A SEMINORM with SQUARE PROPERTY on a BANACH ALGEBRA IS SUBMULTIPLICATIVE A. Then the Following Hold
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												  Duality for Outer $ L^ P \Mu (\Ell^ R) $ Spaces and Relation to Tent Spacesp r DUALITY FOR OUTER Lµpℓ q SPACES AND RELATION TO TENT SPACES MARCO FRACCAROLI p r Abstract. We prove that the outer Lµpℓ q spaces, introduced by Do and Thiele, are isomorphic to Banach spaces, and we show the expected duality properties between them for 1 ă p ď8, 1 ď r ă8 or p “ r P t1, 8u uniformly in the finite setting. In the case p “ 1, 1 ă r ď8, we exhibit a counterexample to uniformity. We show that in the upper half space setting these properties hold true in the full range 1 ď p,r ď8. These results are obtained via greedy p r decompositions of functions in Lµpℓ q. As a consequence, we establish the p p r equivalence between the classical tent spaces Tr and the outer Lµpℓ q spaces in the upper half space. Finally, we give a full classification of weak and strong type estimates for a class of embedding maps to the upper half space with a fractional scale factor for functions on Rd. 1. Introduction The Lp theory for outer measure spaces discussed in [13] generalizes the classical product, or iteration, of weighted Lp quasi-norms. Since we are mainly interested in positive objects, we assume every function to be nonnegative unless explicitly stated. We first focus on the finite setting. On the Cartesian product X of two finite sets equipped with strictly positive weights pY,µq, pZ,νq, we can define the classical product, or iterated, L8Lr,LpLr spaces for 0 ă p, r ă8 by the quasi-norms 1 r r kfkL8ppY,µq,LrpZ,νqq “ supp νpzqfpy,zq q yPY zÿPZ ´1 r 1 “ suppµpyq ωpy,zqfpy,zq q r , yPY zÿPZ p 1 r r p kfkLpppY,µq,LrpZ,νqq “ p µpyqp νpzqfpy,zq q q , arXiv:2001.05903v1 [math.CA] 16 Jan 2020 yÿPY zÿPZ where we denote by ω “ µ b ν the induced weight on X.
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												  Noncommutative Uniform AlgebrasNoncommutative Uniform Algebras Mati Abel and Krzysztof Jarosz Abstract. We show that a real Banach algebra A such that a2 = a 2 , for a A is a subalgebra of the algebra C (X) of continuous quaternion valued functions on a compact setk kX. ∈ H ° ° ° ° 1. Introduction A well known Hirschfeld-Zelazkoú Theorem [5](seealso[7]) states that for a complex Banach algebra A the condition (1.1) a2 = a 2 , for a A k k ∈ implies that (i) A is commutative, and further° ° implies that (ii) A must be of a very speciÞc form, namely it ° ° must be isometrically isomorphic with a uniformly closed subalgebra of CC (X). We denote here by CC (X)the complex Banach algebra of all continuous functions on a compact set X. The obvious question about the validity of the same conclusion for real Banach algebras is immediately dismissed with an obvious counterexample: the non commutative algebra H of quaternions. However it turns out that the second part (ii) above is essentially also true in the real case. We show that the condition (1.1) implies, for a real Banach algebra A,thatA is isometrically isomorphic with a subalgebra of CH (X) - the algebra of continuous quaternion valued functions on acompactsetX. That result is in fact a consequence of a theorem by Aupetit and Zemanek [1]. We will also present several related results and corollaries valid for real and complex Banach and topological algebras. To simplify the notation we assume that the algebras under consideration have units, however, like in the case of the Hirschfeld-Zelazkoú Theorem, the analogous results can be stated for none unital algebras as one can formally add aunittosuchanalgebra.
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												  Boundedness in Linear Topological SpacesBOUNDEDNESS IN LINEAR TOPOLOGICAL SPACES BY S. SIMONS Introduction. Throughout this paper we use the symbol X for a (real or complex) linear space, and the symbol F to represent the basic field in question. We write R+ for the set of positive (i.e., ^ 0) real numbers. We use the term linear topological space with its usual meaning (not necessarily Tx), but we exclude the case where the space has the indiscrete topology (see [1, 3.3, pp. 123-127]). A linear topological space is said to be a locally bounded space if there is a bounded neighbourhood of 0—which comes to the same thing as saying that there is a neighbourhood U of 0 such that the sets {(1/n) U} (n = 1,2,—) form a base at 0. In §1 we give a necessary and sufficient condition, in terms of invariant pseudo- metrics, for a linear topological space to be locally bounded. In §2 we discuss the relationship of our results with other results known on the subject. In §3 we introduce two ways of classifying the locally bounded spaces into types in such a way that each type contains exactly one of the F spaces (0 < p ^ 1), and show that these two methods of classification turn out to be identical. Also in §3 we prove a metrization theorem for locally bounded spaces, which is related to the normal metrization theorem for uniform spaces, but which uses a different induction procedure. In §4 we introduce a large class of linear topological spaces which includes the locally convex spaces and the locally bounded spaces, and for which one of the more important results on boundedness in locally convex spaces is valid.
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												  Superadditive and Subadditive Transformations of Integrals and Aggregation FunctionsView metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Portsmouth University Research Portal (Pure) Superadditive and subadditive transformations of integrals and aggregation functions Salvatore Greco⋆12, Radko Mesiar⋆⋆34, Fabio Rindone⋆⋆⋆1, and Ladislav Sipeky†3 1 Department of Economics and Business 95029 Catania, Italy 2 University of Portsmouth, Portsmouth Business School, Centre of Operations Research and Logistics (CORL), Richmond Building, Portland Street, Portsmouth PO1 3DE, United Kingdom 3 Department of Mathematics and Descriptive Geometry, Faculty of Civil Engineering Slovak University of Technology 810 05 Bratislava, Slovakia 4 Institute of Theory of Information and Automation Czech Academy of Sciences Prague, Czech Republic Abstract. We propose the concepts of superadditive and of subadditive trans- formations of aggregation functions acting on non-negative reals, in particular of integrals with respect to monotone measures. We discuss special properties of the proposed transforms and links between some distinguished integrals. Superaddi- tive transformation of the Choquet integral, as well as of the Shilkret integral, is shown to coincide with the corresponding concave integral recently introduced by Lehrer. Similarly the transformation of the Sugeno integral is studied. Moreover, subadditive transformation of distinguished integrals is also discussed. Keywords: Aggregation function; superadditive and subadditive transformations; fuzzy integrals. 1 Introduction The concepts of subadditivity and superadditivity are very important in economics. For example, consider a production function A : Rn R assigning to each vector of pro- + → + duction factors x = (x1,...,xn) the corresponding output A(x1,...,xn). If one has available resources given by the vector x =(x1,..., xn), then, the production function A assigns the output A(x1,..., xn).
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												  A Mini-Introduction to Information TheoryA Mini-Introduction To Information Theory Edward Witten School of Natural Sciences, Institute for Advanced Study Einstein Drive, Princeton, NJ 08540 USA Abstract This article consists of a very short introduction to classical and quantum information theory. Basic properties of the classical Shannon entropy and the quantum von Neumann entropy are described, along with related concepts such as classical and quantum relative entropy, conditional entropy, and mutual information. A few more detailed topics are considered in the quantum case. arXiv:1805.11965v5 [hep-th] 4 Oct 2019 Contents 1 Introduction 2 2 Classical Information Theory 2 2.1 ShannonEntropy ................................... .... 2 2.2 ConditionalEntropy ................................. .... 4 2.3 RelativeEntropy .................................... ... 6 2.4 Monotonicity of Relative Entropy . ...... 7 3 Quantum Information Theory: Basic Ingredients 10 3.1 DensityMatrices .................................... ... 10 3.2 QuantumEntropy................................... .... 14 3.3 Concavity ......................................... .. 16 3.4 Conditional and Relative Quantum Entropy . ....... 17 3.5 Monotonicity of Relative Entropy . ...... 20 3.6 GeneralizedMeasurements . ...... 22 3.7 QuantumChannels ................................... ... 24 3.8 Thermodynamics And Quantum Channels . ...... 26 4 More On Quantum Information Theory 27 4.1 Quantum Teleportation and Conditional Entropy . ......... 28 4.2 Quantum Relative Entropy And Hypothesis Testing . ......... 32 4.3 Encoding
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												  Regularity Conditions for Banach Function AlgebrasRegularity conditions for Banach function algebras Dr J. F. Feinstein University of Nottingham June 2009 1 1 Useful sources A very useful text for the material in this mini-course is the book Banach Algebras and Automatic Continuity by H. Garth Dales, London Mathematical Society Monographs, New Series, Volume 24, The Clarendon Press, Oxford, 2000. In particular, many of the examples and conditions discussed here may be found in Chapter 4 of that book. We shall refer to this book throughout as the book of Dales. Most of my e-prints are available from www.maths.nott.ac.uk/personal/jff/Papers Several of my research and teaching presentations are available from www.maths.nott.ac.uk/personal/jff/Beamer 2 2 Introduction to normed algebras and Banach algebras 2.1 Some problems to think about Those who have seen much of this introductory material before may wish to think about some of the following problems. We shall return to these problems at suitable points in this course. Problem 2.1.1 (Easy using standard theory!) It is standard that the set of all rational functions (quotients of polynomials) with complex coefficients is a field: this is a special case of the “field of fractions" of an integral domain. Question: Is there an algebra norm on this field (regarded as an algebra over C)? 3 Problem 2.1.2 (Very hard!) Does there exist a pair of sequences (λn), (an) of non-zero complex numbers such that (i) no two of the an are equal, P1 (ii) n=1 jλnj < 1, (iii) janj < 2 for all n 2 N, and yet, (iv) for all z 2 C, 1 X λn exp (anz) = 0? n=1 Gap to fill in 4 Problem 2.1.3 Denote by C[0; 1] the \trivial" uniform algebra of all continuous, complex-valued functions on [0; 1].
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												  Uniqueness of Von Neumann Bornology in Locally C∗-AlgebrasScientiae Mathematicae Japonicae Online, e-2009 91 UNIQUENESS OF VON NEUMANN BORNOLOGY IN LOCALLY C∗-ALGEBRAS. A BORNOLOGICAL ANALOGUE OF JOHNSON’S THEOREM M. Oudadess Received May 31, 2008; revised March 20, 2009 Abstract. All locally C∗- structures on a commutative complex algebra have the same bound structure. It is also shown that a Mackey complete C∗-convex algebra is semisimple. By the well-known Johnson’s theorem [4], there is on a given complex semi-simple algebra a unique (up to an isomorphism) Banach algebra norm. R. C. Carpenter extended this result to commutative Fr´echet locally m-convex algebras [3]. Without metrizability, it is not any more valid even in the rich context of locally C∗-convex algebras. Below there are given telling examples where even a C∗-algebra structure is involved. We follow the terminology of [5], pp. 101-102. Let E be an involutive algebra and p a vector space seminorm on E. We say that p is a C∗-seminorm if p(x∗x)=[p(x)]2, for every x. An involutive topological algebra whose topology is defined by a (saturated) family of C∗-seminorms is called a C∗-convex algebra. A complete C∗-convex algebra is called a locally C∗-algebra (by Inoue). A Fr´echet C∗-convex algebra is a metrizable C∗- convex algebra, that is equivalently a metrizable locally C∗-algebra, or also a Fr´echet locally C∗-algebra. All the bornological notions can be found in [6]. The references for m-convexity are [5], [8] and [9]. Let us recall for convenience that the bounded structure (bornology) of a locally convex algebra (l.c.a.)(E,τ) is the collection Bτ of all the subsets B of E which are bounded in the sense of Kolmogorov and von Neumann, that is B is absorbed by every neighborhood of the origin (see e.g.
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												  Chapter 2 C -AlgebrasChapter 2 C∗-algebras This chapter is mainly based on the first chapters of the book [Mur90]. Material bor- rowed from other references will be specified. 2.1 Banach algebras Definition 2.1.1. A Banach algebra C is a complex vector space endowed with an associative multiplication and with a norm k · k which satisfy for any A; B; C 2 C and α 2 C (i) (αA)B = α(AB) = A(αB), (ii) A(B + C) = AB + AC and (A + B)C = AC + BC, (iii) kABk ≤ kAkkBk (submultiplicativity) (iv) C is complete with the norm k · k. One says that C is abelian or commutative if AB = BA for all A; B 2 C . One also says that C is unital if 1 2 C , i.e. if there exists an element 1 2 C with k1k = 1 such that 1B = B = B1 for all B 2 C . A subalgebra J of C is a vector subspace which is stable for the multiplication. If J is norm closed, it is a Banach algebra in itself. Examples 2.1.2. (i) C, Mn(C), B(H), K (H) are Banach algebras, where Mn(C) denotes the set of n × n-matrices over C. All except K (H) are unital, and K (H) is unital if H is finite dimensional. (ii) If Ω is a locally compact topological space, C0(Ω) and Cb(Ω) are abelian Banach algebras, where Cb(Ω) denotes the set of all bounded and continuous complex func- tions from Ω to C, and C0(Ω) denotes the subset of Cb(Ω) of functions f which vanish at infinity, i.e.
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												  Fact Sheet Functional AnalysisFact Sheet Functional Analysis Literature: Hackbusch, W.: Theorie und Numerik elliptischer Differentialgleichungen. Teubner, 1986. Knabner, P., Angermann, L.: Numerik partieller Differentialgleichungen. Springer, 2000. Triebel, H.: H¨ohere Analysis. Harri Deutsch, 1980. Dobrowolski, M.: Angewandte Funktionalanalysis, Springer, 2010. 1. Banach- and Hilbert spaces Let V be a real vector space. Normed space: A norm is a mapping k · k : V ! [0; 1), such that: kuk = 0 , u = 0; (definiteness) kαuk = jαj · kuk; α 2 R; u 2 V; (positive scalability) ku + vk ≤ kuk + kvk; u; v 2 V: (triangle inequality) The pairing (V; k · k) is called a normed space. Seminorm: In contrast to a norm there may be elements u 6= 0 such that kuk = 0. It still holds kuk = 0 if u = 0. Comparison of two norms: Two norms k · k1, k · k2 are called equivalent if there is a constant C such that: −1 C kuk1 ≤ kuk2 ≤ Ckuk1; u 2 V: If only one of these inequalities can be fulfilled, e.g. kuk2 ≤ Ckuk1; u 2 V; the norm k · k1 is called stronger than the norm k · k2. k · k2 is called weaker than k · k1. Topology: In every normed space a canonical topology can be defined. A subset U ⊂ V is called open if for every u 2 U there exists a " > 0 such that B"(u) = fv 2 V : ku − vk < "g ⊂ U: Convergence: A sequence vn converges to v w.r.t. the norm k · k if lim kvn − vk = 0: n!1 1 A sequence vn ⊂ V is called Cauchy sequence, if supfkvn − vmk : n; m ≥ kg ! 0 for k ! 1.
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												  An Upper Bound on the Size of Diamond-Free Families of SetsView metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Repository of the Academy's Library An upper bound on the size of diamond-free families of sets Dániel Grósz∗ Abhishek Methuku† Casey Tompkins‡ Abstract Let La(n, P ) be the maximum size of a family of subsets of [n] = {1, 2,...,n} not containing P as a (weak) subposet. The diamond poset, denoted Q2, is defined on four elements x,y,z,w with the relations x < y,z and y,z < w. La(n, P ) has been studied for many posets; one of the major n open problems is determining La(n, Q2). It is conjectured that La(n, Q2) = (2+ o(1))⌊n/2⌋, and infinitely many significantly different, asymptotically tight constructions are known. Studying the average number of sets from a family of subsets of [n] on a maximal chain in the Boolean lattice 2[n] has been a fruitful method. We use a partitioning of the maximal chains and n introduce an induction method to show that La(n, Q2) ≤ (2.20711 + o(1))⌊n/2⌋, improving on the n earlier bound of (2.25 + o(1))⌊n/2⌋ by Kramer, Martin and Young. 1 Introduction Let [n]= 1, 2,...,n . The Boolean lattice 2[n] is defined as the family of all subsets of [n]= 1, 2,...,n , and the ith{ level of 2}[n] refers to the collection of all sets of size i. In 1928, Sperner proved the{ following} well-known theorem. Theorem 1.1 (Sperner [24]).
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												  Class Notes, Functional Analysis 7212Class notes, Functional Analysis 7212 Ovidiu Costin Contents 1 Banach Algebras 2 1.1 The exponential map.....................................5 1.2 The index group of B = C(X) ...............................6 1.2.1 p1(X) .........................................7 1.3 Multiplicative functionals..................................7 1.3.1 Multiplicative functionals on C(X) .........................8 1.4 Spectrum of an element relative to a Banach algebra.................. 10 1.5 Examples............................................ 19 1.5.1 Trigonometric polynomials............................. 19 1.6 The Shilov boundary theorem................................ 21 1.7 Further examples....................................... 21 1.7.1 The convolution algebra `1(Z) ........................... 21 1.7.2 The return of Real Analysis: the case of L¥ ................... 23 2 Bounded operators on Hilbert spaces 24 2.1 Adjoints............................................ 24 2.2 Example: a space of “diagonal” operators......................... 30 2.3 The shift operator on `2(Z) ................................. 32 2.3.1 Example: the shift operators on H = `2(N) ................... 38 3 W∗-algebras and measurable functional calculus 41 3.1 The strong and weak topologies of operators....................... 42 4 Spectral theorems 46 4.1 Integration of normal operators............................... 51 4.2 Spectral projections...................................... 51 5 Bounded and unbounded operators 54 5.1 Operations..........................................
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												  5 Norms on Linear Spaces5 Norms on Linear Spaces 5.1 Introduction In this chapter we study norms on real or complex linear linear spaces. Definition 5.1. Let F = (F, {0, 1, +, −, ·}) be the real or the complex field. A semi-norm on an F -linear space V is a mapping ν : V −→ R that satisfies the following conditions: (i) ν(x + y) ≤ ν(x)+ ν(y) (the subadditivity property of semi-norms), and (ii) ν(ax)= |a|ν(x), for x, y ∈ V and a ∈ F . By taking a = 0 in the second condition of the definition we have ν(0)=0 for every semi-norm on a real or complex space. A semi-norm can be defined on every linear space. Indeed, if B is a basis of V , B = {vi | i ∈ I}, J is a finite subset of I, and x = i∈I xivi, define νJ (x) as P 0 if x = 0, νJ (x)= ( j∈J |aj | for x ∈ V . We leave to the readerP the verification of the fact that νJ is indeed a seminorm. Theorem 5.2. If V is a real or complex linear space and ν : V −→ R is a semi-norm on V , then ν(x − y) ≥ |ν(x) − ν(y)|, for x, y ∈ V . Proof. We have ν(x) ≤ ν(x − y)+ ν(y), so ν(x) − ν(y) ≤ ν(x − y). (5.1) 160 5 Norms on Linear Spaces Since ν(x − y)= |− 1|ν(y − x) ≥ ν(y) − ν(x) we have −(ν(x) − ν(y)) ≤ ν(x) − ν(y). (5.2) The Inequalities 5.1 and 5.2 give the desired inequality.