A Remark on Sobolev Spaces. the Case 0
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Sobolev Spaces, Theory and Applications
Sobolev spaces, theory and applications Piotr Haj lasz1 Introduction These are the notes that I prepared for the participants of the Summer School in Mathematics in Jyv¨askyl¨a,August, 1998. I thank Pekka Koskela for his kind invitation. This is the second summer course that I delivere in Finland. Last August I delivered a similar course entitled Sobolev spaces and calculus of variations in Helsinki. The subject was similar, so it was not posible to avoid overlapping. However, the overlapping is little. I estimate it as 25%. While preparing the notes I used partially the notes that I prepared for the previous course. Moreover Lectures 9 and 10 are based on the text of my joint work with Pekka Koskela [33]. The notes probably will not cover all the material presented during the course and at the some time not all the material written here will be presented during the School. This is however, not so bad: if some of the results presented on lectures will go beyond the notes, then there will be some reasons to listen the course and at the same time if some of the results will be explained in more details in notes, then it might be worth to look at them. The notes were prepared in hurry and so there are many bugs and they are not complete. Some of the sections and theorems are unfinished. At the end of the notes I enclosed some references together with comments. This section was also prepared in hurry and so probably many of the authors who contributed to the subject were not mentioned. -
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....... -
Using Functional Analysis and Sobolev Spaces to Solve Poisson’S Equation
USING FUNCTIONAL ANALYSIS AND SOBOLEV SPACES TO SOLVE POISSON'S EQUATION YI WANG Abstract. We study Banach and Hilbert spaces with an eye to- wards defining weak solutions to elliptic PDE. Using Lax-Milgram we prove that weak solutions to Poisson's equation exist under certain conditions. Contents 1. Introduction 1 2. Banach spaces 2 3. Weak topology, weak star topology and reflexivity 6 4. Lower semicontinuity 11 5. Hilbert spaces 13 6. Sobolev spaces 19 References 21 1. Introduction We will discuss the following problem in this paper: let Ω be an open and connected subset in R and f be an L2 function on Ω, is there a solution to Poisson's equation (1) −∆u = f? From elementary partial differential equations class, we know if Ω = R, we can solve Poisson's equation using the fundamental solution to Laplace's equation. However, if we just take Ω to be an open and connected set, the above method is no longer useful. In addition, for arbitrary Ω and f, a C2 solution does not always exist. Therefore, instead of finding a strong solution, i.e., a C2 function which satisfies (1), we integrate (1) against a test function φ (a test function is a Date: September 28, 2016. 1 2 YI WANG smooth function compactly supported in Ω), integrate by parts, and arrive at the equation Z Z 1 (2) rurφ = fφ, 8φ 2 Cc (Ω): Ω Ω So intuitively we want to find a function which satisfies (2) for all test functions and this is the place where Hilbert spaces come into play. -
Function Spaces Mikko Salo
Function spaces Lecture notes, Fall 2008 Mikko Salo Department of Mathematics and Statistics University of Helsinki Contents Chapter 1. Introduction 1 Chapter 2. Interpolation theory 5 2.1. Classical results 5 2.2. Abstract interpolation 13 2.3. Real interpolation 16 2.4. Interpolation of Lp spaces 20 Chapter 3. Fractional Sobolev spaces, Besov and Triebel spaces 27 3.1. Fourier analysis 28 3.2. Fractional Sobolev spaces 33 3.3. Littlewood-Paley theory 39 3.4. Besov and Triebel spaces 44 3.5. H¨olderand Zygmund spaces 54 3.6. Embedding theorems 60 Bibliography 63 v CHAPTER 1 Introduction In mathematical analysis one deals with functions which are dif- ferentiable (such as continuously differentiable) or integrable (such as square integrable or Lp). It is often natural to combine the smoothness and integrability requirements, which leads one to introduce various spaces of functions. This course will give a brief introduction to certain function spaces which are commonly encountered in analysis. This will include H¨older, Lipschitz, Zygmund, Sobolev, Besov, and Triebel-Lizorkin type spaces. We will try to highlight typical uses of these spaces, and will also give an account of interpolation theory which is an important tool in their study. The first part of the course covered integer order Sobolev spaces in domains in Rn, following Evans [4, Chapter 5]. These lecture notes contain the second part of the course. Here the emphasis is on Sobolev type spaces where the smoothness index may be any real number. This second part of the course is more or less self-contained, in that we will use the first part mainly as motivation. -
Fact Sheet Functional Analysis
Fact Sheet Functional Analysis Literature: Hackbusch, W.: Theorie und Numerik elliptischer Differentialgleichungen. Teubner, 1986. Knabner, P., Angermann, L.: Numerik partieller Differentialgleichungen. Springer, 2000. Triebel, H.: H¨ohere Analysis. Harri Deutsch, 1980. Dobrowolski, M.: Angewandte Funktionalanalysis, Springer, 2010. 1. Banach- and Hilbert spaces Let V be a real vector space. Normed space: A norm is a mapping k · k : V ! [0; 1), such that: kuk = 0 , u = 0; (definiteness) kαuk = jαj · kuk; α 2 R; u 2 V; (positive scalability) ku + vk ≤ kuk + kvk; u; v 2 V: (triangle inequality) The pairing (V; k · k) is called a normed space. Seminorm: In contrast to a norm there may be elements u 6= 0 such that kuk = 0. It still holds kuk = 0 if u = 0. Comparison of two norms: Two norms k · k1, k · k2 are called equivalent if there is a constant C such that: −1 C kuk1 ≤ kuk2 ≤ Ckuk1; u 2 V: If only one of these inequalities can be fulfilled, e.g. kuk2 ≤ Ckuk1; u 2 V; the norm k · k1 is called stronger than the norm k · k2. k · k2 is called weaker than k · k1. Topology: In every normed space a canonical topology can be defined. A subset U ⊂ V is called open if for every u 2 U there exists a " > 0 such that B"(u) = fv 2 V : ku − vk < "g ⊂ U: Convergence: A sequence vn converges to v w.r.t. the norm k · k if lim kvn − vk = 0: n!1 1 A sequence vn ⊂ V is called Cauchy sequence, if supfkvn − vmk : n; m ≥ kg ! 0 for k ! 1. -
Optimal Sobolev Embeddings and Function Spaces
Optimal Sobolev embeddings and Function Spaces Nadia Clavero Director: Javier Soria Tutor: Joan Cerd`a M´asteren Matem´aticaAvanzada y Profesional Especialidad Acad´emicaAvanzada Curso 2010/2011 U UNIVERSITAT DE BARCELONA B Contents 1 Introduction5 2 Preliminaries 11 2.1 The distribution function............................. 11 2.2 Decreasing rearrangements............................ 12 2.3 Rearrangement invariant Banach function spaces................ 16 2.4 Orlicz spaces................................... 18 2.5 Lorentz spaces................................... 22 2.6 Lorentz Zygmund spaces............................. 25 2.7 Interpolation spaces................................ 26 2.8 Weighted Hardy operators............................ 28 3 Sobolev spaces 35 3.1 Introduction.................................... 35 3.2 Definitions and basic properties......................... 35 3.3 Riesz potencials.................................. 38 3.4 Sobolev embedding theorem........................... 40 4 Orlicz spaces and Lorentz spaces 49 4.1 Introduction.................................... 49 4.2 Sobolev embeddings into Orlicz spaces..................... 50 4.3 Sobolev embeddings into Lorentz spaces.................... 52 4.4 Sobolev embeddings into Lorentz Zygmund spaces............... 56 5 Optimal Sobolev embeddings on rearrangement invariant spaces 59 5.1 Introduction.................................... 59 5.2 Reduction Theorem................................ 59 5.3 Optimal range and optimal domain of r.i. norms................ 70 5.4 Examples.................................... -
Spectral Radii of Bounded Operators on Topological Vector Spaces
SPECTRAL RADII OF BOUNDED OPERATORS ON TOPOLOGICAL VECTOR SPACES VLADIMIR G. TROITSKY Abstract. In this paper we develop a version of spectral theory for bounded linear operators on topological vector spaces. We show that the Gelfand formula for spectral radius and Neumann series can still be naturally interpreted for operators on topological vector spaces. Of course, the resulting theory has many similarities to the conventional spectral theory of bounded operators on Banach spaces, though there are several im- portant differences. The main difference is that an operator on a topological vector space has several spectra and several spectral radii, which fit a well-organized pattern. 0. Introduction The spectral radius of a bounded linear operator T on a Banach space is defined by the Gelfand formula r(T ) = lim n T n . It is well known that r(T ) equals the n k k actual radius of the spectrum σ(T ) p= sup λ : λ σ(T ) . Further, it is known −1 {| | ∈ } ∞ T i that the resolvent R =(λI T ) is given by the Neumann series +1 whenever λ − i=0 λi λ > r(T ). It is natural to ask if similar results are valid in a moreP general setting, | | e.g., for a bounded linear operator on an arbitrary topological vector space. The author arrived to these questions when generalizing some results on Invariant Subspace Problem from Banach lattices to ordered topological vector spaces. One major difficulty is that it is not clear which class of operators should be considered, because there are several non-equivalent ways of defining bounded operators on topological vector spaces. -
Sobolev-Type Spaces (Mainly Based on the Lp Norm) on Metric Spaces, and Newto- Nian Spaces in Particular, Have Been Under Intensive Study Since the Mid-"##$S
- ) . / 0 &/ . ! " # $" ! %&' '( ! ) *+, !"## $ "% ' ( &)*+) ,##(-./*01*2/ ,#3(+140+)01*)+0.*/0- %"52-)/ 6 7 %80$%6!"6#62-)/ i Abstract !is thesis consists of four papers and focuses on function spaces related to !rst- order analysis in abstract metric measure spaces. !e classical (i.e., Sobolev) theory in Euclidean spaces makes use of summability of distributional gradients, whose de!nition depends on the linear structure of Rn. In metric spaces, we can replace the distributional gradients by (weak) upper gradients that control the functions’ behav- ior along (almost) all recti!able curves, which gives rise to the so-called Newtonian spaces. !e summability condition, considered in the thesis, is expressed using a general Banach function lattice quasi-norm and so an extensive framework is built. Sobolev-type spaces (mainly based on the Lp norm) on metric spaces, and Newto- nian spaces in particular, have been under intensive study since the mid-"##$s. In Paper I, the elementary theory of Newtonian spaces based on quasi-Banach function lattices is built up. Standard tools such as moduli of curve families and the Sobolev capacity are developed and applied to study the basic properties of Newto- nian functions. Summability of a (weak) upper gradient of a function is shown to guarantee the function’s absolute continuity on almost all curves. Moreover, New- tonian spaces are proven complete in this general setting. Paper II investigates the set of all weak upper gradients of a Newtonian function. In particular, existence of minimal weak upper gradients is established. Validity of Lebesgue’s di%erentiation theorem for the underlying metric measure space ensures that a family of representation formulae for minimal weak upper gradients can be found. -
Note on the Solvability of Equations Involving Unbounded Linear and Quasibounded Nonlinear Operators*
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector JOURNAL OF MATHEMATICAL ANALYSIS AND APPLICATIONS 56, 495-501 (1976) Note on the Solvability of Equations Involving Unbounded Linear and Quasibounded Nonlinear Operators* W. V. PETRYSHYN Deportment of Mathematics, Rutgers University, New Brunswick, New Jersey 08903 Submitted by Ky Fan INTRODUCTION Let X and Y be Banach spaces, X* and Y* their respective duals and (u, x) the value of u in X* at x in X. For a bounded linear operator T: X---f Y (i.e., for T EL(X, Y)) let N(T) C X and R(T) C Y denote the null space and the range of T respectively and let T *: Y* --f X* denote the adjoint of T. Foranyset vinXandWinX*weset I”-={uEX*~(U,X) =OV~EV) and WL = {x E X 1(u, x) = OVu E W). In [6] Kachurovskii obtained (without proof) a partial generalization of the closed range theorem of Banach for mildly nonlinear equations which can be stated as follows: THEOREM K. Let T EL(X, Y) have a closed range R(T) and a Jinite dimensional null space N(T). Let S: X --f Y be a nonlinear compact mapping such that R(S) C N( T*)l and S is asymptotically zer0.l Then the equation TX + S(x) = y is solvable for a given y in Y if and only if y E N( T*)l. The purpose of this note is to extend Theorem K to equations of the form TX + S(x) = y (x E WY, y E Y), (1) where T: D(T) X--f Y is a closed linear operator with domain D(T) not necessarily dense in X and such that R(T) is closed and N(T) (CD(T)) has a closed complementary subspace in X and S: X-t Y is a nonlinear quasi- bounded mapping but not necessarily compact or asymptotically zero. -
Lp Spaces in Isabelle
Lp spaces in Isabelle Sebastien Gouezel Abstract Lp is the space of functions whose p-th power is integrable. It is one of the most fundamental Banach spaces that is used in analysis and probability. We develop a framework for function spaces, and then im- plement the Lp spaces in this framework using the existing integration theory in Isabelle/HOL. Our development contains most fundamental properties of Lp spaces, notably the Hölder and Minkowski inequalities, completeness of Lp, duality, stability under almost sure convergence, multiplication of functions in Lp and Lq, stability under conditional expectation. Contents 1 Functions as a real vector space 2 2 Quasinorms on function spaces 4 2.1 Definition of quasinorms ..................... 5 2.2 The space and the zero space of a quasinorm ......... 7 2.3 An example: the ambient norm in a normed vector space .. 9 2.4 An example: the space of bounded continuous functions from a topological space to a normed real vector space ....... 10 2.5 Continuous inclusions between functional spaces ....... 10 2.6 The intersection and the sum of two functional spaces .... 12 2.7 Topology ............................. 14 3 Conjugate exponents 16 4 Convexity inequalities and integration 18 5 Lp spaces 19 5.1 L1 ................................. 20 5.2 Lp for 0 < p < 1 ......................... 21 5.3 Specialization to L1 ....................... 22 5.4 L0 ................................. 23 5.5 Basic results on Lp for general p ................ 24 5.6 Lp versions of the main theorems in integration theory .... 25 1 5.7 Completeness of Lp ........................ 26 5.8 Multiplication of functions, duality ............... 26 5.9 Conditional expectations and Lp ............... -
Topological Invariants for Discontinuous Mappings Differential Topology in Sobolev Spaces
Topological invariants for discontinuous mappings Differential topology in Sobolev spaces Paweł Goldstein [email protected] Kolokwium MIM, 7 listopada 2019 TOPOLOGICAL INVARIANTS FOR DISCONTINUOUS MAPPINGS 1/21 Two reasons: • natural: folding, breaking, changes of state; • technical: necessary because of the available mathematical tools. Introduction Why do we need • non-differentiable • discontinuous mappings in real-life applications? TOPOLOGICAL INVARIANTS FOR DISCONTINUOUS MAPPINGS 2/21 Introduction Why do we need • non-differentiable • discontinuous mappings in real-life applications? Two reasons: • natural: folding, breaking, changes of state; • technical: necessary because of the available mathematical tools. TOPOLOGICAL INVARIANTS FOR DISCONTINUOUS MAPPINGS 2/21 Minima of accumulative, i.e, integral quantities ) we measure distance to minimizer with integral expressions. Introduction Variational principles • Fermat’s principle (Hero of Alexandria, Pierre de Fermat): Light travels through media along paths of shortest time. • Extremal action principle (Euler, Maupertuis): Bodies travel along paths locally minimizing the reduced action (integral of the momentum). Other examples: Dirichlet’s principle for harmonic maps, Einstein-Hilbert action in general relativity etc. TOPOLOGICAL INVARIANTS FOR DISCONTINUOUS MAPPINGS 3/21 Introduction Variational principles • Fermat’s principle (Hero of Alexandria, Pierre de Fermat): Light travels through media along paths of shortest time. • Extremal action principle (Euler, Maupertuis): -
Characterizations of Screened Sobolev Spaces Noah Stevenson and Ian Tice DEPARTMENTOF MATHEMATICAL SCIENCES,CARNEGIE MELLON UNIVERSITY
Characterizations of Screened Sobolev Spaces Noah Stevenson and Ian Tice DEPARTMENT OF MATHEMATICAL SCIENCES,CARNEGIE MELLON UNIVERSITY An approach which is promising in the resolution of this issue is to swap the inhomogeneous Sobolev spaces for their homogeneous counterparts, Does the topology on the screened Sobolev spaces Background W_ k;p (Ω). The upshot is that the latter families allow for a larger variety of Research admit a Fourier space characterization? behaviors at infinity. For this approach to have any chance of being fruitful in the Leoni and Tice gave the following partial frequency & Motivation study of boundary value problems, it is essential to identify and understand the Questions n characterization of these spaces: for f 2 S R it holds Partial differential equations (PDEs) are trace spaces associated to the homogeneous Sobolev spaces. Recall that the trace Z 1 2s 2 ^ 2 2 central to the modeling of natural space associated to a Sobolev space on a domain is a space of functions holding Can the screened Sobolev spaces be [f]W~ s;2 minfjξj ; jξj g f (ξ) dξ ; (2) (σ) n understood through interpolation theory? R phenomena. As a result, the study of these the possible boundary values and, for higher order Sobolev spaces, powers of the where 0 < s < 1 and constant screening function σ = 1. equations and their solutions has held a normal derivative. Interpolation theory is a set of tools which This expression suggests that the high-mode part of a prominent place in mathematics for For functions of finite energy in planar strips these trace spaces were first s;2 take certain pairs of topological vector member of W~ behaves like a member of the centuries.