# Book:Philippe G. Ciarlet/Linear and Nonlinear Functional Analysis with Applications

## Philippe G. Ciarlet: Linear and Nonlinear Functional Analysis with Applications

Published $\text {2013}$, Society for Industrial and Applied Mathematics

ISBN 978-1611972580.

### Subject Matter

Functional Analysis
Partial Differential Equations
Differential Geometry

### Contents

Preface

1. Real Analysis and Theory of Functions: A Quick Review
Introduction
1.1 Sets
1.2 Mappings
1.3 The axiom of choice and Zorn's lemma
1.4 Construction of the sets $\R$ and $\C$
1.5 Cardinal numbers; finite and infinite sets
1.6 Topological spaces
1.7 Continuity in topological spaces
1.8 Compactness in topological spaces
1.9 Conectedness and simple-conectedness in topological spaces
1.10 Metric spaces
1.11 Continuity and uniform continuity in metric spaces
1.12 Complete metric spaces
1.13 Compactness in metric spaces
1.14 The Lebesgue measure in $\R^n$; measurable functions
1.15 The Lebesgue integral in $\R^n$; the basic theorems
1.16 Change of variable in Lebesgue integrals in $\R^n$
1.17 Volumes, areas, and lengths in $\R^n$
1.18 The spaces $\map {\cal {C}^m} \Omega$ and $\map {\cal {C}^m} {\bar \Omega}$; domains in $\R^n$
2. Normed Vector Spaces
Introduction
2.1 Vector spaces; Hamel bases; dimension of a vector space
2.2 Normed vector spaces; first properties and examples; quotient spaces
2.3 The space $\map {\cal C} {K;Y}$ with $K$ compact; uniform convergence and local uniform convergence
2.4 The spaces ${\cal l}^p, 1 \le p \le \infty$
2.5 The Lebesgue spaces $\map {L^p} \Omega, 1 \le p \le \infty$
2.6 Regularization and approximation in the spaces $\map {L^p} \Omega, 1 \le p < \infty$
2.7 Compactness and finite-dimensional normed vector spaces; F. Riesz theorem
2.8 Application of compactness in finite-dimensional normed vector space: The fundamental theorem of algebra
2.9 Continuous linear operators in normed vector soaces; the spaces $\map {\cal L} {X;Y}$, $\map {\cal L} X$, and $X'$
2.10 Compact linear operatros in normed vector spaces
2.11 Continuous multilinear mappings in normed vector spaces; the space $\map { {\cal L}_k} {X_1, X_2, \dots , X_k; Y}$
2.12 Korovkin's theorem
2.13 Application of Korovkin's theorem to polynomial approximation; Bohman's, Bernstein's, and Weierstrass' theorems
2.14 Application of Korovkin's theorem to trigonometric polynomial approximation; Fejér's theorem
2.15 The Stone-Weierstrass theorem
2.16 Convex sets
2.17 Convex functions
3. Banach Spaces
Introduction
3.1 Banach spaces; first properties
3.2 First examples of Banach spaces; the spaces $\map {\cal C} {K;Y}$ with $K$ compact and $Y$ complete, and ${\cal L} {X;Y}$ with $Y$ complete
3.3 Integral of a continuous function of a real variable with values in a Banach space
3.4 Further examples of Banach spaces: the spaces $l^p$ and $\map {L^p} \Omega$, $, \le p \le \infty$
3.5 Dual of a normed vector space; first examples; F. Riesz representation theorem in $\map {L^p} \Omega$, $1 \le p < \infty$
3.6 Series in Banach space
3.7 Banach fixed point theorem
3.8 Application of Banach fixed point theorem: Existence of solutions to nonlinear ordinary differential equations; Cauchy-Lipschitz theorem; the pendulum equation
3.9 Applictaion of Banach fixed point theorem: Existence of solutions to nonlinear two-point boundary value problems
3.10 Ascoli-Arzelà's theorem
3.11 Application of Ascoli-Arzelà's theorem: Existence of solutions to nonlinear ordinary differential equations; Cauchy-Peano theorem; Euler's method
4. Inner Product Spaces and Hilbert Spaces
Introduction
4.1 Inner-product spaces and Hilbert spaces; first properties; Cauchy-Schwarz-Bunyakovskii inequality; parallelogram law
4.2 First examples of inner-product spaces and Hilbert spaces; the spaces $l^2$ and $\map {L^2} \Omega$
4.3 The projection theorem
4.4 Application of the projection theorem; Least-squares solution of a linear system
4.5 Orthogonality; direct sum theorem
4.6 F. Riesz representation theorem in a Hilbert space
4.7 First applications of the F. Riesz representation theorem: Hahn-Banach theorem in a Hilbert space; adjoint operators; reproducing kernels
4.8 Maximal orthonormal families in an inner-product space
4.9 Hilbert bases and Fourier series in a Hilbert space
4.10 Eigenvalues and eigenvectors of self-adjoint operators in inner-product spaces
4.11 The spectral theorem for compact self-adjoint operators
5. The "Great Theorems" of Linear Functional Analysis
Introduction
5.1 Baire's theorem; a first application: Noncompleteness of the space of all polynomials
5.2 Application of Baire's theorem: Existence of nowhere differentiable continuous functions
5.3 Banach-Steinhaus theorem, alias the uniform boundedness principle; application to numerical quadrature formulas
5.4 Application of the Banach-Steinhaus theorem: Divergence of Lagrange interpolation
5.5 Application of the Banach-Steinhaus theorem: Divergence of Fourier series
5.6 Banach open mapping theorem; a first application: Well-posedness of two-point boundary value problems
5.7 Banach closed graph theorem; a first application: Hellinger-Toeplitz theorem
5.8 The Hahn-Banach theorem in a vector space
5.9 The Hahn-Banach theorem in a normed vector space: first consequences
5.10 Geometric forms of the Hahn-Banach theorem; separation of convex sets
5.11 Dual operators; Banach closed range theorem
5.12 Weak convergence and weak* convergence
5.13 Banach-Saks-Mazur theorem
5.14 Reflexive spaces; the Banach-Eberlein-Šmulian theorem
6. Linear Partial Differential Equations
Introduction
6.1 Quadratic minimization problems; variational equations and variational inequalities
6.2 The Max-Milgram lemma
6.3 Weak partial derivative in $\map {L_{loc}^1} \Omega$; a brief incursion into distribution theory
6.4 Hypoellipticity of $\Delta$
6.5 The Sobolev spaces $\map {W^{m,p} } \Omega$ and $\map {H^m} \Omega$: First properties
6.6 The Sobolev spaces $\map {W^{m,p} } \Omega$ and $\map {H^m} \Omega$ with $\Omega$ a domain: imbedding theorems, traces, Green's formulas
6.7 Examples of second-order linear elliptic boundary value problems; the membrane problem
6.8 Examples of fourth-order linear boundary value problems; the biharmonic and plate problems
6.9 Examples of nonlinear boundary value problems associated with variational inequalities; obstacle problems
6.10 Eigenvalue problems for second-order elliptic operators
6.11 The spaces $\map {W^{-m,q} } \Omega$ and $\map {H^{-m} } \Omega$; J. L. Lions lemma
6.12 The Babuška-Brezzi inf-sup theorem; application to constrained quadratic minimization problems
6.13 Application of the Babuška-Brezzi inf-sup theorem: Primal, mixed, and dual formulations of variational problems
6.14 Application of the Babuška-Brezzi inf-sup theorem and of J. L. Lions lemma: The Stokes equations
6.15 A second application of J. L. Lions lemma: Korn's inequalitity
6.16 Application of Korn's inequality: The equations of three-dimensional linearized elasticity
6.17 The classical Poincaré lemma and its weak version as an application of J. L. Lions lemma and of the hypoellipticity of $\Delta$
6.18 Application of Poincaré's lemma: The classical and weak Saint-Venant lemmas; the Cesàro-Volterra path integral formula
6.19 Another application of J. L. Lions lemma: The Donati lemmas
6.20 Pfaff systems
7. Differential Calculus in Normed Vector Spaces
Introduction
7.1 The Fréchet derivative; the chain rule; the Piola identity; application to extrema of real-valued functions
7.2 The mean value theorem in a normed vector space; first applications
7.3 Application of the mean value theorem: Differentiability of the limit of a sequence of differentiable functions
7.4 Application of the mean value theorem: Differentiability of a function defined by an integral
7.5 Application of the mean value theorem: Sard's theorem
7.6 A mean value theorem for functions of class ${\cal C}^1$ with values in a Banach space
7.7 Newton's method for solving nonlinear equations; the Newton-Kantorovich theorem in a Banach space
7.8 Higher order derivatives; Schwarz lemma
7.9 Taylor formulas; application to extrema of real-valued functions
7.10 Application: Maximum principle for second-order linear elliptic operators
7.11 Application: Lagrange interpolation in $\R^n$ and multipoint Taylor formulas
7.12 Convex functions and differentiability; application to extrema of real-valued functions
7.13 The implicit functions theorem: first application: Class ${\cal C}^\infty$ of the mapping $A \rightarrow A^{-1}$
7.14 The local inversion theorem; the invariance of domain theorem for mappings of class ${\cal C}^1$ in Banach spaces; class ${\cal C}^\infty$ of the mapping $A \rightarrow A^{1/2}$
7.15 Constrained extrema of real-valued functions; Lagrange multipliers
7.16 Lagrangians and saddle-points; primal and dual problems
8. Differential Geometry in $\R^n$
Introduction
8.1 Curvilinear coordinates in an open subset of $\R^n$
8.2 Metric tensor; volumes and legths in curvilinear coordinates
8.3 Covariant derivative of a vector field
8.4 Tensors - a brief introduction
8.5 Necessary conditions satisfied by the metric tensor; the Riemann curvature tensor
8.6 Existence of an immersion on an open subset $\R^n$ with a prescribed metric tensor; the fundamental theorem of Riemannian geometry
8.7 Uniqueness up to isometries of immersions with the same metric tensor; the rigidity theorem for an open subset of $\R^n$
8.8 Curvilinear coordinates on a surface in $\R^3$
8.9 First fundamental form of a surface; areas, lengths, and angles on a surface
8.10 Isometric, equiareal, and conformal surfaces
8.11 Second fundamental form of a surface; curvature on a surface
8.12 Principal curvatures; Gaussian curvature
8.13 Covariant derivatives of a vector field defined on a surface; the Gauss and Weingarten formulas
8.14 Necessary conditions satisfied by the first and second fundamental forms; The Gauss and Codazzi-Mainardi equations
8.15 Gauss Theorema Egregium; applicaiton to cartography
8.16 Existence of a surface with prescribed first and second fundamental forms; the fundamental theorem of surface theory
8.17 Uniqueness of surfaces with the same fundamental forms; the rigidity theorem for surfaces
9. The "Great Theorems" of Nonlinear Functional Analysis
Introduction
9.1 Nonlinear partial differential equations as the Euler-Lagrange equations associated with the minimization of a functional
9.2 Convex function and sequentially lower semicontinuous functions with values in $\R \cup \set \infty$
9.3 Existence of minimizers for coercive and sequentailly weakly lower semicontinuous functionals
9.4 Applications to the von Kármán equations
9.5 Existence of minimizers in $\map {W^{1,p} } \Omega$
9.6 Application to the $p-$Laplace operator
9.7 Polyconvexity; compensated compactness; John Ball's existence theorem in nonlinear elasticity
9.8 Ekeland's variational principle; existence of minimizers for functional that satisfy the Palais-Smale condition
9.9 Brouwer's fixed point theorem - a first proof
9.10 Application of Brouwer's theorem to the von Kármán equations, by means of the Galerkin method
9.11 Application of Brouwer's theorem to the Navier-Stokes equations, by means of the Galerkin method
9.12 Schauder's fixed point theorem; Schäfer's fixed point theorem; Leray-Schauder fixed point theorem
9.13 Monotone operators
9.14 The Minty-Browder theorem for monotone operators; application to the $p-$Laplace operator
9.15 The Brouwer topological degree in $\R^n$: Definition and properties
9.16 Brouwer's fixed point theorem - a second proof - and the hairy ball theorem
9.17 Borsuk's and Borsuk-Ulam theorems; Brouwer's invariance of domain theorem

Bibliographical Notes

Bibliography

Main Notations

Index