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Weak and Norm Approximate Identities Are Different
Pacific Journal of Mathematics WEAK AND NORM APPROXIMATE IDENTITIES ARE DIFFERENT CHARLES ALLEN JONES AND CHARLES DWIGHT LAHR Vol. 72, No. 1 January 1977 PACIFIC JOURNAL OF MATHEMATICS Vol. 72, No. 1, 1977 WEAK AND NORM APPROXIMATE IDENTITIES ARE DIFFERENT CHARLES A. JONES AND CHARLES D. LAHR An example is given of a convolution measure algebra which has a bounded weak approximate identity, but no norm approximate identity. 1* Introduction* Let A be a commutative Banach algebra, Ar the dual space of A, and ΔA the maximal ideal space of A. A weak approximate identity for A is a net {e(X):\eΛ} in A such that χ(e(λ)α) > χ(α) for all αei, χ e A A. A norm approximate identity for A is a net {e(λ):λeΛ} in A such that ||β(λ)α-α|| >0 for all aeA. A net {e(X):\eΛ} in A is bounded and of norm M if there exists a positive number M such that ||e(λ)|| ^ M for all XeΛ. It is well known that if A has a bounded weak approximate identity for which /(e(λ)α) —>/(α) for all feA' and αeA, then A has a bounded norm approximate identity [1, Proposition 4, page 58]. However, the situation is different if weak convergence is with re- spect to ΔA and not A'. An example is given in § 2 of a Banach algebra A which has a weak approximate identity, but does not have a norm approximate identity. This algebra provides a coun- terexample to a theorem of J. -
The Heisenberg Group Fourier Transform
THE HEISENBERG GROUP FOURIER TRANSFORM NEIL LYALL Contents 1. Fourier transform on Rn 1 2. Fourier analysis on the Heisenberg group 2 2.1. Representations of the Heisenberg group 2 2.2. Group Fourier transform 3 2.3. Convolution and twisted convolution 5 3. Hermite and Laguerre functions 6 3.1. Hermite polynomials 6 3.2. Laguerre polynomials 9 3.3. Special Hermite functions 9 4. Group Fourier transform of radial functions on the Heisenberg group 12 References 13 1. Fourier transform on Rn We start by presenting some standard properties of the Euclidean Fourier transform; see for example [6] and [4]. Given f ∈ L1(Rn), we define its Fourier transform by setting Z fb(ξ) = e−ix·ξf(x)dx. Rn n ih·ξ If for h ∈ R we let (τhf)(x) = f(x + h), then it follows that τdhf(ξ) = e fb(ξ). Now for suitable f the inversion formula Z f(x) = (2π)−n eix·ξfb(ξ)dξ, Rn holds and we see that the Fourier transform decomposes a function into a continuous sum of characters (eigenfunctions for translations). If A is an orthogonal matrix and ξ is a column vector then f[◦ A(ξ) = fb(Aξ) and from this it follows that the Fourier transform of a radial function is again radial. In particular the Fourier transform −|x|2/2 n of Gaussians take a particularly nice form; if G(x) = e , then Gb(ξ) = (2π) 2 G(ξ). In general the Fourier transform of a radial function can always be explicitly expressed in terms of a Bessel 1 2 NEIL LYALL transform; if g(x) = g0(|x|) for some function g0, then Z ∞ n 2−n n−1 gb(ξ) = (2π) 2 g0(r)(r|ξ|) 2 J n−2 (r|ξ|)r dr, 0 2 where J n−2 is a Bessel function. -
Surjective Isometries on Grassmann Spaces 11
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Repository of the Academy's Library SURJECTIVE ISOMETRIES ON GRASSMANN SPACES FERNANDA BOTELHO, JAMES JAMISON, AND LAJOS MOLNAR´ Abstract. Let H be a complex Hilbert space, n a given positive integer and let Pn(H) be the set of all projections on H with rank n. Under the condition dim H ≥ 4n, we describe the surjective isometries of Pn(H) with respect to the gap metric (the metric induced by the operator norm). 1. Introduction The study of isometries of function spaces or operator algebras is an important research area in functional analysis with history dating back to the 1930's. The most classical results in the area are the Banach-Stone theorem describing the surjective linear isometries between Banach spaces of complex- valued continuous functions on compact Hausdorff spaces and its noncommutative extension for general C∗-algebras due to Kadison. This has the surprising and remarkable consequence that the surjective linear isometries between C∗-algebras are closely related to algebra isomorphisms. More precisely, every such surjective linear isometry is a Jordan *-isomorphism followed by multiplication by a fixed unitary element. We point out that in the aforementioned fundamental results the underlying structures are algebras and the isometries are assumed to be linear. However, descriptions of isometries of non-linear structures also play important roles in several areas. We only mention one example which is closely related with the subject matter of this paper. This is the famous Wigner's theorem that describes the structure of quantum mechanical symmetry transformations and plays a fundamental role in the probabilistic aspects of quantum theory. -
The Hahn-Banach Theorem and Infima of Convex Functions
The Hahn-Banach theorem and infima of convex functions Hajime Ishihara School of Information Science Japan Advanced Institute of Science and Technology (JAIST) Nomi, Ishikawa 923-1292, Japan first CORE meeting, LMU Munich, 7 May, 2016 Normed spaces Definition A normed space is a linear space E equipped with a norm k · k : E ! R such that I kxk = 0 $ x = 0, I kaxk = jajkxk, I kx + yk ≤ kxk + kyk, for each x; y 2 E and a 2 R. Note that a normed space E is a metric space with the metric d(x; y) = kx − yk: Definition A Banach space is a normed space which is complete with respect to the metric. Examples For 1 ≤ p < 1, let p N P1 p l = f(xn) 2 R j n=0 jxnj < 1g and define a norm by P1 p 1=p k(xn)k = ( n=0 jxnj ) : Then lp is a (separable) Banach space. Examples Classically the normed space 1 N l = f(xn) 2 R j (xn) is boundedg with the norm k(xn)k = sup jxnj n is an inseparable Banach space. However, constructively, it is not a normed space. Linear mappings Definition A mapping T between linear spaces E and F is linear if I T (ax) = aTx, I T (x + y) = Tx + Ty for each x; y 2 E and a 2 R. Definition A linear functional f on a linear space E is a linear mapping from E into R. Bounded linear mappings Definition A linear mapping T between normed spaces E and F is bounded if there exists c ≥ 0 such that kTxk ≤ ckxk for each x 2 E. -
On Order Preserving and Order Reversing Mappings Defined on Cones of Convex Functions MANUSCRIPT
ON ORDER PRESERVING AND ORDER REVERSING MAPPINGS DEFINED ON CONES OF CONVEX FUNCTIONS MANUSCRIPT Lixin Cheng∗ Sijie Luo School of Mathematical Sciences Yau Mathematical Sciences Center Xiamen University Tsinghua University Xiamen 361005, China Beijing 100084, China [email protected] [email protected] ABSTRACT In this paper, we first show that for a Banach space X there is a fully order reversing mapping T from conv(X) (the cone of all extended real-valued lower semicontinuous proper convex functions defined on X) onto itself if and only if X is reflexive and linearly isomorphic to its dual X∗. Then we further prove the following generalized “Artstein-Avidan-Milman” representation theorem: For every fully order reversing mapping T : conv(X) → conv(X) there exist a linear isomorphism ∗ ∗ ∗ U : X → X , x0, ϕ0 ∈ X , α> 0 and r0 ∈ R so that ∗ (Tf)(x)= α(Ff)(Ux + x0)+ hϕ0, xi + r0, ∀x ∈ X, where F : conv(X) → conv(X∗) is the Fenchel transform. Hence, these resolve two open questions. We also show several representation theorems of fully order preserving mappings de- fined on certain cones of convex functions. For example, for every fully order preserving mapping S : semn(X) → semn(X) there is a linear isomorphism U : X → X so that (Sf)(x)= f(Ux), ∀f ∈ semn(X), x ∈ X, where semn(X) is the cone of all lower semicontinuous seminorms on X. Keywords Fenchel transform · order preserving mapping · order reversing mapping · convex function · Banach space 1 Introduction An elegant theorem of Artstein-Avidan and Milman [5] states that every fully order reversing (resp. -
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. -
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 Study of Uniform Boundedness
CANADIAN THESES H pap^^ are missmg, contact the university whch granted the Sil manque des pages, veuiflez communlquer avec I'univer- degree.-. sit6 qui a mf&B b grade. henaPsty coWngMed materiats (journal arbcks. puMished Les documents qui tont c&j& robjet dun dfoit dautew (Wicks tests, etc.) are not filmed. de revue, examens pubiles, etc.) ne scmt pas mlcrofiimes. Repockbm in full or in part of this film is governed by the lareproduction, m&ne partielk, de ce microfibn est soumise . Gawc&n CoWnght Act, R.S.C. 1970, c. G30. P!ease read B h Ldcanaden ne sur b droit &auteur, SRC 1970, c. C30. the alrhmfm fmwhich mpanythfs tksts. Veuikz pm&e des fmhdautortsetion qui A ac~ompegnentcette Mse. - - - -- - - -- - -- ppp- -- - THIS DISSERTATlON LA W&E A - - -- EXACTLY AS RECEIVED NOUS L'AVONS RECUE d the fitsr. da prdrer w de vervke des exsaplairas du fib, *i= -4 wit- tM arrhor's rrrittm lsrmissitn. (Y .~-rmntrep&ds sns rrror;s~m&rite de /.auefa. e-zEEEsXs-a--==-- , THE RZ~lREHEHTFOR THE DEGREB OF in the Wpartesent R.T. SBantunga, 1983 SLW PRllSER BNFJERSI'PY Decenber 1983 Hae: Degree: Title of Thesis: _ C, Godsil ~srtsrnalgnamniner I3e-t of Hathematics Shmn Praser University 'i hereby grant to Simn Fraser University tba right to .lend ,y 'hcsis, or ~.ndadessay 4th title of which is 5taun helor) f to users ot the 5imFrasar University Library, and to mke partial or r'H.lgtrt copies oniy for such users 5r in response to a request fram the 1 Ibrary oh any other university, or other educationat institution, on its orn behaif or for one of its users. -
A Topology for Operator Modules Over W*-Algebras Bojan Magajna
Journal of Functional AnalysisFU3203 journal of functional analysis 154, 1741 (1998) article no. FU973203 A Topology for Operator Modules over W*-Algebras Bojan Magajna Department of Mathematics, University of Ljubljana, Jadranska 19, Ljubljana 1000, Slovenia E-mail: Bojan.MagajnaÄuni-lj.si Received July 23, 1996; revised February 11, 1997; accepted August 18, 1997 dedicated to professor ivan vidav in honor of his eightieth birthday Given a von Neumann algebra R on a Hilbert space H, the so-called R-topology is introduced into B(H), which is weaker than the norm and stronger than the COREultrastrong operator topology. A right R-submodule X of B(H) is closed in the Metadata, citation and similar papers at core.ac.uk Provided byR Elsevier-topology - Publisher if and Connector only if for each b #B(H) the right ideal, consisting of all a # R such that ba # X, is weak* closed in R. Equivalently, X is closed in the R-topology if and only if for each b #B(H) and each orthogonal family of projections ei in R with the sum 1 the condition bei # X for all i implies that b # X. 1998 Academic Press 1. INTRODUCTION Given a C*-algebra R on a Hilbert space H, a concrete operator right R-module is a subspace X of B(H) (the algebra of all bounded linear operators on H) such that XRX. Such modules can be characterized abstractly as L -matricially normed spaces in the sense of Ruan [21], [11] which are equipped with a completely contractive R-module multi- plication (see [6] and [9]). -
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. -
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.