FINITE DIMENSIONAL NORMED SPACES in This Course We Shall Study the Classical Theory of Banach Spaces with an Eye to Its Quantita
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Projective Tensor Products, Injective Tensor Products, and Dual Relations on Operator Spaces
University of Windsor Scholarship at UWindsor Electronic Theses and Dissertations Theses, Dissertations, and Major Papers 1-1-2006 Projective tensor products, injective tensor products, and dual relations on operator spaces. Fuhua Chen University of Windsor Follow this and additional works at: https://scholar.uwindsor.ca/etd Recommended Citation Chen, Fuhua, "Projective tensor products, injective tensor products, and dual relations on operator spaces." (2006). Electronic Theses and Dissertations. 7096. https://scholar.uwindsor.ca/etd/7096 This online database contains the full-text of PhD dissertations and Masters’ theses of University of Windsor students from 1954 forward. These documents are made available for personal study and research purposes only, in accordance with the Canadian Copyright Act and the Creative Commons license—CC BY-NC-ND (Attribution, Non-Commercial, No Derivative Works). Under this license, works must always be attributed to the copyright holder (original author), cannot be used for any commercial purposes, and may not be altered. Any other use would require the permission of the copyright holder. Students may inquire about withdrawing their dissertation and/or thesis from this database. For additional inquiries, please contact the repository administrator via email ([email protected]) or by telephone at 519-253-3000ext. 3208. P r o je c t iv e T e n so r P r o d u c t s , In je c t iv e T e n so r P r o d u c t s , a n d D ual R elatio ns on O p e r a t o r S paces by Fuhua Chen A Thesis Submitted to the Faculty of Graduate Studies and Research through Mathematics and Statistics in Partial Fulfillment of the Requirements of the Degree of Master of Science at the University of Windsor Windsor, Ontario, Canada 2006 © 2006 Fuhua Chen Reproduced with permission of the copyright owner. -
Grothendieck's Tensor Norms
Grothendieck's tensor norms Vandana Shivaji College, University of Delhi, India April, 2015 Vandana Grothendieck's tensor norms Overview Grothendieck's tensor norms Operator spaces Tensor products of Operator spaces Schur tensor product Vandana Grothendieck's tensor norms Grothendieck's tensor norms A Banach space is a complete normed space. For Banach spaces X and Y , X ⊗ Y = spanfx ⊗ y : x 2 X; y 2 Y g, where x ⊗ y is the functional on B(X∗ × Y ∗; C) given by x ⊗ y(f; g) = f(x)g(y) for f 2 X∗ and g 2 Y ∗. For a pair of arbitrary Banach spaces X and Y , the norm on X ⊗ Y induced by the embedding X ⊗ Y ! B(X∗ × Y ∗; C) is known as Banach space injective tensor norm. That is , for u 2 X ⊗ Y , the Banach space injective tensor norm is defined to be n n o X ∗ ∗ kukλ = sup f(xi)g(yi) : f 2 X1 ; g 2 Y1 : i=1 Vandana Grothendieck's tensor norms Grothendieck's tensor norms Question is How can we norm on X ⊗ Y ? n X kx ⊗ ykα ≤ kxkkyk, then, for u = xi ⊗ yi, by triangle's i=1 n X inequality it follows that kukα ≤ kxikkyik. Since this holds for i=1 n X every representation of u, so we have kukα ≤ inff kxikkyikg. i=1 For a pair of arbitrary Banach spaces X and Y and u an element in the algebraic tensor product X ⊗ Y , the Banach space projective tensor norm is defined to be n n X X kukγ = inff kxikkyik : u = xi ⊗ yi; n 2 Ng: i=1 i=1 X ⊗γ Y will denote the completion of X ⊗ Y with respect to this norm. -
Grothendieck-Type Inequalities in Combinatorial Optimization
GROTHENDIECK-TYPE INEQUALITIES IN COMBINATORIAL OPTIMIZATION SUBHASH KHOT AND ASSAF NAOR Abstract. We survey connections of the Grothendieck inequality and its variants to com- binatorial optimization and computational complexity. Contents 1. Introduction 2 1.1. Assumptions from computational complexity 3 1.2. Convex and semidefinite programming 4 2. Applications of the classical Grothendieck inequality 5 2.1. Cut norm estimation 5 2.1.1. Szemer´edipartitions 8 2.1.2. Frieze-Kannan matrix decomposition 10 2.1.3. Maximum acyclic subgraph 11 2.1.4. Linear equations modulo 2 14 2.2. Rounding 16 3. The Grothendieck constant of a graph 18 3.1. Algorithmic consequences 20 3.1.1. Spin glasses 20 3.1.2. Correlation clustering 20 arXiv:1108.2464v1 [cs.DS] 11 Aug 2011 4. Kernel clustering and the propeller conjecture 21 5. The Lp Grothendieck problem 25 6. Higher rank Grothendieck inequalities 28 7. Hardness of approximation 29 References 31 S. K. was partially supported by NSF CAREER grant CCF-0833228, NSF Expeditions grant CCF- 0832795, an NSF Waterman award, and BSF grant 2008059. A. N. was partially supported by NSF Expe- ditions grant CCF-0832795, BSF grant 2006009, and the Packard Foundation. 1 1. Introduction The Grothendieck inequality asserts that there exists a universal constant K 2 (0; 1) such that for every m; n 2 N and every m × n matrix A = (aij) with real entries we have ( m n ) X X m n n+m−1 max aijhxi; yji : fxigi=1; fyjgj=1 ⊆ S i=1 j=1 ( m n ) X X m n 6 K max aij"iδj : f"igi=1; fδjgj=1 ⊆ {−1; 1g : (1) i=1 j=1 k Pk Here, and in what follows, the standard scalar product on R is denoted hx; yi = i=1 xiyi k k−1 k Pk 2 and the Euclidean sphere in R is denoted S = fx 2 R : i=1 xi = 1g. -
Grothendieck's Theorem, Past and Present
Grothendieck’s Theorem, past and present by Gilles Pisier∗ Texas A&M University College Station, TX 77843, U. S. A. and Universit´eParis VI Equipe d’Analyse, Case 186, 75252 Paris Cedex 05, France January 26, 2011 Abstract Probably the most famous of Grothendieck’s contributions to Banach space theory is the result that he himself described as “the fundamental theorem in the metric theory of tensor products”. That is now commonly referred to as “Grothendieck’s theorem” (GT in short), or sometimes as “Grothendieck’s inequality”. This had a major impact first in Banach space theory (roughly after 1968), then, later on, in C∗-algebra theory, (roughly after 1978). More recently, in this millennium, a new version of GT has been successfully developed in the framework of “operator spaces” or non-commutative Banach spaces. In addition, GT independently surfaced in several quite unrelated fields: in connection with Bell’s inequality in quantum mechanics, in graph theory where the Grothendieck constant of a graph has been introduced and in computer science where the Grothendieck inequality is invoked to replace certain NP hard problems by others that can be treated by “semidefinite programming’ and hence solved in polynomial time. In this expository paper, we present a review of all these topics, starting from the original GT. We concentrate on the more recent developments and merely outline those of the first Banach space period since detailed accounts of that are already available, for instance the author’s 1986 CBMS notes. ∗Partially supported by NSF grant 0503688 Contents 1 Introduction 1 2 Classical GT 7 3 The Grothendieck constants 15 4 The Hahn-Banach argument 17 5 The “little” GT 20 6 Banach spaces satisfying GT and operator ideals 22 7 Non-commutative GT 23 8 Non-commutative “little GT” 25 9 Non-commutative Khintchine inequality 26 10 Maurey factorization 32 11 Best constants (Non-commutative case) 33 12 C∗-algebra tensor products, Nuclearity 35 13 Operator spaces, c.b. -
Distinguished Property in Tensor Products and Weak* Dual Spaces
axioms Article Distinguished Property in Tensor Products and Weak* Dual Spaces Salvador López-Alfonso 1 , Manuel López-Pellicer 2,* and Santiago Moll-López 3 1 Department of Architectural Constructions, Universitat Politècnica de València, 46022 Valencia, Spain; [email protected] 2 Emeritus and IUMPA, Universitat Politècnica de València, 46022 Valencia, Spain 3 Department of Applied Mathematics, Universitat Politècnica de València, 46022 Valencia, Spain; [email protected] * Correspondence: [email protected] 0 Abstract: A local convex space E is said to be distinguished if its strong dual Eb has the topology 0 0 0 0 b(E , (Eb) ), i.e., if Eb is barrelled. The distinguished property of the local convex space Cp(X) of real- valued functions on a Tychonoff space X, equipped with the pointwise topology on X, has recently aroused great interest among analysts and Cp-theorists, obtaining very interesting properties and nice characterizations. For instance, it has recently been obtained that a space Cp(X) is distinguished if and only if any function f 2 RX belongs to the pointwise closure of a pointwise bounded set in C(X). The extensively studied distinguished properties in the injective tensor products Cp(X) ⊗# E and in Cp(X, E) contrasts with the few distinguished properties of injective tensor products related to the dual space Lp(X) of Cp(X) endowed with the weak* topology, as well as to the weak* dual of Cp(X, E). To partially fill this gap, some distinguished properties in the injective tensor product space Lp(X) ⊗# E are presented and a characterization of the distinguished property of the weak* dual of Cp(X, E) for wide classes of spaces X and E is provided. -
Arxiv:Math/9201256V1 [Math.RT] 1 Jan 1992 Naso Lblaayi N Geometry and Vol
Annals of Global Analysis and Geometry Vol. 8, No. 3 (1990), 299–313 THE MOMENT MAPPING FOR UNITARY REPRESENTATIONS Peter W. Michor Institut f¨ur Mathematik der Universit¨at Wien, Austria Abstract. For any unitary representation of an arbitrary Lie group I construct a moment mapping from the space of smooth vectors of the representation into the dual of the Lie algebra. This moment mapping is equivariant and smooth. For the space of analytic vectors the same construction is possible and leads to a real analytic moment mapping. Table of contents 1.Introduction . .. .. .. .. .. .. .. .. .. .. 1 2.Calculusofsmoothmappings . 2 3.Calculusofholomorphicmappings . 5 4.Calculusofrealanalyticmappings . 6 5.TheSpaceofSmoothVectors . 7 6.Themodelforthemomentmapping . 8 7. Hamiltonian Mechanics on H∞ .................... 9 8. The moment mapping for a unitary representation . .... 11 9.Therealanalyticmomentmapping . 13 1. Introduction arXiv:math/9201256v1 [math.RT] 1 Jan 1992 With the help of the cartesian closed calculus for smooth mappings as explained in [F-K] we can show, that for any Lie group and for any unitary representation its restriction to the space of smooth vectors is smooth. The imaginary part of the hermitian inner product restricts to a ”weak” symplectic structure on the vector space of smooth vectors. This gives rise to the Poisson bracket on a suitably chosen space of smooth functions on the space of smooth vectors. The derivative of the representation on the space of smooth vectors is a symplectic action of the Lie algebra, which can be lifted to a Hamiltonian action, i.e. a Lie algebra homomorphism from the Lie algebra into the function space with the Poisson bracket. -
On the Geometry of Projective Tensor Products
ON THE GEOMETRY OF PROJECTIVE TENSOR PRODUCTS OHAD GILADI, JOSCHA PROCHNO, CARSTEN SCHUTT,¨ NICOLE TOMCZAK-JAEGERMANN, AND ELISABETH WERNER n Abstract. In this work, we study the volume ratio of the projective tensor products `p ⊗π n n `q ⊗π `r with 1 ≤ p ≤ q ≤ r ≤ 1. We obtain asymptotic formulas that are sharp in almost all cases. As a consequence of our estimates, these spaces allow for a nearly Euclidean decomposition of Kaˇsintype whenever 1 ≤ p ≤ q ≤ r ≤ 2 or 1 ≤ p ≤ 2 ≤ r ≤ 1 and q = 2. Also, from the Bourgain-Milman bound on the volume ratio of Banach spaces in terms of their cotype 2 constant, we obtain information on the cotype of these 3-fold projective tensor products. Our results naturally generalize to k-fold products `n ⊗ · · · ⊗ `n with k 2 p1 π π pk N and 1 ≤ p1 ≤ · · · ≤ pk ≤ 1. 1. Introduction In the geometry of Banach spaces the volume ratio vr(X) of an n-dimensional normed space X is defined as the n-th root of the volume of the unit ball in X divided by the volume of its John ellipsoid. This notion plays an important role in the local theory of Banach spaces and has significant applications in approximation theory. It formally originates in the works [Sza78] and [STJ80], which were influenced by the famous paper of B. Kaˇsin[Kaˇs77] on nearly Euclidean orthogonal decompositions. Kaˇsindiscovered that for arbitrary n 2 N, 2n the space `1 contains two orthogonal subspaces which are nearly Euclidean, meaning that n their Banach-Mazur distance to `2 is bounded by an absolute constant. -
Metric Embeddings and Geometric Inequalities
Metric embeddings and geometric inequalities Lectures by Professor Assaf Naor Scribes: Holden Lee and Kiran Vodrahalli April 27, 2016 MAT529 Metric embeddings and geometric inequalities 2 Contents 1 The Ribe Program7 1 The Ribe Program................................7 2 Bourgain's Theorem implies Ribe's Theorem.................. 14 2.1 Bourgain's discretization theorem.................... 15 2.2 Bourgain's Theorem implies Ribe's Theorem.............. 17 2 Restricted invertibility principle 19 1 Restricted invertibility principle......................... 19 1.1 The first restricted invertibility principles................ 19 1.2 A general restricted invertibility principle................ 21 2 Ky Fan maximum principle........................... 23 3 Finding big subsets................................ 26 3.1 Little Grothendieck inequality...................... 26 3.1.1 Tightness of Grothendieck's inequality............ 29 3.2 Pietsch Domination Theorem...................... 30 3.3 A projection bound............................ 32 3.4 Sauer-Shelah Lemma........................... 33 4 Proof of RIP.................................... 34 4.1 Step 1................................... 34 4.2 Step 2................................... 36 3 Bourgain's Discretization Theorem 47 1 Outline....................................... 47 1.1 Reduction to smooth norm........................ 48 2 Bourgain's almost extension theorem...................... 49 2.1 Lipschitz extension problem....................... 50 2.2 John ellipsoid.............................. -
Tensor Products of Convex Cones, Part I: Mapping Properties, Faces, and Semisimplicity
Tensor Products of Convex Cones, Part I: Mapping Properties, Faces, and Semisimplicity Josse van Dobben de Bruyn 24 September 2020 Abstract The tensor product of two ordered vector spaces can be ordered in more than one way, just as the tensor product of normed spaces can be normed in multiple ways. Two natural orderings have received considerable attention in the past, namely the ones given by the projective and injective (or biprojective) cones. This paper aims to show that these two cones behave similarly to their normed counterparts, and furthermore extends the study of these two cones from the algebraic tensor product to completed locally convex tensor products. The main results in this paper are the following: (i) drawing parallels with the normed theory, we show that the projective/injective cone has mapping properties analogous to those of the projective/injective norm; (ii) we establish direct formulas for the lineality space of the projective/injective cone, in particular providing necessary and sufficient conditions for the cone to be proper; (iii) we show how to construct faces of the projective/injective cone from faces of the base cones, in particular providing a complete characterization of the extremal rays of the projective cone; (iv) we prove that the projective/injective tensor product of two closed proper cones is contained in a closed proper cone (at least in the algebraic tensor product). 1 Introduction 1.1 Outline Tensor products of ordered (topological) vector spaces have been receiving attention for more than 50 years ([Mer64], [HF68], [Pop68], [PS69], [Pop69], [DS70], [vGK10], [Wor19]), but the focus has mostly been on Riesz spaces ([Sch72], [Fre72], [Fre74], [Wit74], [Sch74, §IV.7], [Bir76], [FT79], [Nie82], [GL88], [Nie88], [Bla16]) or on finite-dimensional spaces ([BL75], [Bar76], [Bar78a], [Bar78b], [Bar81], [BLP87], [ST90], [Tam92], [Mul97], [Hil08], [HN18], [ALPP19]). -
Convenient Vector Spaces, Convenient Manifolds and Differential Linear Logic
Convenient Vector Spaces, Convenient Manifolds and Differential Linear Logic Richard Blute University of Ottawa ongoing discussions with Geoff Crutwell, Thomas Ehrhard, Alex Hoffnung, Christine Tasson June 20, 2011 Richard Blute Convenient Vector Spaces, Convenient Manifolds and Differential Linear Logic Goals Develop a theory of (smooth) manifolds based on differential linear logic. Or perhaps develop a differential linear logic based on manifolds. Convenient vector spaces were recently shown to be a model. There is a well-developed theory of convenient manifolds, including infinite-dimensional manifolds. Convenient manifolds reveal additional structure not seen in finite dimensions. In particular, the notion of tangent space is much more complex. Synthetic differential geometry should also provide information. Convenient vector spaces embed into an extremely good model. Richard Blute Convenient Vector Spaces, Convenient Manifolds and Differential Linear Logic Convenient vector spaces (Fr¨olicher,Kriegl) Definition A vector space is locally convex if it is equipped with a topology such that each point has a neighborhood basis of convex sets, and addition and scalar multiplication are continuous. Locally convex spaces are the most well-behaved topological vector spaces, and most studied in functional analysis. Note that in any topological vector space, one can take limits and hence talk about derivatives of curves. A curve is smooth if it has derivatives of all orders. The analogue of Cauchy sequences in locally convex spaces are called Mackey-Cauchy sequences. The convergence of Mackey-Cauchy sequences implies the convergence of all Mackey-Cauchy nets. The following is taken from a long list of equivalences. Richard Blute Convenient Vector Spaces, Convenient Manifolds and Differential Linear Logic Convenient vector spaces II: Definition Theorem Let E be a locally convex vector space. -
Grothendieck Proved a Theorem That He Called “Le Th´Eor`Eme Fondamental De La Th´Eoriemetrique Des Produits Tensoriels”
THE GROTHENDIECK CONSTANT IS STRICTLY SMALLER THAN KRIVINE'S BOUND MARK BRAVERMAN, KONSTANTIN MAKARYCHEV, YURY MAKARYCHEV, AND ASSAF NAOR Abstract. The (real) Grothendieck constant KG is the infimum over those K 2 (0; 1) such that for every m; n 2 N and every m × n real matrix (aij) we have m n m n X X X X max aijhxi; yji 6 K max aij"iδj: fx gm ;fy gn ⊆Sn+m−1 f" gm ;fδ gn ⊆{−1;1g i i=1 j j=1 i=1 j=1 i i=1 j j=1 i=1 j=1 The classical Grothendieck inequality asserts the non-obvious fact that the above inequal- ity does hold true for some K 2 (0; 1) that is independent of m; n and (aij). Since Grothendieck's 1953 discovery of this powerful theorem, it has found numerous applica- tions in a variety of areas, but despite attracting a lot of attention, the exact value of the Grothendieck constant KG remains a mystery. The last progress on this problem was in 1977, when Krivine proved that K π p and conjectured that his bound is opti- G 6 2 log(1+ 2) mal. Krivine's conjecture has been restated repeatedly since 1977, resulting in focusing the subsequent research on the search for examples of matrices (aij) which exhibit (asymptot- ically, as m; n ! 1) a lower bound on KG that matches Krivine's bound. Here we obtain an improved Grothendieck inequality that holds for all matrices (aij) and yields a bound K < π p − " for some effective constant " > 0. -
Grothendieck Inequalities for Semidefinite Programs with Rank Constraint
THEORY OF COMPUTING, Volume 10 (4), 2014, pp. 77–105 www.theoryofcomputing.org Grothendieck Inequalities for Semidefinite Programs with Rank Constraint Jop Briët∗ Fernando Mário de Oliveira Filho† Frank Vallentin‡ Received May 4, 2012; Revised January 21, 2014; Published May 31, 2014 Abstract: Grothendieck inequalities are fundamental inequalities which are frequently used in many areas of mathematics and computer science. They can be interpreted as upper bounds for the integrality gap between two optimization problems: a difficult semidefinite program with rank-1 constraint and its easy semidefinite relaxation where the rank constraint is dropped. For instance, the integrality gap of the Goemans-Williamson approximation algorithm for MAX CUT can be seen as a Grothendieck inequality. In this paper we consider Grothendieck inequalities for ranks greater than 1 and we give two applications: approximating ground states in the n-vector model in statistical mechanics and XOR games in quantum information theory. ACM Classification: G.1.6, G.2.2 AMS Classification: 68W25, 90C22 Key words and phrases: randomized rounding, Grothendieck inequality, n-vector model, XOR games 1 Introduction V Let G = (V;E) be a graph with finite vertex set V and edge set E ⊆ 2 . Let A: V ×V ! R be a symmetric matrix whose rows and columns are indexed by the vertex set of G, and r be a positive integer. The ∗Supported by Vici grant 639.023.302 from the Netherlands Organization for Scientific Research (NWO), by the European Commission under the Integrated Project Qubit Applications (QAP) funded by the IST directorate as Contract Number 015848, by the Dutch BSIK/BRICKS project and by the European grant QCS.