Operator Ranges and Spaceability ∗ Derek Kitson, Richard M
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Linear Operators and Adjoints
Chapter 6 Linear operators and adjoints Contents Introduction .......................................... ............. 6.1 Fundamentals ......................................... ............. 6.2 Spaces of bounded linear operators . ................... 6.3 Inverseoperators.................................... ................. 6.5 Linearityofinverses.................................... ............... 6.5 Banachinversetheorem ................................. ................ 6.5 Equivalenceofspaces ................................. ................. 6.5 Isomorphicspaces.................................... ................ 6.6 Isometricspaces...................................... ............... 6.6 Unitaryequivalence .................................... ............... 6.7 Adjoints in Hilbert spaces . .............. 6.11 Unitaryoperators ...................................... .............. 6.13 Relations between the four spaces . ................. 6.14 Duality relations for convex cones . ................. 6.15 Geometric interpretation of adjoints . ............... 6.15 Optimization in Hilbert spaces . .............. 6.16 Thenormalequations ................................... ............... 6.16 Thedualproblem ...................................... .............. 6.17 Pseudo-inverseoperators . .................. 6.18 AnalysisoftheDTFT ..................................... ............. 6.21 6.1 Introduction The field of optimization uses linear operators and their adjoints extensively. Example. differentiation, convolution, Fourier transform, -
A Note on Riesz Spaces with Property-$ B$
Czechoslovak Mathematical Journal Ş. Alpay; B. Altin; C. Tonyali A note on Riesz spaces with property-b Czechoslovak Mathematical Journal, Vol. 56 (2006), No. 2, 765–772 Persistent URL: http://dml.cz/dmlcz/128103 Terms of use: © Institute of Mathematics AS CR, 2006 Institute of Mathematics of the Czech Academy of Sciences provides access to digitized documents strictly for personal use. Each copy of any part of this document must contain these Terms of use. This document has been digitized, optimized for electronic delivery and stamped with digital signature within the project DML-CZ: The Czech Digital Mathematics Library http://dml.cz Czechoslovak Mathematical Journal, 56 (131) (2006), 765–772 A NOTE ON RIESZ SPACES WITH PROPERTY-b S¸. Alpay, B. Altin and C. Tonyali, Ankara (Received February 6, 2004) Abstract. We study an order boundedness property in Riesz spaces and investigate Riesz spaces and Banach lattices enjoying this property. Keywords: Riesz spaces, Banach lattices, b-property MSC 2000 : 46B42, 46B28 1. Introduction and preliminaries All Riesz spaces considered in this note have separating order duals. Therefore we will not distinguish between a Riesz space E and its image in the order bidual E∼∼. In all undefined terminology concerning Riesz spaces we will adhere to [3]. The notions of a Riesz space with property-b and b-order boundedness of operators between Riesz spaces were introduced in [1]. Definition. Let E be a Riesz space. A set A E is called b-order bounded in ⊂ E if it is order bounded in E∼∼. A Riesz space E is said to have property-b if each subset A E which is order bounded in E∼∼ remains order bounded in E. -
7.3 Topological Vector Spaces, the Weak and Weak⇤ Topology on Banach Spaces
138 CHAPTER 7. ELEMENTS OF FUNCTIONAL ANALYSIS 7.3 Topological Vector spaces, the weak and weak⇤ topology on Banach spaces The following generalizes normed Vector space. Definition 7.3.1. Let X be a vector space over K, K = C, or K = R, and assume that is a topology on X. we say that X is a topological vector T space (with respect to ), if (X X and K X are endowed with the T ⇥ ⇥ respective product topology) +:X X X, (x, y) x + y is continuous ⇥ ! 7! : K X (λ, x) λ x is continuous. · ⇥ 7! · A topological vector space X is called locally convex,ifeveryx X has a 2 neighborhood basis consisting of convex sets, where a set A X is called ⇢ convex if for all x, y A, and 0 <t<1, it follows that tx +1 t)y A. 2 − 2 In order to define a topology on a vector space E which turns E into a topological vector space we (only) need to define an appropriate neighbor- hood basis of 0. Proposition 7.3.2. Assume that (E, ) is a topological vector space. And T let = U , 0 U . U0 { 2T 2 } Then a) For all x E, x + = x + U : U is a neighborhood basis of x, 2 U0 { 2U0} b) for all U there is a V so that V + V U, 2U0 2U0 ⇢ c) for all U and all R>0 there is a V ,sothat 2U0 2U0 λ K : λ <R V U, { 2 | | }· ⇢ d) for all U and x E there is an ">0,sothatλx U,forall 2U0 2 2 λ K with λ <", 2 | | e) if (E, ) is Hausdor↵, then for every x E, x =0, there is a U T 2 6 2U0 with x U, 62 f) if E is locally convex, then for all U there is a convex V , 2U0 2T with V U. -
Baire Category Theorem and Its Consequences
Functional Analysis, BSM, Spring 2012 Exercise sheet: Baire category theorem and its consequences S1 Baire category theorem. If (X; d) is a complete metric space and X = n=1 Fn for some closed sets Fn, then for at least one n the set Fn contains a ball, that is, 9x 2 X; r > 0 : Br(x) ⊂ Fn. Principle of uniform boundedness (Banach-Steinhaus). Let (X; k · kX ) be a Banach space, (Y; k · kY ) a normed space and Tn : X ! Y a bounded operator for each n 2 N. Suppose that for any x 2 X there exists Cx > 0 such that kTnxkY ≤ Cx for all n. Then there exists C > 0 such that kTnk ≤ C for all n. Inverse mapping theorem. Let X; Y be Banach spaces and T : X ! Y a bounded operator. Suppose that T is injective (ker T = f0g) and surjective (ran T = Y ). Then the inverse operator T −1 : Y ! X is necessarily bounded. 1. Consider the set Q of rational numbers with the metric d(x; y) = jx − yj; x; y 2 Q. Show that the Baire category theorem does not hold in this metric space. 2. Let (X; d) be a complete metric space. Suppose that Gn ⊂ X is a dense open set for n 2 N. Show that T1 n=1 Gn is non-empty. Find a non-complete metric space in which this is not true. T1 In fact, we can say more: n=1 Gn is dense. Prove this using the fact that a closed subset of a complete metric space is also complete. -
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. -
Bounded Operator - Wikipedia, the Free Encyclopedia
Bounded operator - Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Bounded_operator Bounded operator From Wikipedia, the free encyclopedia In functional analysis, a branch of mathematics, a bounded linear operator is a linear transformation L between normed vector spaces X and Y for which the ratio of the norm of L(v) to that of v is bounded by the same number, over all non-zero vectors v in X. In other words, there exists some M > 0 such that for all v in X The smallest such M is called the operator norm of L. A bounded linear operator is generally not a bounded function; the latter would require that the norm of L(v) be bounded for all v, which is not possible unless Y is the zero vector space. Rather, a bounded linear operator is a locally bounded function. A linear operator on a metrizable vector space is bounded if and only if it is continuous. Contents 1 Examples 2 Equivalence of boundedness and continuity 3 Linearity and boundedness 4 Further properties 5 Properties of the space of bounded linear operators 6 Topological vector spaces 7 See also 8 References Examples Any linear operator between two finite-dimensional normed spaces is bounded, and such an operator may be viewed as multiplication by some fixed matrix. Many integral transforms are bounded linear operators. For instance, if is a continuous function, then the operator defined on the space of continuous functions on endowed with the uniform norm and with values in the space with given by the formula is bounded. -
Note on Operator Algebras
Note on Operator Algebras Takahiro Sagawa Department of Physics, The University of Tokyo 15 December 2010 Contents 1 General Topology 2 2 Hilbert Spaces and Operator Algebras 5 2.1 Hilbert Space . 5 2.2 Bounded Operators . 6 2.3 Trace Class Operators . 8 2.4 von Neumann Algebras . 10 2.5 Maps on von Neumann Algebras . 12 3 Abstract Operator Algebras 13 3.1 C∗-Algebras . 13 3.2 W ∗-algebras . 14 1 Chapter 1 General Topology Topology is an abstract structure that can be built on the set theory. We start with introducing the topological structure by open stets, which is the most standard way. A topological space is a set Ω together with O, a collection of subsets of Ω, satisfying the following properties: ∙ 휙 2 O and Ω 2 O. ∙ If O1 2 O and O2 2 O, then O1 \ O2 2 O. ∙ If O훼 2 O (훼 2 I) for arbitrary set of suffixes, then [훼2I O훼 2 O. An element of O is called an open set. In general, a set may have several topologies. If two topologies satisfy O1 ⊂ O2, then O1 is called weaker than O2, or smaller than O2. Topological structure can be generated by a subset of open spaces. Let B be a collection of subsets of a set Ω. The weakest topology O such that B ⊂ O is called generated by B. We note that such O does not always exist for an arbitrary B. Figure 1.1: An open set and a compact set. We review some important concepts in topological spaces: 2 ∙ If O is an open set, then Ω n O is called a closed set. -
Functional Analysis
Functional Analysis Lecture Notes of Winter Semester 2017/18 These lecture notes are based on my course from winter semester 2017/18. I kept the results discussed in the lectures (except for minor corrections and improvements) and most of their numbering. Typi- cally, the proofs and calculations in the notes are a bit shorter than those given in class. The drawings and many additional oral remarks from the lectures are omitted here. On the other hand, the notes con- tain a couple of proofs (mostly for peripheral statements) and very few results not presented during the course. With `Analysis 1{4' I refer to the class notes of my lectures from 2015{17 which can be found on my webpage. Occasionally, I use concepts, notation and standard results of these courses without further notice. I am happy to thank Bernhard Konrad, J¨orgB¨auerle and Johannes Eilinghoff for their careful proof reading of my lecture notes from 2009 and 2011. Karlsruhe, May 25, 2020 Roland Schnaubelt Contents Chapter 1. Banach spaces2 1.1. Basic properties of Banach and metric spaces2 1.2. More examples of Banach spaces 20 1.3. Compactness and separability 28 Chapter 2. Continuous linear operators 38 2.1. Basic properties and examples of linear operators 38 2.2. Standard constructions 47 2.3. The interpolation theorem of Riesz and Thorin 54 Chapter 3. Hilbert spaces 59 3.1. Basic properties and orthogonality 59 3.2. Orthonormal bases 64 Chapter 4. Two main theorems on bounded linear operators 69 4.1. The principle of uniform boundedness and strong convergence 69 4.2. -
Tutorial on Von Neumann Algebras
Tutorial on von Neumann algebras Adrian Ioana University of California, San Diego Model Theory and Operator Algebras UC Irvine September 20-22, 2017 1/174 the adjoint T ⇤ B(H) given by T ⇠,⌘ = ⇠,T ⇤⌘ ,forall⇠,⌘ H. 2 h i h i 2 the spectrum of T is σ(T )= λ C T λ I not invertible . { 2 | − } Fact: σ(T ) is a compact non-empty subset of C. Definition An operator T B(H)iscalled 2 1 self-adjoint if T = T ⇤. 2 positive if T ⇠,⇠ 0, for all ⇠ H. (positive self-adjoint) h i 2 ) 3 a projection if T = T = T 2 T is the orthogonal projection onto ⇤ , a closed subspace K H. ⇢ 4 a unitary if TT ⇤ = T ⇤T = I . The algebra of bounded linear operators H separable Hilbert space, e.g. `2(N), L2([0, 1], Leb). B(H) algebra of bounded linear operators T : H H, ! i.e. such that T =sup T ⇠ ⇠ =1 < . k k {k k|k k } 1 2/174 the spectrum of T is σ(T )= λ C T λ I not invertible . { 2 | − } Fact: σ(T ) is a compact non-empty subset of C. Definition An operator T B(H)iscalled 2 1 self-adjoint if T = T ⇤. 2 positive if T ⇠,⇠ 0, for all ⇠ H. (positive self-adjoint) h i 2 ) 3 a projection if T = T = T 2 T is the orthogonal projection onto ⇤ , a closed subspace K H. ⇢ 4 a unitary if TT ⇤ = T ⇤T = I . The algebra of bounded linear operators H separable Hilbert space, e.g. -
Mean Ergodic Operators in Fréchet Spaces
Annales Academiæ Scientiarum Fennicæ Mathematica Volumen 34, 2009, 401–436 MEAN ERGODIC OPERATORS IN FRÉCHET SPACES Angela A. Albanese, José Bonet* and Werner J. Ricker Università del Salento, Dipartimento di Matematica “Ennio De Giorgi” C.P. 193, I-73100 Lecce, Italy; [email protected] Universidad Politécnica de Valencia, Instituto Universitario de Matemática Pura y Aplicada Edificio IDI5 (8E), Cubo F, Cuarta Planta, E-46071 Valencia, Spain; [email protected] Katholische Universität Eichstätt-Ingolstadt, Mathematisch-Geographische Fakultät D-85072 Eichstätt, Germany; [email protected] Abstract. Classical results of Pelczynski and of Zippin concerning bases in Banach spaces are extended to the Fréchet space setting, thus answering a question posed by Kalton almost 40 years ago. Equipped with these results, we prove that a Fréchet space with a basis is reflexive (resp. Montel) if and only if every power bounded operator is mean ergodic (resp. uniformly mean ergodic). New techniques are developed and many examples in classical Fréchet spaces are exhibited. 1. Introduction and statement of the main results A continuous linear operator T in a Banach space X (or a locally convex Haus- dorff space, briefly lcHs) is called mean ergodic if the limits 1 Xn (1.1) P x := lim T mx; x 2 X; n!1 n m=1 exist (in the topology of X). von Neumann (1931) proved that unitary operators in Hilbert space are mean ergodic. Ever since, intensive research has been undertaken concerning mean ergodic operators and their applications; for the period up to the 1980’s see [19, Ch. VIII Section 4], [25, Ch. -
247A Notes on Lorentz Spaces Definition 1. for 1 ≤ P < ∞ and F : R D → C We Define (1) Weak(Rd) := Sup Λ∣∣{X
247A Notes on Lorentz spaces Definition 1. For 1 ≤ p < 1 and f : Rd ! C we define ∗ 1=p (1) kfkLp ( d) := sup λ fx : jf(x)j > λg weak R λ>0 and the weak Lp space p d ∗ L ( ) := f : kfk p d < 1 : weak R Lweak(R ) p −p Equivalently, f 2 Lweak if and only if jfx : jf(x)j > λgj . λ . Warning. The quantity in (1) does not define a norm. This is the reason we append the asterisk to the usual norm notation. To make a side-by-side comparison with the usual Lp norm, we note that ZZ 1=p p−1 kfkLp = pλ dλ dx 0≤λ<jf(x)j Z 1 dλ1=p = jfjfj > λgj pλp 0 λ 1=p 1=p = p λjfjfj > λgj p dλ L ((0;1); λ ) and, with the convention that p1=1 = 1, ∗ 1=1 1=p kfkLp = p λjfjfj > λgj 1 dλ : weak L ((0;1); λ ) This suggests the following definition. Definition 2. For 1 ≤ p < 1 and 1 ≤ q ≤ 1 we define the Lorentz space Lp;q(Rd) as the space of measurable functions f for which ∗ 1=q 1=p (2) kfkLp;q := p λjfjfj > λgj q dλ < 1: L ( λ ) p;p p p;1 p From the discussion above, we see that L = L and L = Lweak. Again ∗ k · kLp;q is not a norm in general. Nevertheless, it is positively homogeneous: for all a 2 C, ∗ −1 1=p ∗ (3) kafkLp;q = λ fjfj > jaj λg Lq (dλ/λ) = jaj · kfkLp;q (strictly the case a = 0 should receive separate treatment).