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Integral Representation of a Linear Functional on Function Spaces
INTEGRAL REPRESENTATION OF LINEAR FUNCTIONALS ON FUNCTION SPACES MEHDI GHASEMI Abstract. Let A be a vector space of real valued functions on a non-empty set X and L : A −! R a linear functional. Given a σ-algebra A, of subsets of X, we present a necessary condition for L to be representable as an integral with respect to a measure µ on X such that elements of A are µ-measurable. This general result then is applied to the case where X carries a topological structure and A is a family of continuous functions and naturally A is the Borel structure of X. As an application, short solutions for the full and truncated K-moment problem are presented. An analogue of Riesz{Markov{Kakutani representation theorem is given where Cc(X) is replaced with whole C(X). Then we consider the case where A only consists of bounded functions and hence is equipped with sup-norm. 1. Introduction A positive linear functional on a function space A ⊆ RX is a linear map L : A −! R which assigns a non-negative real number to every function f 2 A that is globally non-negative over X. The celebrated Riesz{Markov{Kakutani repre- sentation theorem states that every positive functional on the space of continuous compactly supported functions over a locally compact Hausdorff space X, admits an integral representation with respect to a regular Borel measure on X. In symbols R L(f) = X f dµ, for all f 2 Cc(X). Riesz's original result [12] was proved in 1909, for the unit interval [0; 1]. -
Some Properties of Gromov–Hausdorff Distances
Discrete Comput Geom (2012) 48:416–440 DOI 10.1007/s00454-012-9406-8 Some Properties of Gromov–Hausdorff Distances Facundo Mémoli Received: 25 March 2011 / Revised: 6 December 2011 / Accepted: 7 February 2012 / Published online: 29 February 2012 © Springer Science+Business Media, LLC 2012 Abstract The Gromov–Hausdorff distance between metric spaces appears to be a useful tool for modeling some object matching procedures. Since its conception it has been mainly used by pure mathematicians who are interested in the topology generated by this distance, and quantitative consequences of the definition are not very common. As a result, only few lower bounds for the distance are known, and the stability of many metric invariants is not understood. This paper aims at clarifying some of these points by proving several results dealing with explicit lower bounds for the Gromov–Hausdorff distance which involve different standard metric invari- ants. We also study a modified version of the Gromov–Hausdorff distance which is motivated by practical applications and both prove a structural theorem for it and study its topological equivalence to the usual notion. This structural theorem pro- vides a decomposition of the modified Gromov–Hausdorff distance as the supremum over a family of pseudo-metrics, each of which involves the comparison of certain discrete analogues of curvature. This modified version relates the standard Gromov– Hausdorff distance to the work of Boutin and Kemper, and Olver. Keywords Gromov–Hausdorff distance · Metric geometry · Curvature sets 1 Introduction The Gromov–Hausdorff distance is a useful tool for studying topological properties of families of metric spaces. -
Set Theory, Including the Axiom of Choice) Plus the Negation of CH
ANNALS OF ~,IATltEMATICAL LOGIC - Volume 2, No. 2 (1970) pp. 143--178 INTERNAL COHEN EXTENSIONS D.A.MARTIN and R.M.SOLOVAY ;Tte RockeJ~'ller University and University (.~t CatiJbrnia. Berkeley Received 2 l)ecemt)er 1969 Introduction Cohen [ !, 2] has shown that tile continuum hypothesis (CH) cannot be proved in Zermelo-Fraenkel set theory. Levy and Solovay [9] have subsequently shown that CH cannot be proved even if one assumes the existence of a measurable cardinal. Their argument in tact shows that no large cardinal axiom of the kind present;y being considered by set theorists can yield a proof of CH (or of its negation, of course). Indeed, many set theorists - including the authors - suspect that C1t is false. But if we reject CH we admit Gurselves to be in a state of ignorance about a great many questions which CH resolves. While CH is a power- full assertion, its negation is in many ways quite weak. Sierpinski [ 1 5 ] deduces propcsitions there called C l - C82 from CH. We know of none of these propositions which is decided by the negation of CH and only one of them (C78) which is decided if one assumes in addition that a measurable cardinal exists. Among the many simple questions easily decided by CH and which cannot be decided in ZF (Zerme!o-Fraenkel set theory, including the axiom of choice) plus the negation of CH are tile following: Is every set of real numbers of cardinality less than tha't of the continuum of Lebesgue measure zero'? Is 2 ~0 < 2 ~ 1 ? Is there a non-trivial measure defined on all sets of real numbers? CIhis third question could be decided in ZF + not CH only in the unlikely event t Tile second author received support from a Sloan Foundation fellowship and tile National Science Foundation Grant (GP-8746). -
On Stochastic Distributions and Currents
NISSUNA UMANA INVESTIGAZIONE SI PUO DIMANDARE VERA SCIENZIA S’ESSA NON PASSA PER LE MATEMATICHE DIMOSTRAZIONI LEONARDO DA VINCI vol. 4 no. 3-4 2016 Mathematics and Mechanics of Complex Systems VINCENZO CAPASSO AND FRANCO FLANDOLI ON STOCHASTIC DISTRIBUTIONS AND CURRENTS msp MATHEMATICS AND MECHANICS OF COMPLEX SYSTEMS Vol. 4, No. 3-4, 2016 dx.doi.org/10.2140/memocs.2016.4.373 ∩ MM ON STOCHASTIC DISTRIBUTIONS AND CURRENTS VINCENZO CAPASSO AND FRANCO FLANDOLI Dedicated to Lucio Russo, on the occasion of his 70th birthday In many applications, it is of great importance to handle random closed sets of different (even though integer) Hausdorff dimensions, including local infor- mation about initial conditions and growth parameters. Following a standard approach in geometric measure theory, such sets may be described in terms of suitable measures. For a random closed set of lower dimension with respect to the environment space, the relevant measures induced by its realizations are sin- gular with respect to the Lebesgue measure, and so their usual Radon–Nikodym derivatives are zero almost everywhere. In this paper, how to cope with these difficulties has been suggested by introducing random generalized densities (dis- tributions) á la Dirac–Schwarz, for both the deterministic case and the stochastic case. For the last one, mean generalized densities are analyzed, and they have been related to densities of the expected values of the relevant measures. Ac- tually, distributions are a subclass of the larger class of currents; in the usual Euclidean space of dimension d, currents of any order k 2 f0; 1;:::; dg or k- currents may be introduced. -
Resonance Van Hove Singularities in Wave Kinetics
Resonance Van Hove Singularities in Wave Kinetics Yi-Kang Shi1 and Gregory L. Eyink1;2 (1) Department of Applied Mathematics & Statistics and (2) Department of Physics & Astronomy, The Johns Hopkins University, Baltimore, MD, USA Abstract Wave kinetic theory has been developed to describe the statistical dynamics of weakly nonlinear, dispersive waves. However, we show that systems which are generally dispersive can have resonant sets of wave modes with identical group velocities, leading to a local breakdown of dispersivity. This shows up as a geometric singularity of the resonant manifold and possibly as an infinite phase measure in the collision integral. Such singularities occur widely for classical wave systems, including acoustical waves, Rossby waves, helical waves in rotating fluids, light waves in nonlinear optics and also in quantum transport, e.g. kinetics of electron-hole excitations (matter waves) in graphene. These singularities are the exact analogue of the critical points found by Van Hove in 1953 for phonon dispersion relations in crystals. The importance of these singularities in wave kinetics depends on the dimension of phase space D = (N − 2)d (d physical space dimension, N the number of waves in resonance) and the degree of degeneracy δ of the critical points. Following Van Hove, we show that non-degenerate singularities lead to finite phase measures for D > 2 but produce divergences when D ≤ 2 and possible breakdown of wave kinetics if the collision integral itself becomes too large (or even infinite). Similar divergences and possible breakdown can occur for degenerate singularities, when D − δ ≤ 2; as we find for several physical examples, including electron-hole kinetics in graphene. -
Shape Analysis, Lebesgue Integration and Absolute Continuity Connections
NISTIR 8217 Shape Analysis, Lebesgue Integration and Absolute Continuity Connections Javier Bernal This publication is available free of charge from: https://doi.org/10.6028/NIST.IR.8217 NISTIR 8217 Shape Analysis, Lebesgue Integration and Absolute Continuity Connections Javier Bernal Applied and Computational Mathematics Division Information Technology Laboratory This publication is available free of charge from: https://doi.org/10.6028/NIST.IR.8217 July 2018 INCLUDES UPDATES AS OF 07-18-2018; SEE APPENDIX U.S. Department of Commerce Wilbur L. Ross, Jr., Secretary National Institute of Standards and Technology Walter Copan, NIST Director and Undersecretary of Commerce for Standards and Technology ______________________________________________________________________________________________________ This Shape Analysis, Lebesgue Integration and publication Absolute Continuity Connections Javier Bernal is National Institute of Standards and Technology, available Gaithersburg, MD 20899, USA free of Abstract charge As shape analysis of the form presented in Srivastava and Klassen’s textbook “Functional and Shape Data Analysis” is intricately related to Lebesgue integration and absolute continuity, it is advantageous from: to have a good grasp of the latter two notions. Accordingly, in these notes we review basic concepts and results about Lebesgue integration https://doi.org/10.6028/NIST.IR.8217 and absolute continuity. In particular, we review fundamental results connecting them to each other and to the kind of shape analysis, or more generally, functional data analysis presented in the aforeme- tioned textbook, in the process shedding light on important aspects of all three notions. Many well-known results, especially most results about Lebesgue integration and some results about absolute conti- nuity, are presented without proofs. -
Some Inequalities in the Theory of Functions^)
SOME INEQUALITIES IN THE THEORY OF FUNCTIONS^) BY ZEEV NEHARI 1. Introduction. Many of the inequalities of function theory and potential theory may be reduced to statements regarding the properties of harmonic domain functions with vanishing or constant boundary values, that is, func- tions which can be obtained from the Green's function by means of elementary processes. For the derivation of these inequalities a large number of different techniques and procedures have been used. It is the aim of this paper to show that many of the known inequalities of this type, and also others which are new, can be obtained as simple consequences of the classical minimum prop- erty of the Dirichlet integral. In addition to the resulting simplification, this method has the further advantage of being capable of generalization to a wide class of linear partial differential equations of elliptic type in two or more variables. The idea of using the positive-definite character of an integral as the point of departure for the derivation of function-theoretic inequalities is, of course, not new and it has been successfully used for this purpose by a num- ber of authors [l; 2; 8; 9; 16]. What the present paper attempts is to give a more or less systematic survey of the type of inequality obtainable in this way. 2. Monotonie functionals. 1. The domains we shall consider will be as- sumed to be bounded by a finite number of closed analytic curves and they will be embedded in a given closed Riemann surface R of finite genus. The symbol 5(a) will be used to denote a "singularity function" with the follow- ing properties: 5(a) is real, harmonic, and single-valued on R, with the excep- tion of a finite number of points at which 5(a) has specified singularities. -
Introduction to Sobolev Spaces
Introduction to Sobolev Spaces Lecture Notes MM692 2018-2 Joa Weber UNICAMP December 23, 2018 Contents 1 Introduction1 1.1 Notation and conventions......................2 2 Lp-spaces5 2.1 Borel and Lebesgue measure space on Rn .............5 2.2 Definition...............................8 2.3 Basic properties............................ 11 3 Convolution 13 3.1 Convolution of functions....................... 13 3.2 Convolution of equivalence classes................. 15 3.3 Local Mollification.......................... 16 3.3.1 Locally integrable functions................. 16 3.3.2 Continuous functions..................... 17 3.4 Applications.............................. 18 4 Sobolev spaces 19 4.1 Weak derivatives of locally integrable functions.......... 19 1 4.1.1 The mother of all Sobolev spaces Lloc ........... 19 4.1.2 Examples........................... 20 4.1.3 ACL characterization.................... 21 4.1.4 Weak and partial derivatives................ 22 4.1.5 Approximation characterization............... 23 4.1.6 Bounded weakly differentiable means Lipschitz...... 24 4.1.7 Leibniz or product rule................... 24 4.1.8 Chain rule and change of coordinates............ 25 4.1.9 Equivalence classes of locally integrable functions..... 27 4.2 Definition and basic properties................... 27 4.2.1 The Sobolev spaces W k;p .................. 27 4.2.2 Difference quotient characterization of W 1;p ........ 29 k;p 4.2.3 The compact support Sobolev spaces W0 ........ 30 k;p 4.2.4 The local Sobolev spaces Wloc ............... 30 4.2.5 How the spaces relate.................... 31 4.2.6 Basic properties { products and coordinate change.... 31 i ii CONTENTS 5 Approximation and extension 33 5.1 Approximation............................ 33 5.1.1 Local approximation { any domain............. 33 5.1.2 Global approximation on bounded domains....... -
Measure Theory John K. Hunter
Measure Theory John K. Hunter Department of Mathematics, University of California at Davis Abstract. These are some brief notes on measure theory, concentrating on n Lebesgue measure on R . Some missing topics I would have liked to have in- cluded had time permitted are: the change of variable formula for the Lebesgue n integral on R ; absolutely continuous functions and functions of bounded vari- ation of a single variable and their connection with Lebesgue-Stieltjes measures n on R; Radon measures on R , and other locally compact Hausdorff topological spaces, and the Riesz representation theorem for bounded linear functionals on spaces of continuous functions; and other examples of measures, including n k-dimensional Hausdorff measure in R , Wiener measure and Brownian mo- tion, and Haar measure on topological groups. All these topics can be found in the references. c John K. Hunter, 2011 Contents Chapter 1. Measures 1 1.1. Sets 1 1.2. Topological spaces 2 1.3. Extended real numbers 2 1.4. Outer measures 3 1.5. σ-algebras 4 1.6. Measures 5 1.7. Sets of measure zero 6 Chapter 2. Lebesgue Measure on Rn 9 2.1. Lebesgue outer measure 10 2.2. Outer measure of rectangles 12 2.3. Carath´eodory measurability 14 2.4. Null sets and completeness 18 2.5. Translational invariance 19 2.6. Borel sets 20 2.7. Borel regularity 22 2.8. Linear transformations 27 2.9. Lebesgue-Stieltjes measures 30 Chapter 3. Measurable functions 33 3.1. Measurability 33 3.2. Real-valued functions 34 3.3. -
Proving the Regularity of the Reduced Boundary of Perimeter Minimizing Sets with the De Giorgi Lemma
PROVING THE REGULARITY OF THE REDUCED BOUNDARY OF PERIMETER MINIMIZING SETS WITH THE DE GIORGI LEMMA Presented by Antonio Farah In partial fulfillment of the requirements for graduation with the Dean's Scholars Honors Degree in Mathematics Honors, Department of Mathematics Dr. Stefania Patrizi, Supervising Professor Dr. David Rusin, Honors Advisor, Department of Mathematics THE UNIVERSITY OF TEXAS AT AUSTIN May 2020 Acknowledgements I deeply appreciate the continued guidance and support of Dr. Stefania Patrizi, who supervised the research and preparation of this Honors Thesis. Dr. Patrizi kindly dedicated numerous sessions to this project, motivating and expanding my learning. I also greatly appreciate the support of Dr. Irene Gamba and of Dr. Francesco Maggi on the project, who generously helped with their reading and support. Further, I am grateful to Dr. David Rusin, who also provided valuable help on this project in his role of Honors Advisor in the Department of Mathematics. Moreover, I would like to express my gratitude to the Department of Mathematics' Faculty and Administration, to the College of Natural Sciences' Administration, and to the Dean's Scholars Honors Program of The University of Texas at Austin for my educational experience. 1 Abstract The Plateau problem consists of finding the set that minimizes its perimeter among all sets of a certain volume. Such set is known as a minimal set, or perimeter minimizing set. The problem was considered intractable until the 1960's, when the development of geometric measure theory by researchers such as Fleming, Federer, and De Giorgi provided the necessary tools to find minimal sets. -
Hausdorff Measure
Hausdorff Measure Jimmy Briggs and Tim Tyree December 3, 2016 1 1 Introduction In this report, we explore the the measurement of arbitrary subsets of the metric space (X; ρ); a topological space X along with its distance function ρ. We introduce Hausdorff Measure as a natural way of assigning sizes to these sets, especially those of smaller \dimension" than X: After an exploration of the salient properties of Hausdorff Measure, we proceed to a definition of Hausdorff dimension, a separate idea of size that allows us a more robust comparison between rough subsets of X. Many of the theorems in this report will be summarized in a proof sketch or shown by visual example. For a more rigorous treatment of the same material, we redirect the reader to Gerald B. Folland's Real Analysis: Modern techniques and their applications. Chapter 11 of the 1999 edition served as our primary reference. 2 Hausdorff Measure 2.1 Measuring low-dimensional subsets of X The need for Hausdorff Measure arises from the need to know the size of lower-dimensional subsets of a metric space. This idea is not as exotic as it may sound. In a high school Geometry course, we learn formulas for objects of various dimension embedded in R3: In Figure 1 we see the line segment, the circle, and the sphere, each with it's own idea of size. We call these length, area, and volume, respectively. Figure 1: low-dimensional subsets of R3: 2 4 3 2r πr 3 πr Note that while only volume measures something of the same dimension as the host space, R3; length, and area can still be of interest to us, especially 2 in applications. -
Integral Geometry – Measure Theoretic Approach and Stochastic Applications
Integral geometry – measure theoretic approach and stochastic applications Rolf Schneider Preface Integral geometry, as it is understood here, deals with the computation and application of geometric mean values with respect to invariant measures. In the following, I want to give an introduction to the integral geometry of polyconvex sets (i.e., finite unions of compact convex sets) in Euclidean spaces. The invariant or Haar measures that occur will therefore be those on the groups of translations, rotations, or rigid motions of Euclidean space, and on the affine Grassmannians of k-dimensional affine subspaces. How- ever, it is also in a different sense that invariant measures will play a central role, namely in the form of finitely additive functions on polyconvex sets. Such functions have been called additive functionals or valuations in the literature, and their motion invariant specializations, now called intrinsic volumes, have played an essential role in Hadwiger’s [2] and later work (e.g., [8]) on integral geometry. More recently, the importance of these functionals for integral geometry has been rediscovered by Rota [5] and Klain-Rota [4], who called them ‘measures’ and emphasized their role in certain parts of geometric probability. We will, more generally, deal with local versions of the intrinsic volumes, the curvature measures, and derive integral-geometric results for them. This is the third aspect of the measure theoretic approach mentioned in the title. A particular feature of this approach is the essential role that uniqueness results for invariant measures play in the proofs. As prerequisites, we assume some familiarity with basic facts from mea- sure and integration theory.