of E and F, in the sense that it has few properties which are not directly inherited from E and F. -
An Introduction to Some Aspects of Functional Analysis, 7: Convergence of Operators
An introduction to some aspects of functional analysis, 7: Convergence of operators Stephen Semmes Rice University Abstract Here we look at strong and weak operator topologies on spaces of bounded linear mappings, and convergence of sequences of operators with respect to these topologies in particular. Contents I The strong operator topology 2 1 Seminorms 2 2 Bounded linear mappings 4 3 The strong operator topology 5 4 Shift operators 6 5 Multiplication operators 7 6 Dense sets 9 7 Shift operators, 2 10 8 Other operators 11 9 Unitary operators 12 10 Measure-preserving transformations 13 II The weak operator topology 15 11 Definitions 15 1 12 Multiplication operators, 2 16 13 Dual linear mappings 17 14 Shift operators, 3 19 15 Uniform boundedness 21 16 Continuous linear functionals 22 17 Bilinear functionals 23 18 Compactness 24 19 Other operators, 2 26 20 Composition operators 27 21 Continuity properties 30 References 32 Part I The strong operator topology 1 Seminorms Let V be a vector space over the real or complex numbers. A nonnegative real-valued function N(v) on V is said to be a seminorm on V if (1.1) N(tv) = |t| N(v) for every v ∈ V and t ∈ R or C, as appropriate, and (1.2) N(v + w) ≤ N(v) + N(w) for every v, w ∈ V . Here |t| denotes the absolute value of a real number t, or the modulus of a complex number t. If N(v) > 0 when v 6= 0, then N(v) is a norm on V , and (1.3) d(v, w) = N(v − w) defines a metric on V .