Some Problems with the Use of the Dirac Delta Function I: What Is the Value of ∫∫∫ ∞ Δ(X)Dx?
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Distributions:The Evolutionof a Mathematicaltheory
Historia Mathematics 10 (1983) 149-183 DISTRIBUTIONS:THE EVOLUTIONOF A MATHEMATICALTHEORY BY JOHN SYNOWIEC INDIANA UNIVERSITY NORTHWEST, GARY, INDIANA 46408 SUMMARIES The theory of distributions, or generalized func- tions, evolved from various concepts of generalized solutions of partial differential equations and gener- alized differentiation. Some of the principal steps in this evolution are described in this paper. La thgorie des distributions, ou des fonctions g&&alis~es, s'est d&eloppeg 2 partir de divers con- cepts de solutions g&&alis6es d'gquations aux d&i- &es partielles et de diffgrentiation g&&alis6e. Quelques-unes des principales &apes de cette &olution sont d&rites dans cet article. Die Theorie der Distributionen oder verallgemein- erten Funktionen entwickelte sich aus verschiedenen Begriffen von verallgemeinerten Lasungen der partiellen Differentialgleichungen und der verallgemeinerten Ableitungen. In diesem Artikel werden einige der wesentlichen Schritte dieser Entwicklung beschrieben. 1. INTRODUCTION The founder of the theory of distributions is rightly con- sidered to be Laurent Schwartz. Not only did he write the first systematic paper on the subject [Schwartz 19451, which, along with another paper [1947-19481, already contained most of the basic ideas, but he also wrote expository papers on distributions for electrical engineers [19481. Furthermore, he lectured effec- tively on his work, for example, at the Canadian Mathematical Congress [1949]. He showed how to apply distributions to partial differential equations [19SObl and wrote the first general trea- tise on the subject [19SOa, 19511. Recognition of his contri- butions came in 1950 when he was awarded the Fields' Medal at the International Congress of Mathematicians, and in his accep- tance address to the congress Schwartz took the opportunity to announce his celebrated "kernel theorem" [195Oc]. -
Spheres in Infinite-Dimensional Normed Spaces Are Lipschitz Contractible
PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 88. Number 3, July 1983 SPHERES IN INFINITE-DIMENSIONAL NORMED SPACES ARE LIPSCHITZ CONTRACTIBLE Y. BENYAMINI1 AND Y. STERNFELD Abstract. Let X be an infinite-dimensional normed space. We prove the following: (i) The unit sphere {x G X: || x II = 1} is Lipschitz contractible. (ii) There is a Lipschitz retraction from the unit ball of JConto the unit sphere. (iii) There is a Lipschitz map T of the unit ball into itself without an approximate fixed point, i.e. inffjjc - Tx\\: \\x\\ « 1} > 0. Introduction. Let A be a normed space, and let Bx — {jc G X: \\x\\ < 1} and Sx = {jc G X: || jc || = 1} be its unit ball and unit sphere, respectively. Brouwer's fixed point theorem states that when X is finite dimensional, every continuous self-map of Bx admits a fixed point. Two equivalent formulations of this theorem are the following. 1. There is no continuous retraction from Bx onto Sx. 2. Sx is not contractible, i.e., the identity map on Sx is not homotopic to a constant map. It is well known that none of these three theorems hold in infinite-dimensional spaces (see e.g. [1]). The natural generalization to infinite-dimensional spaces, however, would seem to require the maps to be uniformly-continuous and not merely continuous. Indeed in the finite-dimensional case this condition is automatically satisfied. In this article we show that the above three theorems fail, in the infinite-dimen- sional case, even under the strongest uniform-continuity condition, namely, for maps satisfying a Lipschitz condition. -
Examples of Manifolds
Examples of Manifolds Example 1 (Open Subset of IRn) Any open subset, O, of IRn is a manifold of dimension n. One possible atlas is A = (O, ϕid) , where ϕid is the identity map. That is, ϕid(x) = x. n Of course one possible choice of O is IR itself. Example 2 (The Circle) The circle S1 = (x,y) ∈ IR2 x2 + y2 = 1 is a manifold of dimension one. One possible atlas is A = {(U , ϕ ), (U , ϕ )} where 1 1 1 2 1 y U1 = S \{(−1, 0)} ϕ1(x,y) = arctan x with − π < ϕ1(x,y) <π ϕ1 1 y U2 = S \{(1, 0)} ϕ2(x,y) = arctan x with 0 < ϕ2(x,y) < 2π U1 n n n+1 2 2 Example 3 (S ) The n–sphere S = x =(x1, ··· ,xn+1) ∈ IR x1 +···+xn+1 =1 n A U , ϕ , V ,ψ i n is a manifold of dimension . One possible atlas is 1 = ( i i) ( i i) 1 ≤ ≤ +1 where, for each 1 ≤ i ≤ n + 1, n Ui = (x1, ··· ,xn+1) ∈ S xi > 0 ϕi(x1, ··· ,xn+1)=(x1, ··· ,xi−1,xi+1, ··· ,xn+1) n Vi = (x1, ··· ,xn+1) ∈ S xi < 0 ψi(x1, ··· ,xn+1)=(x1, ··· ,xi−1,xi+1, ··· ,xn+1) n So both ϕi and ψi project onto IR , viewed as the hyperplane xi = 0. Another possible atlas is n n A2 = S \{(0, ··· , 0, 1)}, ϕ , S \{(0, ··· , 0, −1)},ψ where 2x1 2xn ϕ(x , ··· ,xn ) = , ··· , 1 +1 1−xn+1 1−xn+1 2x1 2xn ψ(x , ··· ,xn ) = , ··· , 1 +1 1+xn+1 1+xn+1 are the stereographic projections from the north and south poles, respectively. -
Arxiv:1404.7630V2 [Math.AT] 5 Nov 2014 Asoffsae,Se[S4 P8,Vr6.Isedof Instead Ver66]
PROPER BASE CHANGE FOR SEPARATED LOCALLY PROPER MAPS OLAF M. SCHNÜRER AND WOLFGANG SOERGEL Abstract. We introduce and study the notion of a locally proper map between topological spaces. We show that fundamental con- structions of sheaf theory, more precisely proper base change, pro- jection formula, and Verdier duality, can be extended from contin- uous maps between locally compact Hausdorff spaces to separated locally proper maps between arbitrary topological spaces. Contents 1. Introduction 1 2. Locally proper maps 3 3. Proper direct image 5 4. Proper base change 7 5. Derived proper direct image 9 6. Projection formula 11 7. Verdier duality 12 8. The case of unbounded derived categories 15 9. Remindersfromtopology 17 10. Reminders from sheaf theory 19 11. Representability and adjoints 21 12. Remarks on derived functors 22 References 23 arXiv:1404.7630v2 [math.AT] 5 Nov 2014 1. Introduction The proper direct image functor f! and its right derived functor Rf! are defined for any continuous map f : Y → X of locally compact Hausdorff spaces, see [KS94, Spa88, Ver66]. Instead of f! and Rf! we will use the notation f(!) and f! for these functors. They are embedded into a whole collection of formulas known as the six-functor-formalism of Grothendieck. Under the assumption that the proper direct image functor f(!) has finite cohomological dimension, Verdier proved that its ! derived functor f! admits a right adjoint f . Olaf Schnürer was supported by the SPP 1388 and the SFB/TR 45 of the DFG. Wolfgang Soergel was supported by the SPP 1388 of the DFG. 1 2 OLAFM.SCHNÜRERANDWOLFGANGSOERGEL In this article we introduce in 2.3 the notion of a locally proper map between topological spaces and show that the above results even hold for arbitrary topological spaces if all maps whose proper direct image functors are involved are locally proper and separated. -
Mathematical and Physical Interpretations of Fractional Derivatives and Integrals
R. Hilfer Mathematical and Physical Interpretations of Fractional Derivatives and Integrals Abstract: Brief descriptions of various mathematical and physical interpretations of fractional derivatives and integrals have been collected into this chapter as points of reference and departure for deeper studies. “Mathematical interpre- tation” in the title means a brief description of the basic mathematical idea underlying a precise definition. “Physical interpretation” means a brief descrip- tion of the physical theory underlying an identification of the fractional order with a known physical quantity. Numerous interpretations had to be left out due to page limitations. Only a crude, rough and ready description is given for each interpretation. For precise theorems and proofs an extensive list of references can serve as a starting point. Keywords: fractional derivatives and integrals, Riemann-Liouville integrals, Weyl integrals, Riesz potentials, operational calculus, functional calculus, Mikusinski calculus, Hille-Phillips calculus, Riesz-Dunford calculus, classification, phase transitions, time evolution, anomalous diffusion, continuous time random walks Mathematics Subject Classification 2010: 26A33, 34A08, 35R11 published in: Handbook of Fractional Calculus: Basic Theory, Vol. 1, Ch. 3, pp. 47-86, de Gruyter, Berlin (2019) ISBN 978-3-11-057162-2 R. Hilfer, ICP, Fakultät für Mathematik und Physik, Universität Stuttgart, Allmandring 3, 70569 Stuttgart, Deutschland DOI https://doi.org/10.1515/9783110571622 Interpretations 1 1 Prolegomena -
MATH 418 Assignment #7 1. Let R, S, T Be Positive Real Numbers Such That R
MATH 418 Assignment #7 1. Let r, s, t be positive real numbers such that r + s + t = 1. Suppose that f, g, h are nonnegative measurable functions on a measure space (X, S, µ). Prove that Z r s t r s t f g h dµ ≤ kfk1kgk1khk1. X s t Proof . Let u := g s+t h s+t . Then f rgsht = f rus+t. By H¨older’s inequality we have Z Z rZ s+t r s+t r 1/r s+t 1/(s+t) r s+t f u dµ ≤ (f ) dµ (u ) dµ = kfk1kuk1 . X X X For the same reason, we have Z Z s t s t s+t s+t s+t s+t kuk1 = u dµ = g h dµ ≤ kgk1 khk1 . X X Consequently, Z r s t r s+t r s t f g h dµ ≤ kfk1kuk1 ≤ kfk1kgk1khk1. X 2. Let Cc(IR) be the linear space of all continuous functions on IR with compact support. (a) For 1 ≤ p < ∞, prove that Cc(IR) is dense in Lp(IR). Proof . Let X be the closure of Cc(IR) in Lp(IR). Then X is a linear space. We wish to show X = Lp(IR). First, if I = (a, b) with −∞ < a < b < ∞, then χI ∈ X. Indeed, for n ∈ IN, let gn the function on IR given by gn(x) := 1 for x ∈ [a + 1/n, b − 1/n], gn(x) := 0 for x ∈ IR \ (a, b), gn(x) := n(x − a) for a ≤ x ≤ a + 1/n and gn(x) := n(b − x) for b − 1/n ≤ x ≤ b. -
On Fractional Whittaker Equation and Operational Calculus
J. Math. Sci. Univ. Tokyo 20 (2013), 127–146. On Fractional Whittaker Equation and Operational Calculus By M. M. Rodrigues and N. Vieira Abstract. This paper is intended to investigate a fractional dif- ferential Whittaker’s equation of order 2α, with α ∈]0, 1], involving the Riemann-Liouville derivative. We seek a possible solution in terms of power series by using operational approach for the Laplace and Mellin transform. A recurrence relation for coefficients is obtained. The exis- tence and uniqueness of solutions is discussed via Banach fixed point theorem. 1. Introduction The Whittaker functions arise as solutions of the Whittaker differential equation (see [4], Vol.1)). These functions have acquired a significant in- creasing due to its frequent use in applications of mathematics to physical and technical problems [1]. Moreover, they are closely related to the con- fluent hypergeometric functions, which play an important role in various branches of applied mathematics and theoretical physics, for instance, fluid mechanics, electromagnetic diffraction theory, and atomic structure theory. This justifies the continuous effort in studying properties of these functions and in gathering information about them. As far as the authors aware, there were no attempts to study the corresponding fractional Whittaker equation (see below). Fractional differential equations are widely used for modeling anomalous relaxation and diffusion phenomena (see [3], Ch. 5, [6], Ch. 2). A systematic development of the analytic theory of fractional differential equations with variable coefficients can be found, for instance, in the books of Samko, Kilbas and Marichev (see [13], Ch. 3). 2010 Mathematics Subject Classification. Primary 35R11; Secondary 34B30, 42A38, 47H10. -
GENERALIZED FUNCTIONS LECTURES Contents 1. the Space
GENERALIZED FUNCTIONS LECTURES Contents 1. The space of generalized functions on Rn 2 1.1. Motivation 2 1.2. Basic definitions 3 1.3. Derivatives of generalized functions 5 1.4. The support of generalized functions 6 1.5. Products and convolutions of generalized functions 7 1.6. Generalized functions on Rn 8 1.7. Generalized functions and differential operators 9 1.8. Regularization of generalized functions 9 n 2. Topological properties of Cc∞(R ) 11 2.1. Normed spaces 11 2.2. Topological vector spaces 12 2.3. Defining completeness 14 2.4. Fréchet spaces 15 2.5. Sequence spaces 17 2.6. Direct limits of Fréchet spaces 18 2.7. Topologies on the space of distributions 19 n 3. Geometric properties of C−∞(R ) 21 3.1. Sheaf of distributions 21 3.2. Filtration on spaces of distributions 23 3.3. Functions and distributions on a Cartesian product 24 4. p-adic numbers and `-spaces 26 4.1. Defining p-adic numbers 26 4.2. Misc. -not sure what to do with them (add to an appendix about p-adic numbers?) 29 4.3. p-adic expansions 31 4.4. Inverse limits 32 4.5. Haar measure and local fields 32 4.6. Some basic properties of `-spaces. 33 4.7. Distributions on `-spaces 35 4.8. Distributions supported on a subspace 35 5. Vector valued distributions 37 Date: October 7, 2018. 1 GENERALIZED FUNCTIONS LECTURES 2 5.1. Smooth measures 37 5.2. Generalized functions versus distributions 38 5.3. Some linear algebra 39 5.4. Generalized functions supported on a subspace 41 6. -
Convolution on the N-Sphere with Application to PDF Modeling Ivan Dokmanic´, Student Member, IEEE, and Davor Petrinovic´, Member, IEEE
IEEE TRANSACTIONS ON SIGNAL PROCESSING, VOL. 58, NO. 3, MARCH 2010 1157 Convolution on the n-Sphere With Application to PDF Modeling Ivan Dokmanic´, Student Member, IEEE, and Davor Petrinovic´, Member, IEEE Abstract—In this paper, we derive an explicit form of the convo- emphasis on wavelet transform in [8]–[12]. Computation of the lution theorem for functions on an -sphere. Our motivation comes Fourier transform and convolution on groups is studied within from the design of a probability density estimator for -dimen- the theory of noncommutative harmonic analysis. Examples sional random vectors. We propose a probability density function (pdf) estimation method that uses the derived convolution result of applications of noncommutative harmonic analysis in engi- on . Random samples are mapped onto the -sphere and esti- neering are analysis of the motion of a rigid body, workspace mation is performed in the new domain by convolving the samples generation in robotics, template matching in image processing, with the smoothing kernel density. The convolution is carried out tomography, etc. A comprehensive list with accompanying in the spectral domain. Samples are mapped between the -sphere theory and explanations is given in [13]. and the -dimensional Euclidean space by the generalized stereo- graphic projection. We apply the proposed model to several syn- Statistics of random vectors whose realizations are observed thetic and real-world data sets and discuss the results. along manifolds embedded in Euclidean spaces are commonly termed directional statistics. An excellent review may be found Index Terms—Convolution, density estimation, hypersphere, hy- perspherical harmonics, -sphere, rotations, spherical harmonics. in [14]. It is of interest to develop tools for the directional sta- tistics in analogy with the ordinary Euclidean. -
American Mathematical Society TRANSLATIONS Series 2 • Volume 130
American Mathematical Society TRANSLATIONS Series 2 • Volume 130 One-Dimensional Inverse Problems of Mathematical Physics aM „ °m American Mathematical Society One-Dimensional Inverse Problems of Mathematical Physics http://dx.doi.org/10.1090/trans2/130 American Mathematical Society TRANSLATIONS Series 2 • Volume 130 One-Dimensional Inverse Problems of Mathematical Physics By M. M. Lavrent'ev K. G. Reznitskaya V. G. Yakhno do, n American Mathematical Society r, --1 Providence, Rhode Island Translated by J. R. SCHULENBERGER Translation edited by LEV J. LEIFMAN 1980 Mathematics Subject Classification (1985 Revision): Primary 35K05, 35L05, 35R30. Abstract. Problems of determining a variable coefficient and right side for hyperbolic and parabolic equations on the basis of known solutions at fixed points of space for all times are considered in this monograph. Here the desired coefficient of the equation is a function of only one coordinate, while the desired right side is a function only of time. On the basis of solution of direct problems the inverse problems are reduced to nonlinear operator equations for which uniqueness and in some cases also existence questions are investigated. The problems studied have applied importance, since they are models for interpreting data of geophysical prospecting by seismic and electric means. The monograph is of interest to mathematicians concerned with mathematical physics. Bibliography: 75 titles. Library of Congress Cataloging-in-Publication Data Lavrent'ev, M. M. (Mlkhail Milchanovich) One-dimensional inverse problems of mathematical physics. (American Mathematical Society translations; ser. 2, v. 130) Translation of: Odnomernye obratnye zadachi matematicheskoi Bibliography: p. 67. 1. Inverse problems (Differential equations) 2. Mathematical physics. -
Minkowski Products of Unit Quaternion Sets 1 Introduction
Minkowski products of unit quaternion sets 1 Introduction The Minkowski sum A⊕B of two point sets A; B 2 Rn is the set of all points generated [16] by the vector sums of points chosen independently from those sets, i.e., A ⊕ B := f a + b : a 2 A and b 2 B g : (1) The Minkowski sum has applications in computer graphics, geometric design, image processing, and related fields [9, 11, 12, 13, 14, 15, 20]. The validity of the definition (1) in Rn for all n ≥ 1 stems from the straightforward extension of the vector sum a + b to higher{dimensional Euclidean spaces. However, to define a Minkowski product set A ⊗ B := f a b : a 2 A and b 2 B g ; (2) it is necessary to specify products of points in Rn. In the case n = 1, this is simply the real{number product | the resulting algebra of point sets in R1 is called interval arithmetic [17, 18] and is used to monitor the propagation of uncertainty through computations in which the initial operands (and possibly also the arithmetic operations) are not precisely determined. A natural realization of the Minkowski product (2) in R2 may be achieved [7] by interpreting the points a and b as complex numbers, with a b being the usual complex{number product. Algorithms to compute Minkowski products of complex{number sets have been formulated [6], and extended to determine Minkowski roots and powers [3, 8] of complex sets; to evaluate polynomials specified by complex{set coefficients and arguments [4]; and to solve simple equations expressed in terms of complex{set coefficients and unknowns [5]. -
GEOMETRY Contents 1. Euclidean Geometry 2 1.1. Metric Spaces 2 1.2
GEOMETRY JOUNI PARKKONEN Contents 1. Euclidean geometry 2 1.1. Metric spaces 2 1.2. Euclidean space 2 1.3. Isometries 4 2. The sphere 7 2.1. More on cosine and sine laws 10 2.2. Isometries 11 2.3. Classification of isometries 12 3. Map projections 14 3.1. The latitude-longitude map 14 3.2. Stereographic projection 14 3.3. Inversion 14 3.4. Mercator’s projection 16 3.5. Some Riemannian geometry. 18 3.6. Cylindrical projection 18 4. Triangles in the sphere 19 5. Minkowski space 21 5.1. Bilinear forms and Minkowski space 21 5.2. The orthogonal group 22 6. Hyperbolic space 24 6.1. Isometries 25 7. Models of hyperbolic space 30 7.1. Klein’s model 30 7.2. Poincaré’s ball model 30 7.3. The upper halfspace model 31 8. Some geometry and techniques 32 8.1. Triangles 32 8.2. Geodesic lines and isometries 33 8.3. Balls 35 9. Riemannian metrics, area and volume 36 Last update: December 12, 2014. 1 1. Euclidean geometry 1.1. Metric spaces. A function d: X × X ! [0; +1[ is a metric in the nonempty set X if it satisfies the following properties (1) d(x; x) = 0 for all x 2 X and d(x; y) > 0 if x 6= y, (2) d(x; y) = d(y; x) for all x; y 2 X, and (3) d(x; y) ≤ d(x; z) + d(z; y) for all x; y; z 2 X (the triangle inequality). The pair (X; d) is a metric space.