Introduction to the Theory of Distributions

by
Edition: 2nd
Format: Hardcover
Pub. Date: 1999-01-28
Publisher(s): Cambridge University Press
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Summary

The theory of distributions is an extension of classical analysis which has acquired a particular importance in the field of linear partial differential equations, as well as having many other applications, for example in harmonic analysis. Underlying it is the theory of topological vector spaces, but it is possible to give a systematic presentation without presupposing a knowledge, or using more than a bare minimum, of this. This book adopts this course and is based on graduate lectures given over a number of years. The prerequisites are few, but a reasonable degree of mathematical maturity is expected of the reader, as the treatment is rigorous throughout. From the outset the theory is developed in several variables, unlike most elementary texts; it is taken as far as such important topics as Schwartz kernels, the Paley-Wiener-Schwartz theorem and Sobolev spaces. In this second edition, the notion of the wavefront set of a distribution is introduced, which allows many operations on distributions to be extended to larger classes and gives much more precise understanding of the nature of the singularities of a distribution. This is done in an elementary fashion without using any involved theories. This account should therefore be useful to graduate students and research workers who are interested in the applications of analysis in mathematics and mathematical physics.

Table of Contents

Preface ix
Introduction 1(3)
Test functions and distributions
4(13)
Some notations and definitions
4(1)
Test functions
5(2)
Distributions
7(3)
Localization
10(3)
Convergence of distributions
13(4)
Exercises
15(2)
Differentiation, and multiplication by smooth functions
17(17)
The derivatives of a distribution
17(1)
Some examples
18(2)
A distribution obtained by analytic continuation
20(2)
Primitives in D'(R)
22(1)
Product of a distribution and a smooth function
23(2)
Linear differential operators
25(2)
Division in D'(R)
27(2)
Duality
29(5)
Exercises
30(4)
Distributions with compact support
34(6)
Continuous linear forms on C∫ (X), and distributions with compact support
34(2)
Distributions supported at the origin
36(4)
Exercises
39(1)
Tensor products
40(10)
Test functions which depend on a parameter
40(2)
Affine transformations
42(2)
The tensor product of distributions
44(6)
Exercises
48(2)
Convolution
50(18)
The convolution of two distributions
50(3)
Regularization
53(2)
Convolution of distributions with non-compact supports
55(4)
Fundamental solutions of some differential operators
59(9)
Exercises
65(3)
Distribution kernels
68(12)
Schwartz kernels and the kernel theorem
68(5)
Regular kernels
73(3)
Fundamental kernels of differential operators
76(4)
Exercises
78(2)
Coordinate transformations and pullbacks
80(10)
Diffeomorphisms
80(1)
The pullback of a distribution by a function
81(4)
The wave equation on R4
85(5)
Exercises
88(2)
Tempered distributions and Fourier transforms
90(24)
Introduction
90(3)
Rapidly descreasing test functions
93(3)
Tempered distributions
96(5)
The convolution theorem
101(3)
Poisson's summation formula, and periodic distributions
104(4)
The elliptic regularity theorem
108(6)
Exercises
110(4)
Plancherel's theorem, and Sobolev spaces
114(14)
Hilbert space
114(2)
The Fourier transform on L2(Rn)
116(4)
Sobolev spaces
120(8)
Exercises
126(2)
The Fourier-Laplace transform
128(16)
Analytic functions of several complex variables
128(2)
The Paley-Wiener-Schwartz theorem
130(4)
An application to evolution operators
134(5)
The Malgrange-Ehrenpreis theorem
139(5)
Exercises
142(2)
The calculus of wavefront sets
144(18)
Definitions
144(4)
Transformations of wavefront sets under elementary operations
148(6)
Push-forwards and pull-backs
154(3)
Wavefront sets and Schwartz kernels
157(2)
Propagation of singularities
159(3)
Exercises
160(2)
Appendix: topological vector spaces 162(8)
Bibliography 170(1)
Notation 171(2)
Index 173

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