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Pathways in Mathematics
Peter Junghanns
Giuseppe Mastroianni
Incoronata Notarangelo
Weighted
Polynomial
Approximation
and Numerical
Methods for
Integral Equations
Pathways in Mathematics
Series Editors
Takayuki Hibi, Department of Pure and Applied Mathematics, Osaka University,
Suita, Osaka, Japan
Wolfgang König, Weierstraß-Institut, Berlin, Germany
Johannes Zimmer, Fakultät für Mathematik, Technische Universität München,
Garching, Germany
Each “Pathways in Mathematics” book offers a roadmap to a currently well devel-
oping mathematical research field and is a first-hand information and inspiration
for further study, aimed both at students and researchers. It is written in an
educational style, i.e., in a way that is accessible for advanced undergraduate and
graduate students. It also serves as an introduction to and survey of the field for
researchers who want to be quickly informed about the state of the art. The point of
departure is typically a bachelor/masters level background, from which the reader
is expeditiously guided to the frontiers. This is achieved by focusing on ideas and
concepts underlying the development of the subject while keeping technicalities to
a minimum. Each volume contains an extensive annotated bibliography as well as a
discussion of open problems and future research directions as recommendations for
starting new projects. Titles from this series are indexed by Scopus.
Weighted Polynomial
Approximation
and Numerical Methods
for Integral Equations
Peter Junghanns Giuseppe Mastroianni
Fakultät für Mathematik Department of Mathematics, Computer
Technische Universität Chemnitz Sciences and Economics
Chemnitz, Germany University of Basilicata
Potenza, Italy
Incoronata Notarangelo
Department of Mathematics
”Giuseppe Peano”
University of Turin
Turin, Italy
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland
AG 2021
This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether
the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse
of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and
transmission or information storage and retrieval, electronic adaptation, computer software, or by similar
or dissimilar methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
does not imply, even in the absence of a specific statement, that such names are exempt from the relevant
protective laws and regulations and therefore free for general use.
The publisher, the authors, and the editors are safe to assume that the advice and information in this book
are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or
the editors give a warranty, expressed or implied, with respect to the material contained herein or for any
errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional
claims in published maps and institutional affiliations.
This book is published under the imprint Birkhäuser, www.birkhauser-science.com, by the registered
company Springer Nature Switzerland AG.
The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface
The content of this book is a combination of two topics, one comes from the
theory of approximation of functions and integrals by interpolation and quadrature,
respectively, and the other from the numerical analysis of operator equations,
in particular, of integral and related equations. It is not necessary to point out
that integral equations play an important role in different mathematical areas. We
stress the connection between ordinary differential equations and Volterra-Fredholm
integral equations and the connection between boundary value problems for partial
differential equations and boundary integral equations, which are obtained by so-
called boundary integral methods. These methods lead to different classes of integral
equations like, for example, Fredholm integral equations of first and second kind
involving integral operators with both smooth and weakly singular kernel functions,
or Cauchy singular integral equations, as well as hypersingular integral equations,
or integro-differential equations.
Regarding interpolation and quadrature processes, we restrict ourselves to the
non periodic case, that means to the approximation and integration of functions
defined on bounded or unbounded intervals, where we attach particular value to
functions having singularities at the end points of the interval. This is due to our
further aim in this book, namely, to propose and to investigate numerical methods
for different classes of integral equations given on such intervals, where these
methods are based on the mentioned interpolation and quadrature processes. The
book contains classical results, but also very recent results. We thought it might be
worthwhile to publish a book in which these two topics are summarized.
In Chap. 1, the introduction, we give some hints for the use of the book and
introduce some general notations and agreements for the whole text. Chapter 2
collects the basic principles from linear functional analysis needed in the remaining
part of the book, gives definitions for different kinds of function spaces such as
weighted Lp spaces and weighted spaces of continuous functions as well as scales
of subspaces of them, which are important for our investigations. This chapter also
presents some concepts concerned with the stability and convergence of operator
sequences or, in other words, with numerical or approximation methods for operator
v
vi Preface
equations. Moreover, we recall some basic facts from fixed point theory and about
Newton’s method.
Chapters 3 and 4 are devoted to the study of interpolation processes and the
respective quadrature rules based on the zeros of orthogonal polynomials with
respect to certain weight functions on the interval (−1, 1), the half axis (0, ∞),
and the whole real axis. These chapters can be considered as a continuation of [121,
Chapter 2 and Chapter 4, Section 5.1], where the authors mainly consider classical
weights (also with additional inner singularities). In the present text we concentrate
on recent results and developments concerned with non classical weights like
exponential weights on (−1, 1) and on (0, ∞) and generalized Freud weights on
the real axis.
In Chap. 5, we provide mapping properties of various classes of integral operators
in certain Banach spaces of functions and with respect to appropriate scales of sub-
spaces of these Banach spaces, which are of interest for our further investigations.
Moreover, we discuss solvability properties of certain classes of nonlinear Cauchy
singular integral equations.
Chapters 6 and 7 deal with numerical methods for several classes of integral
equations based on some interpolation and quadrature processes considered in
Chaps. 3 and 4. While Chap. 6 concentrates on respective Nyström and collocation-
quadrature methods for Fredholm integral equations with continuous and weakly
singular kernel functions, in Chap. 7 collocation and collocation-quadrature meth-
ods are applied to strongly singular integral equations like linear and nonlinear
Cauchy singular integral equations, integral equations with strongly fixed singu-
larities, and hypersingular integral equations.
In Chap. 8, we investigate some concrete applications of the theory presented
in the previous chapter to examples from two-dimensional elasticity theory, airfoil
theory, and free boundary seepage flow problems. In the two final chapters, Chaps. 9
and 10, we give complete answers or detailed hints to the exercises and list a
series of inequalities, equivalences, and equalities used at many places in the book,
respectively.
The book is mainly addressed to graduate students familiar with the basics of real
and complex analysis, linear algebra, and functional analysis. But, the study of this
book is also worthwhile for researchers beginning to deal with the approximation
of functions and the numerical solution of operator equations, in particular integral
equations. Moreover, we hope that the present book is also suitable to give ideas for
handling further or new problems of interest, which can be solved with the help of
integral equations. The book should also reach engineers who are interested in the
solution of certain problems of similar kind as presented here.
We are deeply grateful to Birkhäuser for including this book in the very
successful series Pathways in Mathematics and, in particular, for the invaluable
assistance in preparing the final version of the text.
1 Introduction .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 1
2 Basics from Linear and Nonlinear Functional Analysis. . . . . . . . . . . . . . . . 5
2.1 Linear Operators, Banach and Hilbert Spaces . .. . . . . . . . . . . . . . . . . . . . 5
2.2 Fundamental Principles . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 9
2.3 Compact Sets and Compact Operators . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 13
2.4 Function Spaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 16
2.4.1 Lp -Spaces . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 17
2.4.2 Spaces of Continuous Functions . . . . . . . .. . . . . . . . . . . . . . . . . . . . 23
2.4.3 Approximation Spaces and Unbounded
Linear Operators . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 34
2.5 Fredholm Operators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 42
2.6 Stability of Operator Sequences . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 43
2.7 Fixed Point Theorems and Newton’s Method.. .. . . . . . . . . . . . . . . . . . . . 50
3 Weighted Polynomial Approximation and Quadrature Rules
on (−1, 1) .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 57
3.1 Moduli of Smoothness, K-Functionals, and Best
Approximation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 57
3.1.1 Moduli of Smoothness and K-Functionals.. . . . . . . . . . . . . . . . . 58
3.1.2 Moduli of Smoothness and Best Weighted
Approximation . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 65
3.1.3 Besov-Type Spaces . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 68
3.2 Polynomial Approximation with Doubling Weights on
the Interval (−1, 1) .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 78
3.2.1 Definitions .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 78
3.2.2 Polynomial Inequalities with Doubling Weights . . . . . . . . . . . 84
3.2.3 Christoffel Functions with Respect to Doubling
Weights . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 86
3.2.4 Convergence of Fourier Sums in Weighted Lp -Spaces . . . . 91
3.2.5 Lagrange Interpolation in Weighted Lp -Spaces .. . . . . . . . . . . 98
3.2.6 Hermite Interpolation . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 108
vii
viii Contents
8 Applications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 537
8.1 A Cruciform Crack Problem .. . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 537
8.1.1 The Integral Equations Under Consideration .. . . . . . . . . . . . . . 537
8.1.2 Solvability Properties of the Operator Equations .. . . . . . . . . . 542
8.1.3 A Quadrature Method.. . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 547
8.2 The Drag Minimization Problem for a Wing . . .. . . . . . . . . . . . . . . . . . . . 549
8.2.1 Formulation of the Problem . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 549
8.2.2 Derivation of the Operator Equation . . . .. . . . . . . . . . . . . . . . . . . . 553
8.2.3 A Collocation-Quadrature Method .. . . . .. . . . . . . . . . . . . . . . . . . . 558
8.2.4 Numerical Examples .. . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 565
8.3 Two-Dimensional Free Boundary Value Problems . . . . . . . . . . . . . . . . . 570
8.3.1 Seepage Flow from a Dam . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 570
8.3.2 Seepage Flow from a Channel.. . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 582
9 Hints and Answers to the Exercises . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 601
10 Equalities and Inequalities . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 637
10.1 Equalities and Equivalences . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 637
10.2 General Inequalities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 638
10.3 Marcinkiewicz Inequalities . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 640
Bibliography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 643
Index . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . 653
Chapter 1
Introduction
In this book we are mainly interested in the approximation of (in general, complex
valued) functions, defined on bounded or unbounded intervals of the real line, with
possible singularities (like unboundedness or nonsmoothness) at the endpoints of
these intervals (cf. Chaps. 3 and 4). In particular, we focus on situations, where such
functions are (unknown) solutions of different kinds of integral equations, namely
Fredholm integral equations (Chap. 6), linear and nonlinear Cauchy singular integral
equations, hypersingular integral equations, and integral equations with Mellin
kernels (Chap. 7). We propose and investigate numerical methods for solving these
operator equations. Thereby, we concentrate on so-called global ansatz functions
for the unknown solutions by searching an approximate solution as a finite linear
combination of (in general, weighted) polynomials (cf. Chaps. 6 and 7).
Consequently, our main goals are, firstly, studying (weighted) polynomial
approximation of functions from weighted spaces of continuous functions and
weighted Lp -spaces (cf. Chaps. 3 and 4) and, secondly, the stability and convergence
of certain approximation methods for integral equations basing on interpolation and
quadrature processes as investigated in Chaps. 3 and 4. Thus, if readers are mainly
interested in the approximation of functions and integrals, then, after reading this
introduction and Chap. 2, they can concentrate on studying Chaps. 3 and 4 on
weighted polynomial approximation. Readers, who are more interested in numerics
for integral equations, can skip Chaps. 3 and 4 and directly proceed with Chap. 5
on mapping properties of some classes of integral operators, followed by Chap. 6
or/and Chap. 7 (consulting certain results from Chaps. 3 and 4 if necessary). They
should end up reading Chap. 8 on some Applications devoted to fracture mechanics,
wing theory, and free boundary value problems (cf. the picture at the end of this
introduction). Moreover, many sections of the book are written in such a way that,
for a reader who would not go too much into the details, it is also possible to study
a single section with a certain success and without taking into account too much
references to other places in the book. That means, that definitions and notations
Chapter 1 : Introduction
Chapter 6 : Chapter 7 :
Chapter 8 : Applications
In this chapter we collect the basic principles from linear functional analysis needed
in the remaining part of the book. We give definitions for different kinds of function
spaces such as weighted Lp -spaces and weighted spaces of continuous functions as
well as scales of subspaces of them, which are important for our investigations. We
also present some concepts concerned with the stability and convergence of operator
sequences or, in other words, with numerical or approximation methods for operator
equations. Moreover, we recall some basic facts from fixed point theory, namely
Banach’s and Schauder’s fixed point theorems, and discuss a few aspects on the
convergence of Newton’s iteration method.
γ −1 f 2 ≤ f 1 ≤ γ f 2 ∀f ∈ X.
for some p ∈ [1, ∞). We agree that, if in the sequel there occur products of normed
spaces, we will consider them equipped with one of these norms. Moreover, K is
also considered as the Banach space (K, |.|) with the modulus as norm. Clearly,
if both spaces X and Y are Banach spaces, then so is their product. With these
definitions, one can easily see that the maps X × X −→ X, (f, g) → f + g and
K × X −→ X, (α, f ) → αf are continuous maps.
Let X and Y be normed linear spaces over the same field K. A linear operator
A ∈ L(X, Y) is called bounded if it maps bounded sets into bounded sets, which is
equivalent to
AX→Y := sup Af Y : f ∈ X, f X ≤ 1 < ∞ .
Af Y ≤ M f X ∀f ∈ X.
The set of all bounded linear operators from X into Y is denoted by L(X, Y), in case
Y = X by L(X). The linear combination of two linear operators A, B ∈ L(X, Y)
is defined by (αA + βB)f := (αAf ) + (βBf ) ∀f ∈ X, where α, β ∈ K. Then
L(X, Y) is a linear space, and L(X, Y), .X→Y = L(X, Y), .L(X,Y) is a
normed linear space, which is a Banach space if and only if Y is a Banach space
(see the following three exercises).
Let (X, .X ) and (Y, .Y ) be two normed spaces. We say that Y is continu-
ously embedded into X, if Y ⊂ X and the operator E : Y −→ X, y → y is
2.1 Linear Operators, Banach and Hilbert Spaces 7
bounded, i.e., if yX ≤ cyY holds true for all y ∈ Y with a finite constant c ∈ R
not depending on y.
In all what follows, we abstain from writing the index in a norm (for example, in
.X or .L(X,Y)), if there is no possibility of misunderstandings.
Exercise 2.1.1 Let X0 be a dense linear subspace of X and let Y be a Banach space.
Assume A0 ∈ L(X0 , Y). Show that there exists a unique extension A ∈ L(X, Y) of
A0 , i.e., Af = A0 f for all f ∈ X0 .
∞
Exercise 2.1.2 For a sequence (xn )n=1 of elements xn ∈ X of a normed space
∞
n ∞
(X, .), we say that the series xn is convergent if the sequence xk
n=1 k=1 n=1
∞
converges. It is called absolutely convergent, if the number series xn
n=1
converges. Show that X is a Banach space if and only if every absolutely convergent
series of elements of X is convergent in X.
Exercise 2.1.3 Prove that L(X, Y) is a Banach space if and only if Y is a Banach
space. (Hint: For the ⇒-direction, use Corollary 2.2.10 from Sect. 2.2 below.)
An operator P ∈ L(X, X) is called projection if P 2 = P. Since in this case, for
g = Pf , we have PgX = gX , we see that PX→X ≥ 1 for every continuous
projection P ∈ L(X, X).
Let H be a linear space over the field K = R or K = C, equipped with a so-called
inner product ., . : H × H −→ K having the following properties:
(I1) f, f ≥ 0 ∀ f ∈ H, and f, f = 0 if and only if f = ,
(I2) f, g = g, f ∀ f, g ∈ H (α denotes the complex conjugate number of
α ∈ C),
(I3) αf + βg, h = α f, h + β g, h ∀ f, g, h ∈ H, ∀ α, β ∈ K.
A linear space (H, ., .)
√with inner product is considered as a normed linear space
(H, .) with f := f, f . In such a space the Cauchy-Schwarz inequality
holds true,
| f, g | ≤ f g ∀ f, g ∈ H .
1 : m = n,
em , en = δmn := (2.1.1)
0 : m = n .
8 2 Basics from Linear and Nonlinear Functional Analysis
We remark that in this case the system {e0 , e1 , . . . , em } is linearly independent for
every m ∈ N0 . We denote the linear hull of this system by Hm and define the
operators Pm : H −→ H by
m
Pm f = f, ej ej .
j =0
∞
|f, ek |2 = f 2 ∀f ∈ H. (2.1.2)
k=0
lim f − Pm f = 0 ∀f ∈ H, (2.1.3)
m→∞
∞
which can also be written as f = f, ek ek (in the sense of convergence in H)
k=0
and which is a consequence of the relation
m
f − Pm f 2 = f − Pm f, f − Pm f = f 2 − Pm f 2 = f 2 − | f, ek |2 .
k=0
(2.1.4)
2.2 Fundamental Principles 9
∞
Exercise 2.1.4 Show that the orthonormal system (en )n=0 is complete if and only
∞
if the set H := Hm is dense in H, which means that every f ∈ H is the limit of
m=0
a sequence of elements of H.
There exist three fundamental principles in linear functional analysis, the principle
of uniform boundedness, the closed graph theorem, and the theorem on the sufficient
number of bounded linear functionals, which are closely connected with the Banach-
Steinhaus theorem, Banach’s theorem, and the Hahn-Banach theorem, respectively.
In the sequel, we will describe these principles in a short manner.
Principle of Uniform Boundedness Let X be a Banach space and Y be a normed
space. If a family F ⊂ L(X, Y) of bounded linear operators is pointwise bounded,
i.e.,
sup Af Y : A ∈ F < ∞ ∀f ∈ X,
lim An f − Af Y = 0 ∀f ∈ X.
n→∞
holds true. In view of Theorem 2.2.7, there exists a functional f ∈ X∗ such that
f (x) = f0 (x) for all x ∈ X0 and |f (x)| ≤ x∗ = f0 X∗ xX for all x ∈ X.
0
Thus, on the one hand f X∗ ≤ f0 X∗ . On the other hand, we have
0
f X∗ = sup {|f (x)| : x ∈ X, xX ≤ 1} ≥ sup {|f0 (x)| : x ∈ X0 , xX ≤ 1} = f0 X∗ ,
0
∞
∞
p
= ξ= (ξn )n=0 : ξn ∈ C , |ξn | < ∞
p
, (2.2.1)
n=0
1
+ q1 = 1 , its dual space ( p )∗ can be identified with q via the isometrical
p
isomorphism
p ∗ ∞
J : −→ q
, f → J f = η = (ηn )n=0 (2.2.4)
∞
p )∗
with f (ξ ) = ξn ηn for all ξ ∈ p (i.e., J : ( −→ q is linear and bijective
n=0
with J f = f ( for all f ∈ ( p )∗ ).
q p )∗
Exercise 2.2.12 Use Hölder’s inequality (2.2.3) to show that the map J :
( p )∗ −→ q defined in (2.2.4) is an isometrical isomorphism.
∞ p
For a sequence ω = (ωn )n=0 of positive numbers, by ω we denote the weighted
p ∞
√ ∞
space ω = x = (ξn )n=0 : p ωn ξn n=0 ∈ p equipped with the norm
∞
1
p
ξ p
ω
= ωn |ξn | p
. (2.2.5)
n=0
Of course,
p ∗ ∞
Jω : ω −→ q
ω, f → Jω f = η = (ηn )n=0 (2.2.6)
∞
p
with f (ξ ) = ωn ξn ηn for all ξ ∈ ω is an isometrical isomorphism (cf.
n=0
Exercise 2.2.12).
Corollary 2.2.13 Let 1 < p < ∞ and p1 + q1 = 1, and let αk ∈ C, γk > 0, k ∈ N0 ,
be given numbers. If there is a constant A ∈ R such that, for all βk ∈ C and all
n ∈ N,
n n 1
p
γk αk βk ≤ A γk |βk |p , (2.2.7)
k=0 k=0
then
∞ 1
q
γk |αk |q ≤ A. (2.2.8)
k=0
2.3 Compact Sets and Compact Operators 13
∞
Proof For γ = (γn )n=0 , define the linear functional
n
∞
fn : p
γ −→ C, ξ = (ξn )n=0 → γk αk ξk .
k=0
p ∗
By (2.2.7) we have fn ∈ γ and, since Jω in (2.2.6) is an isometrical
1
n q
isomorphism, fn p ∗
γ
= γk |αk |q ≤ A, which yields (2.2.8).
k=0
Let E be a metric space with the distance function d : E × E −→ [0, ∞). Recall
that a subset A ⊂ E is called compact if every covering of A by open sets contains a
finite covering of A and that A is called relatively compact if its closure is compact.
For ε > 0, by an ε-net for a nonempty subset A ⊂ E we mean a set Aε ⊂ E such
that for every x ∈ A there exists an xε ∈ Aε with d(x, xε ) < ε. This condition can
also be written in the formula
Aε ∩ Uε (x) = ∅ ∀x ∈ A,
where Uε (x) = UE
ε (x) denotes the (open) ε-neighbourhood of x ∈ E,
Exercise 2.3.1 Let A ⊂ E be a nonempty subset of a metric space (E, d). Show
that, if for every ε > 0 there exists a finite ε-net Aε ⊂ E for A, then, for every
ε > 0, there exists a finite ε-net Bε ⊂ A for A.
Exercise 2.3.2 Prove that A ⊂ E is relatively compact if and only if every sequence
∞
(xn )n=1 of points xn ∈ A possesses a convergent subsequence. Moreover, show that
a set A ⊂ E is relatively compact if, for every ε > 0, there exists a finite ε-net for
A, and that the reverse conclusion is true, if E is a complete metric space.
Note, that a subset of a finite dimensional normed space is relatively compact if
and only if it is bounded.
Lemma 2.3.3 Let X be a Banach space and Xn ⊂ X, n = 1, 2, . . . be a sequence
of finite dimensional subspaces of X. If A is a bounded subset of X and if
Then there exist gk ∈ A with Enk (gk ) ≥ ε, where we can assume that (due to the
relative compactness of A, cf. Exercise 2.3.2) gk −→ g ∗ for k −→ ∞ and for some
g ∗ ∈ X. Let k be sufficiently large, such that gk − g ∗ < ε2 . Then, for fnk ∈ Xnk ,
ε
ε ≤ fnk − gnk ≤ fnk − g ∗ + g ∗ − gnk < fnk − g ∗ +
2
implying that 2ε ≤ fnk − g ∗ for all fnk ∈ Xnk and all sufficiently large k. Hence,
∞
taking into account Xn ⊂ Xn+1 , we have ε
2 ≤ f − g ∗ for all f ∈ X0 := Xn ,
n=1
which contradicts the assumed density of X0 in X.
Let E be a compact metric space and denote by C(E) the Banach space of all
continuous functions f : E −→ C, where the norm is given by
Exercise 2.3.6 Let (E, d) be a metric space. A family F ⊂ C(E) is called (locally)
equicontinuous in x0 ∈ E, if for every ε > 0 there exists a δ > 0 such that
Show that, for a compact metric space (E, d), a set F ⊂ C(E) is equicontinuous if
and only if it is equicontinuous in every x0 ∈ E.
Exercise 2.3.7 For I = [−1, 1], I = [0, ∞], or I = [−∞, ∞], by (I, db ) we
denote the respective metric spaces defined by db (x, y) = | arctan(x) − arctan(y)|
π
with arctan(±∞) = ± . Prove that (I, db ) is a compact metric space.
2
Exercise 2.3.8 Show that, if E is one of the (compact) metric spaces from
Exercise 2.3.7, then the Banach space (C(E), .∞ ) is given by
⎧
⎪
⎪ C[−1, 1] : I = [−1, 1] ,
⎪
⎨
C(I) = {f ∈ C[0, ∞) : ∃ f (∞) := limx→∞ f (x)} : I = [0, ∞] ,
⎪
⎪
⎪
⎩
{f ∈ C(−∞, ∞) : ∃ f (±∞) := limx→±∞ f (x)} : I = [−∞, ∞] ,
Lemma 2.3.11 Assume that X and Y are Banach spaces, An , A ∈ L(X, Y),
An −→ A strongly, and M ⊂ X is relatively compact. Then
L(Y∗ , X∗ ). Using this and taking into account Corollary 2.3.12, prove the following:
If X, Y, Z, and W are Banach spaces, T ∈ K(X, Y), An , A ∈ L(Y, Z), and if
An −→ A strongly, as well as Bn , B ∈ L(W, X) and Bn∗ −→ B ∗ strongly, then
lim An T Bn − AT BL(W,Z) = 0. (For the definition of the adjoint operator B ∗
n→∞
of B, see Sect. 2.5.)
2.4.1 Lp -Spaces
is finite. In case p = ∞, by L∞ (I )
the space of all (classes of) measurable and
essentially bounded functions equipped with the norm
f L∞ (I ) = ess sup {|f (x)| : x ∈ I } := inf {sup {|f (x)| : x ∈ A} : A ⊂ I, m(A) = 0}
α,β
where pn (x) denotes the normalized Jacobi polynomial with respect to v α,β (x) of
degree n (cf. Sect. 5.1). Equipped with the inner product
∞
α,β
f, gα,β,s := (n + 1)2s f, pnα,β α,β
g, pn α,β
(2.4.2)
n=0
and the respective norm f α,β,s := f, f α,β,s , the space L2,s
α,β is again a Hilbert
2,0
space. Note that Lα,β = L2α,β .
Exercise 2.4.1 Show that L2,s α,β , ., . α,β,s is a Hilbert space.
Remark 2.4.2 It is well-known that, for 1 < p < ∞ and p1 + q1 = 1, the map J :
1
∗
Lq −→ Lp with (J g)(f ) = f (x)g(x) dx is an isometric isomorphism. For
p ∗ −1
this, we write L = Lq . Consequently, in the same way of identification we have
∗ 1
p q
Lv α,β = Lv −α,−β . Moreover, if we use (Jα,β g)(f ) = g(x)f (x)v α,β (x) dx,
∗ −1
q p
then Jα,β : Lα(q−1),β(q−1) −→ Lα,β is also an isometric isomorphism.
Example 2.4.3 Let −1 < α, β < 1, p > 1, and p1 + q1 = 1 and consider the integral
operator K defined by
1
(Kf )(x) = K(x, y)u(y)v α,β (y) dy , −1 < x < 1 ,
−1
|K(x, y)| ≤ c|x − y|−η , (x, y) ∈ (−1, 1)2 \ {(x, x) : x ∈ (−1, 1)} ,
p
for some η ∈ 0, q1 . By Hölder’s inequality we get, for f ∈ Lα,β and −1 < x < 1,
1 q1 1
−ηq α,β − −
f α,β,(p) ≤ c v −α ,−β (x)
q
|(Kf )(x)| ≤ c |x − y| v (y) dy f α,β,(p) ,
−1
where α± = max {0, ±α}, β± = max {0, ±β}, and where we took into account
Lemma 5.2.10. Consequently,
1 q1 1 q1
q −α,−β −α + ,−β +
Kf −α,−β,(q) = |(Kf )(x)| v (x) dx ≤c v (x) dx f α,β,(p) ,
−1 −1
p + +
1
≤ c v −α ,−β Lq 1 (−1,1).
q
i.e., K ∈ L Lα,β , L−α,−β with KLp q
α,β →L−α,−β
∞
1
! "2 2
f α,β,s,∼ := (m + 1) 2s−1 α,β
Em (f )2 ,
m=0
2.4 Function Spaces 19
α,β
where Em (f )p := inf f − P α,β,(p) : P ∈ Pm with Pm being the set of
α,β
polynomials of degree less than m and E0 (f )2 := f α,β . Since, in case γ ≤ α
and δ ≤ β, L2γ ,δ is continuously embedded into L2α,β , we have also the continuous
embedding L2,s 2,s
γ ,δ into Lα,β in this case.
Consequently,
∞
∞
2 ∞ 2
n
f 2α,β,s,∼ = (m + 1)2s−1 f, pnα,β α,β = f, pnα,β α,β (m + 1)2s−1 ,
m=0 n=m n=0 m=0
n n
1
1 m + 1 2s−1 1
lim (m + 1) 2s−1
= lim = x 2s−1 dx
n→∞ (n + 1)2s n→∞ n+1 n+1 0
m=0 m=0
2,1
with domain D(E) = Lα,β (cf. [18, Chapter III, §6.9]). Hence, these spaces have
the interpolation property, i.e., if the linear operator A is bounded from L2,s 1
α1 ,β1
2,s (τ )
into L2,s 2,t1 2,t2
α2 ,β2 and from Lα1 ,β1 into Lα2 ,β2 , then A is also bounded from Lα1 ,β1 into
2 1
2,s (τ )
2
Lα2 ,β 2
, where sj (τ ) = (1 − τ )sj + τ tj and 0 < τ < 1 [18, Chapter III, §6.9,
Theorem 6.10].
Lemma 2.4.6 (cf. [20, Lemma 4.2]) If h(x, .) ∈ L2α,β for all (or almost all) x ∈
[−1, 1] and h(., y) ∈ L2,s
γ ,δ uniformly with respect to y ∈ [−1, 1], then the linear
operator H : L2α,β −→ L2,s
γ ,δ defined by
1
(Hf )(x) = h(x, y)f (y)v α,β (y) dy , −1 < x < 1 ,
−1
is bounded.
20 2 Basics from Linear and Nonlinear Functional Analysis
Proof For f ∈ L2α,β and m ∈ N0 , using Fubini’s theorem and the Cauchy-Schwarz
inequality we can estimate
2 1 1
2
= (y) dy pm (x)v (x) dx
γ ,δ γ ,δ
Hf, pm γ ,δ
h(x, y)f (y)v α,β γ ,δ
−1 −1
2
1
=
γ ,δ α,β
h(., y), pm γ ,δ
f (y)v (y) dy
−1
1 2
γ ,δ α,β
≤ h(., y), pm γ ,δ
v (y) dyf 2α,β .
−1
Hence,
∞
2
γ ,δ
Hf 2γ ,δ,s = (1 + m)2s Hf, pm γ ,δ
m=0
∞
1 2
γ ,δ α,β
≤ (1 + m)2s h(., y), pm γ ,δ
v (y) dyf 2α,β
−1 m=0
1
= h(., y)2γ ,δ,s v α,β (y) dyf 2α,β ≤ c f 2α,β ,
−1
This implies
x ! (k+1) "
fn(k) (x) − Pn(k) (x) − g (k)
(x) = fn (y) − Pn(k+1) (y) − g (k+1) (y) dy
0
p,r
Exercise 2.4.10 Let 1 ≤ p < ∞ and u = v γ ,δ , γ , δ > − p1 . Prove that Wu
equipped with the norm defined in (2.4.4) as well as with the norm
r
(k) k
f ϕ u (2.4.5)
p
k=0
(cf. Lemma 2.4.7) becomes a Banach space and that these two norms are equivalent
p,r
on Wu .
As a conclusion of Exercise 2.4.10 we have the following property of a
multiplication operator. For this, we define the space Crϕ of all r times continuously
differentiable functions f : (−1, 1) −→ C satisfying the conditions f (k) ϕ k ∈
C[−1, 1] for k = 0, 1, . . . , r. This space, equipped with the norm f Crϕ =
r
(k) k
f ϕ , is a Banach space.
∞
k=0
Using
k
k (j ) j (k−j ) k−j
(af ) ϕ =
(k) k
a ϕ f ϕ ,
j
j =0
k
k (j ) j
r
af Wp,r ≤ a ϕ f (k−j ) ϕ k−j
u j ∞ p
k=0 j =0
≤ max a (j )ϕ j max f (k−j ) ϕ k−j 2r+1
0≤j ≤r ∞ 0≤j ≤r p
≤ caCrϕ f Wp,r
u
,
γ δ
Corollary 2.4.12 Since we have W2,ru = L2,r
γ ,δ for r ∈ N0 and u = v
2 , 2 , we
can apply Corollary 2.4.11 together with Remark 2.4.5. Hence, for a ∈ Crϕ , the
multiplication operator aI : L2,s 2,s
γ ,δ −→ Lγ ,δ is continuous for 0 ≤ s ≤ r.
p,r
The Besov-type space Bq,u basing on the kth weighted modulus of continuity
p
of a function f ∈ Lu given by
# $
kϕ (f, t)u,p = sup khϕ f u :0<h≤t , (2.4.6)
Lp (Ihk )
where, for k ∈ N,
k
k k
khϕ f (x) = j
(−1) f x+ − j hϕ(x) (2.4.7)
j 2
j =0
! "
and Ihk = −1 + 2h2 k 2 , 1 − 2h2 k 2 , can be defined as follows. If we set, for k ≥ r,
⎧
⎪
⎪ 1% k &q q1
⎪
⎪
ϕ (f, t)u,p
⎪
⎨ dt : 1 ≤ q < ∞,
0 r+ 1
|f |u,p,q,r := t q
⎪
⎪
⎪
⎪ kϕ (f, t)u,p
⎪
⎩ sup : q=∞
t >0 tr
and f Bp,r
q,u
:= f up + |f |u,p,q,r , then, for 1 ≤ p ≤ ∞, 1 ≤ q ≤ ∞, and r > 0,
p,r p
Bq,u := f ∈ Lu : f Bp,r
q,u
< ∞ . (2.4.8)
Note, that
p,r
(a) Bq,u , .Bp,r
q,u
is a Banach space,
p,r p,r
(b) in case r ∈ N, we have the equality B∞,u = Wu with equivalent norms,
p,[r]+1
(c) for 1 ≤ q ≤ ∞ and r > 0, we have the continuous embeddings Wu ⊂
p,r p,[r]
Bq,u ⊂ Wu (see [139, Proposition 3.3]).
We refer also to Sect. 3.1.3.
For a compact interval [a, b] ⊂ R, by C[a, b] = (C[a, b], .∞ ) we refer to the
linear space of all continuous functions f : [a, b] −→ C, which is, equipped
with the infinity or Chebyshev-norm f ∞,[a,b] := max {|f (x)| : a ≤ x ≤ b}, a
24 2 Basics from Linear and Nonlinear Functional Analysis
Banach space, even a Banach algebra. (See also Exercise 2.4.19 below as well as
Sect. 2.3 and Exercise 2.3.8.) The linear subspace Cr,λ [a, b] of C[a, b] is defined
for r ∈ N0 and 0 < λ ≤ 1 and consists of those functions f : [a, b] −→ C, which
are r times continuously differentiable and the rth derivative of which is Hölder
continuous on [a, b], i.e.,
(r)
f (x1 ) − f (r) (x2 )
cr,λ,[a,b](f ) := sup : a ≤ x1 < x2 ≤ b < ∞ .
|x1 − x2 |λ
r
(k)
f Cr,λ [a,b] = f + cr,λ,[a,b] (f ) (2.4.9)
∞,[a,b]
k=0
and makes it to a Banach space (see Exercise 2.4.17). In case of [a, b] = [−1, 1],
we will write C, Cr,λ , f ∞ , and cr,λ (f ) instead of C[−1, 1], Cr,λ [−1, 1],
f ∞,[−1,1] , and cr,λ,[−1,1](f ), respectively.
Exercise 2.4.13 Show that, for 0 < λ < 1 and 0 < x < 1,
and that the function ϕλ (x) = |x|λ , −1 ≤ x ≤ 1, belongs to C0,λ [−1, 1].
If A ⊂ C0,λ [a, b] is a bounded set in C0,λ [a, b], .C0,λ [a,b] , i.e.,
f C0,λ [a,b] ≤ cA < ∞ for all f ∈ A, then f ∞,[a,b] ≤ cA and |f (x1 ) − f (x2 )| ≤
cA |x1 − x2 |λ for all f ∈ A, which implies that the set A is a uniformly bounded
set of equicontinuous functions. Thus, by the Arzela-Ascoli Theorem 2.3.5, the set
A is relatively compact in C[a, b], i.e., we get the following corollary (see also
Exercise 2.4.18).
Corollary 2.4.14 C0,λ [a, b], .C0,λ [a,b] is compactly embedded into C[a, b],
.∞,[a,b] .
Exercise 2.4.15 Prove that Cr,μ [a, b] ⊂ Cr,λ [a, b] for 0 < λ ≤ μ ≤ 1.
Exercise 2.4.16 For a < b < c, prove that
f ∈ Cr,λ [a, b] ∩ Cr,λ [b, c] : f (j) (b − 0) = f (j) (b + 0), j = 0, . . . , r = Cr,λ [a, c] .
Exercise
r,λ 2.4.17 Show that (2.4.9) defines a norm in Cr,λ [a, b] and that
C [a, b], .Cr,λ [a,b] is a Banach space.
Exercise 2.4.18 Let 0 < λ < μ. By using the compact embedding C0,μ [a, b] ⊂
C[a, b] (see Corollary 2.4.14), prove that C0,μ [a, b] is compactly embedded into
C0,λ [a, b].
2.4 Function Spaces 25
Exercise 2.4.19 Prove that C0,λ [a, b] is a Banach algebra, i.e., that additionally
to the properties of a Banach space we have, for f, g ∈ C0,λ [a, b],
(x − y)|x − y|−λ : x = y ,
h(x, y) =
0 : x =y.
Show that h(., y) ∈ C0,1−λ uniformly with respect to y ∈ [−1, 1], i.e.,
f : [0, a] −→ R, x → x μ ln x (f (0) := 0)
belongs to C0,λ [0, a] for every λ ∈ (0, μ). Moreover, prove that, for every λ ∈
(0, 1), there is a constant cλ such that
Note that the set P of all algebraic polynomials (with complex coefficients) is
dense in Cγ ,δ (cf. the following Exercise 2.4.23 for the case 0 ≤ γ , δ ≤ 1 and
Exercise 6.2.5 for the general case γ , δ ≥ 0). For f ∈ Cbγ ,δ , we define the best
26 2 Basics from Linear and Nonlinear Functional Analysis
γ ,δ γ ,δ
weighted uniform approximation Em (f ) = Em (f )∞ = Em (f )v γ ,δ ,∞ of f by
polynomials, belonging to the subset Pm of P of all polynomials of degree less than
m ∈ N, as
γ ,δ
Em (f ) = inf f − pγ ,δ,∞ : p ∈ Pm .
γ ,δ
In case m = 0, we set E0 (f ) := f γ ,δ,∞ .
Exercise 2.4.23 Show that, for 0 ≤ γ , δ ≤ 1 and f ∈ Cbγ ,δ , we have
γ ,δ
lim Em (f ) = 0 if and only if f ∈ Cγ ,δ . Conclude that Cγ ,δ is equal to the
m→∞
smallest closed subspace of Cbγ ,δ containing the set P of all polynomials.
Exercise 2.4.24 Prove that, for all f ∈ Cbγ ,δ and all n ∈ N, there exists a
f f γ ,δ
polynomial Pn ∈ Pn such that f − Pn = En (f ).
γ ,δ,∞
Exercise 2.4.25 For −1 < xN < . . . < x1 < 1 and αk ∈ C \ {0}, consider the
N
linear functional ϕ : Cbγ ,δ −→ C, f → αk f (xk ) and show that
k=1
N
ϕ(Cb ∗ = v −γ ,−δ (xk )|αk |.
γ ,δ )
k=1
Lemma 2.4.26 For α, β > −1 and s > 12 , the space L2,s is continuously embed-
α,β
ded into the space Cγ ,δ , where γ = 12 max 0, α + 12 and δ = 12 max 0, β + 12 .
α,β α,β
Proof Let f ∈ L2,s
α,β , s > 2 , and f0 = v
1 γ ,δ f as well as p
n =v
γ ,δ p
n . Moreover,
define
# $ # $
1 1
γ1 := α−2γ = α−max 0, α + and δ1 := β−2δ = β−max 0, β + .
2 2
∞
∞ 1
∞
2
−2s
f0 , pnα,β pα,β (x)
γ1 ,δ1 n
≤c f0 , pnα,β γ1 ,δ1 ≤ c f α,β,s (n + 1) .
n=k n=k n=k
2.4 Function Spaces 27
Thus,
the Fourier
series of the function f0 with respect to the orthonormal system
α,β
pn : n ∈ N0 in L2γ1 ,δ1 converges uniformly on [−1, 1], which implies that f0 :
[−1, 1] −→ C is continuous. Moreover, the last estimate shows that f γ ,δ,∞ ≤
c f α,β,s .
∞
For a sequence ξ = (ξn )n=0 of positive real numbers tending to zero for n −→
ξ
∞, by Cγ ,δ we refer to the space of all functions f ∈ Cγ ,δ , for which the number
f γ ,δ,ξ := sup ξn−1 En (f ) : n ∈ N0
γ ,δ
(2.4.12)
γ ,δ γ ,δ γ ,δ γ ,δ γ ,δ
is finite. Since En (f +g) ≤ En (f )+En (g) and En (λf ) = |λ|En (f ) is true
ξ
for all f, g ∈ Cγ ,δ and all λ ∈ C, by (2.4.12) a norm is defined on Cγ ,δ . Therefore,
ξ
by Cγ ,δ we will refer to the space equipped with this norm. In case ξ0 = ξ1 = 1 and
ξn = n−ρ lnτ n, n ≥ 2, ρ > 0, τ ∈ R, we write Cγ ,δ instead of Cγ ,δ and .γ ,δ,ρ,τ
ρ,τ ξ
1 12
f α,β ≤ (1 − x) α−2γ
(1 + x) β−2δ
dx f γ ,δ,∞ = c f γ ,δ,∞ ,
−1
α,β γ ,δ ρ+ε,τ
we have also En (f )2 ≤ c En (f ) with c = c(n). Consequently, for f ∈ Cγ ,δ ,
due to Lemma 2.4.4 we can estimate
∞
! "2
f 2α,β,ρ ≤ c (n + 1)2ρ−1 Enα,β (f )2
n=0
# $
∞
2
≤ c sup (n + 1)2(ρ+ε) ln−2τ (n + 2) En (f ) (n + 1)−2ε−1 ln2τ (n + 2)
γ,δ
: n ∈ N0
n=0
2
≤ c sup (n + 1)ρ+ε ln−τ (n + 2)En (f ) : n ∈ N0
γ,δ
≤ c f 2γ,δ,ρ+ε,τ ,
γ ,δ γ ,δ γ ,δ
En (f ) ≤ En f − fmn + En fmn ≤ (1 + M)ξn .
ξ
Hence, the function f belongs to Cγ ,δ . Moreover, for every ε > 0, there exists
an m0 ∈ N such that fk − fm γ ,δ,ξ ≤ ε for all k,m ≥ m0 . For n ∈ N0 ,
choose a natural number kn ≥ m0 satisfying f − fkn γ ,δ,∞ ≤ ε ξn . Then, for
all m ≥ m0 ,
γ ,δ γ ,δ γ ,δ
En (f − fm ) ≤ En f − fkn + En fkn − fm ≤ 2 ε ξn , n ∈ N,
ξ
which shows that fm converges to f in the norm of Cγ ,δ .
ξ
(b) Since ξn −→ 0, we have Cγ ,δ ⊂ Cγ ,δ (cf. Exercise 2.4.23). Let M be a bounded
ξ f
subset of Cγ ,δ , say f γ ,δ,ξ ≤ c0 < ∞ for all f ∈ M. Moreover, let Pn ∈
f
Pn be a polynomial with f − Pn γ ,δ,∞ = En (f ) (cf. Exercise 2.4.24). It
γ ,δ
f
which implies Pn ∞ ≤ c3 n2 max{γ ,δ} , since, for each polynomial p ∈ Pn , we
have the Remez inequality (cf. Proposition 3.2.21)
# $
1
p∞ ≤ c sup |p(x)| : |x| ≤ 1 − 2 , c = c(n, p) . (2.4.13)
2n
Then v γ ,δ ∈ C0,λ for λ = min {γ0 , δ0 }. For ε > 0, we can choose n0 ∈ N, such
that c0 ξn0 < 4ε , and set
1
λ
ε
η := 2(1+max{γ ,δ}) .
6 c3 n0 v γ ,δ 0,λ
C
f f f f
≤ f (x1 ) − pn0 (x1 ) vγ ,δ (x1 ) + pn0 (x1 )vγ ,δ (x1 ) − pn0 (x2 )vγ ,δ (x2 ) + pn0 (x2 ) − f (x2 ) vγ ,δ (x2 )
f
≤ 2En0 (f ) + pn0 C0,λ vγ ,δ C0,λ |x1 − x2 |λ
γ ,δ
f
≤ 2 c0 ξn0 + 3 n20 pn0 ∞ vγ ,δ C0,λ ηλ ≤ ε ,
we have
1−λ
pm C0,λ ≤ pm ∞ + pm 2
∞
≤ (1 + 21−λ m2 )pm ∞ ≤ 3 m2 pm ∞ .
ξ
(c) Let M be a bounded subset of Cγ ,δ as in the proof of (b), from which we
also conclude that every sequence of elements from M has a subsequence
30 2 Basics from Linear and Nonlinear Functional Analysis
∞
(fm )m=1 convergent in Cγ ,δ , i.e., there exists a function f ∈ Cγ ,δ with
lim fm − f γ ,δ,∞ = 0. For each n ∈ N, choose mn ∈ N such that
m→∞
mn > mn−1 (m0 := 0) and fmn − f γ ,δ,∞ ≤ ξn and let pn∗ be a polynomial
from Pn with pn∗ − fmn γ ,δ,∞ = En (fmn ). Then
γ ,δ
∗
p − f ≤ pn∗ − fmn γ ,δ,∞ + fmn − f γ ,δ,∞ ≤ (c0 + 1)ξn ,
n γ ,δ,∞
ξ
which means that f belongs to Cγ ,δ . For ε > 0, choose an n0 ∈ N, such that
ξn
< ε for all n > n0 , and an n1 ∈ N, such that fm − f <
ηn 2 f γ ,δ,ξ +c0 n γ ,δ,∞
ε min 1,η0 ,...,ηn0
2 for all n > n1 . Then, for all n > n1 ,
εηn
En (f − fmn ) ≤ f − fmn γ ,δ,∞ <
γ ,δ
, n = 0, 1, 2, . . . , n0 ,
2
and
γ ,δ εηn
En (f − fmn ) ≤ f γ ,δ,ξ + c0 ξn < , n = n0 + 1, n0 + 2, . . .
2
Consequently, f − fmn γ ,δ,η < ε for all n > n1 .
(d) Since ξn ≤ c0 ηn , n ∈ N0 with some real constant c0 , the claimed embedding
ξ η
follows immediately from the definition of the norms in Cγ ,δ and Cγ ,δ .
(e) The assertion is a conclusion of the continuous embedding Cγ ,δ ⊂ Cρ,τ .
For a√function f : (−1, 1) −→ C, for r ∈ N, h, t > 0, γ , δ ≥ 0, and for
ϕ(x) = 1 − x 2 , define the symmetric difference of order r (cf. (2.4.7))
r r
k r
hϕ f (x) :=
r
(−1) f x+ − k h ϕ(x) , (2.4.16)
k 2
k=0
“In the whole course of my life I have never met with such stupendous
and finished specimens of human labor and of the science and taste of
ages long since forgot, crowded together in so small a compass, as in this
little spot [Brambanam], which, to use a military phrase, I deem to have
been the headquarters of Hinduism in Java.” (Report to Sir Stamford
Raffles by Captain George Baker of the Bengal establishment.)
There are ruins of more than one hundred and fifty temples in the
historic region lying between Djokjakarta and Soerakarta, or Djokja
and Solo, as common usage abbreviates those syllables of
unnecessary exertion in this steaming, endless mid-summer land of
Middle Java. As the train races on the twenty miles from Djokja to
Brambanam, there is a tantalizing glimpse of the ruined temples at
Kalasan; and one small temple there, the Chandi Kali Bening, ranks
as the gem of Hindu art in Java. It is entirely covered, inside as well
as outside, with bas-reliefs and ornamental carvings which surpass
in elaboration and artistic merit everything else in this region, where
refined ornament and lavish decoration reached their limit at the
hands of the early Hindu sculptors. The Sepoy soldiers who came
with the British engineers were lost in wonder at Kalasan, where the
remains of Hindu art so far surpassed anything they knew in India
itself; while the extent and magnificence of Brambanam’s Brahmanic
and Buddhist temple ruins amaze every visitor—even after Boro
Boedor.
TEMPLE OF LORO JONGGRAN AT BRAMBANAM.
The pity of all this ruined splendor moves one strongly, and one
deplores the impossibility of reconstructing, even on paper, the
whole magnificent place of worship. The wealth of ornament makes
all other temple buildings seem plain and featureless, and one set of
bas-reliefs just rescued and set up in line, depicting scenes from the
Ramayan, would be treasure enough for an art museum. On this
long series of carved stones disconsolate Rama is shown searching
everywhere for Sita, his stolen wife, until the king of the monkeys,
espousing his cause, leads him to success. The story is wonderfully
told in stone, the chisel as eloquent as the pen, and everywhere one
reads as plainly the sacred tales and ancient records. The graceful
figures and their draperies tell of Greek influences acting upon those
northern Hindus who brought the religion to the island; and the
beautifully conventionalized trees and fruits and flowers, the mythical
animals and gaping monsters along the staircases, the masks,
arabesques, bands, scrolls, ornamental keystones, and all the
elaborate symbols and attributes of deities lavished on this group of
temples, constitute a whole gallery of Hindu art, and a complete
grammar of its ornament.
When the director was called away to his workmen, we bade our
guiding Mohammedan lead the way to Chandi Sewou, the
“Thousand Temples,” or great Buddhist shrine of the ancient capital.
“Oh,” he cried, “it is far, far from here—an hour to walk. You must go
to Chandi Sewou in a boat. The water is up to here,” touching his
waist, “and there are many, many snakes.” Distrusting, we made him
lead on in the direction of Chandi Sewou; perhaps we might get at
least a distant view. When we had walked the length of a city block
down a shady road, with carved fragments and overgrown stones
scattered along the way and through the young jungle at one side,
we turned a corner, walked another block, and stood between the
giant images that guard the entrance of Chandi Sewou’s great
quadrangle.
The “Thousand Temples” were really but two hundred and thirty-
six temples, built in five quadrilateral lines around a central cruciform
temple, the whole walled inclosure measuring five hundred feet
either way. Many of these lesser shrines—mere confessional boxes
in size—are now ruined or sunk entirely in the level turf that covers