Integral Representation Theorems in Topological Vector Spaces
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Vector Measures with Variation in a Banach Function Space
VECTOR MEASURES WITH VARIATION IN A BANACH FUNCTION SPACE O. BLASCO Departamento de An´alisis Matem´atico, Universidad de Valencia, Doctor Moliner, 50 E-46100 Burjassot (Valencia), Spain E-mail:[email protected] PABLO GREGORI Departament de Matem`atiques, Universitat Jaume I de Castell´o, Campus Riu Sec E-12071 Castell´o de la Plana (Castell´o), Spain E-mail:[email protected] Let E be a Banach function space and X be an arbitrary Banach space. Denote by E(X) the K¨othe-Bochner function space defined as the set of measurable functions f :Ω→ X such that the nonnegative functions fX :Ω→ [0, ∞) are in the lattice E. The notion of E-variation of a measure —which allows to recover the p- variation (for E = Lp), Φ-variation (for E = LΦ) and the general notion introduced by Gresky and Uhl— is introduced. The space of measures of bounded E-variation VE (X) is then studied. It is shown, amongother thingsand with some restriction ∗ ∗ of absolute continuity of the norms, that (E(X)) = VE (X ), that VE (X) can be identified with space of cone absolutely summingoperators from E into X and that E(X)=VE (X) if and only if X has the RNP property. 1. Introduction The concept of variation in the frame of vector measures has been fruitful in several areas of the functional analysis, such as the description of the duality of vector-valued function spaces such as certain K¨othe-Bochner function spaces (Gretsky and Uhl10, Dinculeanu7), the reformulation of operator ideals such as the cone absolutely summing operators (Blasco4), and the Hardy spaces of harmonic function (Blasco2,3). -
Combinatorics in Banach Space Theory Lecture 2
Combinatorics in Banach space theory Lecture 2 Now, we will derive the promised corollaries from Rosenthal's lemma. First, following [Ros70], we will show how this lemma implies Nikod´ym's uniform boundedness principle for bounded vector measures. Before doing this we need to recall some definitions. Definition 2.4. Let F be a set algebra. By a partition of a given set E 2 F we mean Sk a finite collection fE1;:::;Ekg of pairwise disjoint members of F such that j=1Ej = E. We denote Π(E) the set of all partitions of E. Let also X be a Banach space and µ: F ! X be a finitely additive set function (called a vector measure). The variation of µ is a function jµj: F ! [0; 1] given by ( ) X jµj(E) = sup kµ(A)k: π 2 Π(E) : A2π The semivariation of µ is a function kµk: F ! [0; 1] given by ∗ ∗ kµk = sup jx µj(E): x 2 BX∗ : By a straightforward calculation, one may check that the variation jµj is always finitely additive, whereas the semivariation kµk is monotone and finitely subadditive. Of course, we always have kµk 6 jµj. Moreover, since we know how the functionals on the scalar space (R or C) look like, it is easily seen that for scalar-valued measures the notions of variation and semivariation coincide. By saying that a vector measure µ: F ! X is bounded we mean that kµk is finitely valued. This is in turn equivalent to saying that the range of µ is a bounded subset of X. -
2 Hilbert Spaces You Should Have Seen Some Examples Last Semester
2 Hilbert spaces You should have seen some examples last semester. The simplest (finite-dimensional) ex- C • A complex Hilbert space H is a complete normed space over whose norm is derived from an ample is Cn with its standard inner product. It’s worth recalling from linear algebra that if V is inner product. That is, we assume that there is a sesquilinear form ( , ): H H C, linear in · · × → an n-dimensional (complex) vector space, then from any set of n linearly independent vectors we the first variable and conjugate linear in the second, such that can manufacture an orthonormal basis e1, e2,..., en using the Gram-Schmidt process. In terms of this basis we can write any v V in the form (f ,д) = (д, f ), ∈ v = a e , a = (v, e ) (f , f ) 0 f H, and (f , f ) = 0 = f = 0. i i i i ≥ ∀ ∈ ⇒ ∑ The norm and inner product are related by which can be derived by taking the inner product of the equation v = aiei with ei. We also have n ∑ (f , f ) = f 2. ∥ ∥ v 2 = a 2. ∥ ∥ | i | i=1 We will always assume that H is separable (has a countable dense subset). ∑ Standard infinite-dimensional examples are l2(N) or l2(Z), the space of square-summable As usual for a normed space, the distance on H is given byd(f ,д) = f д = (f д, f д). • • ∥ − ∥ − − sequences, and L2(Ω) where Ω is a measurable subset of Rn. The Cauchy-Schwarz and triangle inequalities, • √ (f ,д) f д , f + д f + д , | | ≤ ∥ ∥∥ ∥ ∥ ∥ ≤ ∥ ∥ ∥ ∥ 2.1 Orthogonality can be derived fairly easily from the inner product. -
Banach Space Properties of V of a Vector Measure
proceedings of the american mathematical society Volume 123, Number 12. December 1995 BANACHSPACE PROPERTIES OF V OF A VECTOR MEASURE GUILLERMO P. CURBERA (Communicated by Dale Alspach) Abstract. We consider the space L'(i>) of real functions which are integrable with respect to a measure v with values in a Banach space X . We study type and cotype for Lx{v). We study conditions on the measure v and the Banach space X that imply that Ll(v) is a Hilbert space, or has the Dunford-Pettis property. We also consider weak convergence in Lx(v). 1. Introduction Given a vector measure v with values in a Banach space X, Lx(v) denotes the space of (classes of) real functions which are integrable with respect to v in the sense of Bartle, Dunford and Schwartz [BDS] and Lewis [L-l]. This space has been studied by Kluvanek and Knowles [KK], Thomas [T] and Okada [O]. It is an order continuous Banach lattice with weak unit. In [C-l, Theorem 8] we have identified the class of spaces Lx(v) , showing that every order continuous Banach lattice with weak unit can be obtained, order isometrically, as L1 of a suitable vector measure. A natural question arises: what is the relation between, on the one hand, the properties of the Banach space X and the measure v, and, on the other hand, the properties of the resulting space Lx(v) . The complexity of the situ- ation is shown by the following example: the measures, defined over Lebesgue measurable sets of [0,1], vx(A) = m(A) £ R, v2(A) = Xa e £'([0, 1]) and v3 — (]"Ar„(t)dt) £ Co, where rn are the Rademacher functions, generate, order isometrically, the same space, namely 7J([0, 1]). -
FLOWS of MEASURES GENERATED by VECTOR FIELDS 1. Introduction Every Sufficiently Smooth and Bounded Vector Field V in the Euclide
FLOWS OF MEASURES GENERATED BY VECTOR FIELDS EMANUELE PAOLINI AND EUGENE STEPANOV Abstract. The scope of the paper is twofold. We show that for a large class of measurable vector fields in the sense of N. Weaver (i.e. derivations over the algebra of Lipschitz functions), called in the paper laminated, the notion of integral curves may be naturally defined and characterized (when appropriate) by an ODE. We further show, that for such vector fields the notion of a flow of the given positive Borel measure similar to the classical one generated by a smooth vector field (in a space with smooth structure) may be defined in a reasonable way, so that the measure “flows along” the appropriately understood integral curves of the given vector field and the classical continuity equation is satisfied in the weak sense. 1. Introduction Every sufficiently smooth and bounded vector field V in the Euclidean space E = Rn is well-known to generate a canonical flow of a given finite Borel measure t + t µ in E by setting µt := ϕ µ, t R , where ϕ (x) := θ(t), θ standing for the V # ∈ V unique solution to the differential equation (1.1) θ˙(t)= V (θ(t)) satisfying the initial condition θ(0) = x. Such a flow satisfies the continuity equation ∂µ (1.2) t + div v µ =0 ∂t t t + in the weak sense in E R , where vt : E E is some velocity field (of course, non unique for the given×V , but in particular,→ this equation is satisfied in this case with vt := V ). -
Algebras and Orthogonal Vector Measures
proceedings of the american mathematical society Volume 110, Number 3, November 1990 STATES ON IT*-ALGEBRAS AND ORTHOGONAL VECTOR MEASURES JAN HAMHALTER (Communicated by William D. Sudderth) Abstract. We show that every state on a If*-algebra sf without type I2 direct summand is induced by an orthogonal vector measure on sf . This result may find an application in quantum stochastics [1, 7]. Particularly, it allows us to find a simple formula for the transition probability between two states on sf [3, 8], 1. Preliminaries Here we fix some notation and recall basic facts about Hilbert-Schmidt op- erators (for details, see [9]). Let H be a complex Hilbert space and let 3§'HA) denote the set of all linear bounded operators on H . An operator A e 33(H) is said to be a trace class operator if the series ^2aeI(Aea, ea) is absolutely convergent for an orthonormal basis (ea)ae! of //. In this case the sum J2a€¡(Aea, ea) does not depend on the choice of the basis (ea)a€¡ and is called a trace of A (abbreviated Tr,4). Let us denote by CX(H) the set of all trace class operators on //. Then Tr AB = Tr BA whenever the product AB belongs to CX(H). Suppose that A e 33(H). Then A is called a Hilbert-Schmidt operator if IMII2 = {X3„e/II^JI } < 00 for some (and therefore for any) orthonor- mal basis (en)n€, of //. Let us denote by C2(H) the set of all Hilbert- Schmidt operators on //. Thus, C2(H) is a two-sided ideal in 33(H), and CX(H) c C2(H). -
Maxwell's Equations in Differential Form
M03_RAO3333_1_SE_CHO3.QXD 4/9/08 1:17 PM Page 71 CHAPTER Maxwell’s Equations in Differential Form 3 In Chapter 2 we introduced Maxwell’s equations in integral form. We learned that the quantities involved in the formulation of these equations are the scalar quantities, elec- tromotive force, magnetomotive force, magnetic flux, displacement flux, charge, and current, which are related to the field vectors and source densities through line, surface, and volume integrals. Thus, the integral forms of Maxwell’s equations,while containing all the information pertinent to the interdependence of the field and source quantities over a given region in space, do not permit us to study directly the interaction between the field vectors and their relationships with the source densities at individual points. It is our goal in this chapter to derive the differential forms of Maxwell’s equations that apply directly to the field vectors and source densities at a given point. We shall derive Maxwell’s equations in differential form by applying Maxwell’s equations in integral form to infinitesimal closed paths, surfaces, and volumes, in the limit that they shrink to points. We will find that the differential equations relate the spatial variations of the field vectors at a given point to their temporal variations and to the charge and current densities at that point. In this process we shall also learn two important operations in vector calculus, known as curl and divergence, and two related theorems, known as Stokes’ and divergence theorems. 3.1 FARADAY’S LAW We recall from the previous chapter that Faraday’s law is given in integral form by d E # dl =- B # dS (3.1) CC dt LS where S is any surface bounded by the closed path C.In the most general case,the elec- tric and magnetic fields have all three components (x, y,and z) and are dependent on all three coordinates (x, y,and z) in addition to time (t). -
Continuity Properties of Vector Measures
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS 86. 268-280 (1982) Continuity Properties of Vector Measures CECILIA H. BROOK Department of Mathematical Sciences, Northern Illinois Unirersity, DeKalb, Illinois 60115 Submitted b! G.-C Rota 1. INTRODUCTION This paper is a sequel to [ I 1. Using projections in the universal measure space of W. H. Graves [ 6 1, we study continuity and orthogonality properties of vector measures. To each strongly countably additive measure 4 on an algebra .d with range in a complete locally convex space we associate a projection P,, which may be thought of as the support of @ and as a projection-valued measure. Our main result is that, as measures, # and P, are mutually continuous. It follows that measures may be compared by comparing their projections. The projection P, induces a decomposition of vector measures which turns out to be Traynor’s general Lebesgue decomposition [8) relative to qs. Those measures $ for which algebraic d-continuity is equivalent to $- continuity are characterized in terms of projections, while $-continuity is shown to be equivalent to &order-continuity whenever -d is a u-algebra. Using projections associated with nonnegative measures, we approximate every 4 uniformly on the algebra ,d by vector measures which have control measures. Last, we interpret our results algebraically. Under the equivalence relation of mutual continuity, and with the order induced by continuity, the collection of strongly countably additive measures on .d which take values in complete spaces forms a complete Boolean algebra 1rV, which is isomorphic to the Boolean algebra of projections in the universal measure space. -
THE RANGE of a VECTOR MEASURE the Purpose of This Note Is to Prove That the Range of a Countably Additive Finite Measure with Va
THE RANGE OF A VECTOR MEASURE PAUL R. HALMOS The purpose of this note is to prove that the range of a countably additive finite measure with values in a finite-dimensional real vector space is closed and, in the non-atomic case, convex. These results were first proved (in 1940) by A. Liapounoff.1 In 1945 K. R. Buch (independently) proved the part of the statement concerning closure for non-negative measures of dimension one or two.2 In 1947 I offered a proof of Buch's results which, however, was correct in the one- dimensional case only.8 In this paper I present a simplified proof of LiapounofPs results. Let X be any set and let S be a <r-field of subsets of X (called the measurable set of X). A measure /i (or, more precisely, an iV-dimen- sional measure (#i, • • • , fix)) is a (bounded) countably additive function of the sets of S with values in iV-dimensional, real vector space (in which the "length" |&| + • • • +|£JV| of a vector ? = (?i» • • • » &v) is denoted by |£|). The measure (/xi, • • • /*#) is non-negative if fXi(E) ^0 for every ££S and i«= 1, • • • , N. For a numerical (one-dimensional) measure /x0, Mo*0E) will denote the total variation of /xo on £; in general, if /x = (jiu • • • , Mtf), M* will denote the non-negative measure (jit!*, • • • , /$). The length |JU*| =Mi*+ • • • +M#* is always a non-negative numerical measure.4 Presented to the Society, September 3,1947 ; received by the editors July 10,1947. 1 Sur les fonctions-vecteurs complètement additives, Bull. -
Some C*-Algebras with a Single Generator*1 )
transactions of the american mathematical society Volume 215, 1976 SOMEC*-ALGEBRAS WITH A SINGLEGENERATOR*1 ) BY CATHERINE L. OLSEN AND WILLIAM R. ZAME ABSTRACT. This paper grew out of the following question: If X is a com- pact subset of Cn, is C(X) ® M„ (the C*-algebra of n x n matrices with entries from C(X)) singly generated? It is shown that the answer is affirmative; in fact, A ® M„ is singly generated whenever A is a C*-algebra with identity, generated by a set of n(n + l)/2 elements of which n(n - l)/2 are selfadjoint. If A is a separable C*-algebra with identity, then A ® K and A ® U are shown to be sing- ly generated, where K is the algebra of compact operators in a separable, infinite- dimensional Hubert space, and U is any UHF algebra. In all these cases, the gen- erator is explicitly constructed. 1. Introduction. This paper grew out of a question raised by Claude Scho- chet and communicated to us by J. A. Deddens: If X is a compact subset of C, is C(X) ® M„ (the C*-algebra ofnxn matrices with entries from C(X)) singly generated? We show that the answer is affirmative; in fact, A ® Mn is singly gen- erated whenever A is a C*-algebra with identity, generated by a set of n(n + l)/2 elements of which n(n - l)/2 are selfadjoint. Working towards a converse, we show that A ® M2 need not be singly generated if A is generated by a set con- sisting of four elements. -
And Varifold-Based Registration of Lung Vessel and Airway Trees
Current- and Varifold-Based Registration of Lung Vessel and Airway Trees Yue Pan, Gary E. Christensen, Oguz C. Durumeric, Sarah E. Gerard, Joseph M. Reinhardt The University of Iowa, IA 52242 {yue-pan-1, gary-christensen, oguz-durumeric, sarah-gerard, joe-reinhardt}@uiowa.edu Geoffrey D. Hugo Virginia Commonwealth University, Richmond, VA 23298 [email protected] Abstract 1. Introduction Registration of lung CT images is important for many radiation oncology applications including assessing and Registering lung CT images is an important problem adapting to anatomical changes, accumulating radiation for many applications including tracking lung motion over dose for planning or assessment, and managing respiratory the breathing cycle, tracking anatomical and function motion. For example, variation in the anatomy during radio- changes over time, and detecting abnormal mechanical therapy introduces uncertainty between the planned and de- properties of the lung. This paper compares and con- livered radiation dose and may impact the appropriateness trasts current- and varifold-based diffeomorphic image of the originally-designed treatment plan. Frequent imaging registration approaches for registering tree-like structures during radiotherapy accompanied by accurate longitudinal of the lung. In these approaches, curve-like structures image registration facilitates measurement of such variation in the lung—for example, the skeletons of vessels and and its effect on the treatment plan. The cumulative dose airways segmentation—are represented by currents or to the target and normal tissue can be assessed by mapping varifolds in the dual space of a Reproducing Kernel Hilbert delivered dose to a common reference anatomy and com- Space (RKHS). Current and varifold representations are paring to the prescribed dose. -
Arxiv:1802.08667V5 [Stat.ML] 13 Apr 2021 Lwrta 1 Than Slower Asna Eoo N,Aogagvnsqec Fmodels)
Manuscript submitted to The Econometrics Journal, pp. 1–49. De-Biased Machine Learning of Global and Local Parameters Using Regularized Riesz Representers Victor Chernozhukov†, Whitney K. Newey†, and Rahul Singh† †MIT Economics, 50 Memorial Drive, Cambridge MA 02142, USA. E-mail: [email protected], [email protected], [email protected] Summary We provide adaptive inference methods, based on ℓ1 regularization, for regular (semi-parametric) and non-regular (nonparametric) linear functionals of the conditional expectation function. Examples of regular functionals include average treatment effects, policy effects, and derivatives. Examples of non-regular functionals include average treatment effects, policy effects, and derivatives conditional on a co- variate subvector fixed at a point. We construct a Neyman orthogonal equation for the target parameter that is approximately invariant to small perturbations of the nui- sance parameters. To achieve this property, we include the Riesz representer for the functional as an additional nuisance parameter. Our analysis yields weak “double spar- sity robustness”: either the approximation to the regression or the approximation to the representer can be “completely dense” as long as the other is sufficiently “sparse”. Our main results are non-asymptotic and imply asymptotic uniform validity over large classes of models, translating into honest confidence bands for both global and local parameters. Keywords: Neyman orthogonality, Gaussian approximation, sparsity 1. INTRODUCTION Many statistical objects of interest can be expressed as a linear functional of a regression function (or projection, more generally). Examples include global parameters: average treatment effects, policy effects from changing the distribution of or transporting regres- sors, and average directional derivatives, as well as their local versions defined by taking averages over regions of shrinking volume.