Global Divergence Theorems in Nonlinear Pdes and Geometry
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Arxiv:1507.07356V2 [Math.AP]
TEN EQUIVALENT DEFINITIONS OF THE FRACTIONAL LAPLACE OPERATOR MATEUSZ KWAŚNICKI Abstract. This article discusses several definitions of the fractional Laplace operator ( ∆)α/2 (α (0, 2)) in Rd (d 1), also known as the Riesz fractional derivative − ∈ ≥ operator, as an operator on Lebesgue spaces L p (p [1, )), on the space C0 of ∈ ∞ continuous functions vanishing at infinity and on the space Cbu of bounded uniformly continuous functions. Among these definitions are ones involving singular integrals, semigroups of operators, Bochner’s subordination and harmonic extensions. We collect and extend known results in order to prove that all these definitions agree: on each of the function spaces considered, the corresponding operators have common domain and they coincide on that common domain. 1. Introduction We consider the fractional Laplace operator L = ( ∆)α/2 in Rd, with α (0, 2) and d 1, 2, ... Numerous definitions of L can be found− in− literature: as a Fourier∈ multiplier with∈{ symbol} ξ α, as a fractional power in the sense of Bochner or Balakrishnan, as the inverse of the−| Riesz| potential operator, as a singular integral operator, as an operator associated to an appropriate Dirichlet form, as an infinitesimal generator of an appropriate semigroup of contractions, or as the Dirichlet-to-Neumann operator for an appropriate harmonic extension problem. Equivalence of these definitions for sufficiently smooth functions is well-known and easy. The purpose of this article is to prove that, whenever meaningful, all these definitions are equivalent in the Lebesgue space L p for p [1, ), ∈ ∞ in the space C0 of continuous functions vanishing at infinity, and in the space Cbu of bounded uniformly continuous functions. -
Laplacians in Geometric Analysis
LAPLACIANS IN GEOMETRIC ANALYSIS Syafiq Johar syafi[email protected] Contents 1 Trace Laplacian 1 1.1 Connections on Vector Bundles . .1 1.2 Local and Explicit Expressions . .2 1.3 Second Covariant Derivative . .3 1.4 Curvatures on Vector Bundles . .4 1.5 Trace Laplacian . .5 2 Harmonic Functions 6 2.1 Gradient and Divergence Operators . .7 2.2 Laplace-Beltrami Operator . .7 2.3 Harmonic Functions . .8 2.4 Harmonic Maps . .8 3 Hodge Laplacian 9 3.1 Exterior Derivatives . .9 3.2 Hodge Duals . 10 3.3 Hodge Laplacian . 12 4 Hodge Decomposition 13 4.1 De Rham Cohomology . 13 4.2 Hodge Decomposition Theorem . 14 5 Weitzenb¨ock and B¨ochner Formulas 15 5.1 Weitzenb¨ock Formula . 15 5.1.1 0-forms . 15 5.1.2 k-forms . 15 5.2 B¨ochner Formula . 17 1 Trace Laplacian In this section, we are going to present a notion of Laplacian that is regularly used in differential geometry, namely the trace Laplacian (also called the rough Laplacian or connection Laplacian). We recall the definition of connection on vector bundles which allows us to take the directional derivative of vector bundles. 1.1 Connections on Vector Bundles Definition 1.1 (Connection). Let M be a differentiable manifold and E a vector bundle over M. A connection or covariant derivative at a point p 2 M is a map D : Γ(E) ! Γ(T ∗M ⊗ E) 1 with the properties for any V; W 2 TpM; σ; τ 2 Γ(E) and f 2 C (M), we have that DV σ 2 Ep with the following properties: 1. -
A Brief Tour of Vector Calculus
A BRIEF TOUR OF VECTOR CALCULUS A. HAVENS Contents 0 Prelude ii 1 Directional Derivatives, the Gradient and the Del Operator 1 1.1 Conceptual Review: Directional Derivatives and the Gradient........... 1 1.2 The Gradient as a Vector Field............................ 5 1.3 The Gradient Flow and Critical Points ....................... 10 1.4 The Del Operator and the Gradient in Other Coordinates*............ 17 1.5 Problems........................................ 21 2 Vector Fields in Low Dimensions 26 2 3 2.1 General Vector Fields in Domains of R and R . 26 2.2 Flows and Integral Curves .............................. 31 2.3 Conservative Vector Fields and Potentials...................... 32 2.4 Vector Fields from Frames*.............................. 37 2.5 Divergence, Curl, Jacobians, and the Laplacian................... 41 2.6 Parametrized Surfaces and Coordinate Vector Fields*............... 48 2.7 Tangent Vectors, Normal Vectors, and Orientations*................ 52 2.8 Problems........................................ 58 3 Line Integrals 66 3.1 Defining Scalar Line Integrals............................. 66 3.2 Line Integrals in Vector Fields ............................ 75 3.3 Work in a Force Field................................. 78 3.4 The Fundamental Theorem of Line Integrals .................... 79 3.5 Motion in Conservative Force Fields Conserves Energy .............. 81 3.6 Path Independence and Corollaries of the Fundamental Theorem......... 82 3.7 Green's Theorem.................................... 84 3.8 Problems........................................ 89 4 Surface Integrals, Flux, and Fundamental Theorems 93 4.1 Surface Integrals of Scalar Fields........................... 93 4.2 Flux........................................... 96 4.3 The Gradient, Divergence, and Curl Operators Via Limits* . 103 4.4 The Stokes-Kelvin Theorem..............................108 4.5 The Divergence Theorem ...............................112 4.6 Problems........................................114 List of Figures 117 i 11/14/19 Multivariate Calculus: Vector Calculus Havens 0. -
Curl, Divergence and Laplacian
Curl, Divergence and Laplacian What to know: 1. The definition of curl and it two properties, that is, theorem 1, and be able to predict qualitatively how the curl of a vector field behaves from a picture. 2. The definition of divergence and it two properties, that is, if div F~ 6= 0 then F~ can't be written as the curl of another field, and be able to tell a vector field of clearly nonzero,positive or negative divergence from the picture. 3. Know the definition of the Laplace operator 4. Know what kind of objects those operator take as input and what they give as output. The curl operator Let's look at two plots of vector fields: Figure 1: The vector field Figure 2: The vector field h−y; x; 0i: h1; 1; 0i We can observe that the second one looks like it is rotating around the z axis. We'd like to be able to predict this kind of behavior without having to look at a picture. We also promised to find a criterion that checks whether a vector field is conservative in R3. Both of those goals are accomplished using a tool called the curl operator, even though neither of those two properties is exactly obvious from the definition we'll give. Definition 1. Let F~ = hP; Q; Ri be a vector field in R3, where P , Q and R are continuously differentiable. We define the curl operator: @R @Q @P @R @Q @P curl F~ = − ~i + − ~j + − ~k: (1) @y @z @z @x @x @y Remarks: 1. -
Part IA — Vector Calculus
Part IA | Vector Calculus Based on lectures by B. Allanach Notes taken by Dexter Chua Lent 2015 These notes are not endorsed by the lecturers, and I have modified them (often significantly) after lectures. They are nowhere near accurate representations of what was actually lectured, and in particular, all errors are almost surely mine. 3 Curves in R 3 Parameterised curves and arc length, tangents and normals to curves in R , the radius of curvature. [1] 2 3 Integration in R and R Line integrals. Surface and volume integrals: definitions, examples using Cartesian, cylindrical and spherical coordinates; change of variables. [4] Vector operators Directional derivatives. The gradient of a real-valued function: definition; interpretation as normal to level surfaces; examples including the use of cylindrical, spherical *and general orthogonal curvilinear* coordinates. Divergence, curl and r2 in Cartesian coordinates, examples; formulae for these oper- ators (statement only) in cylindrical, spherical *and general orthogonal curvilinear* coordinates. Solenoidal fields, irrotational fields and conservative fields; scalar potentials. Vector derivative identities. [5] Integration theorems Divergence theorem, Green's theorem, Stokes's theorem, Green's second theorem: statements; informal proofs; examples; application to fluid dynamics, and to electro- magnetism including statement of Maxwell's equations. [5] Laplace's equation 2 3 Laplace's equation in R and R : uniqueness theorem and maximum principle. Solution of Poisson's equation by Gauss's method (for spherical and cylindrical symmetry) and as an integral. [4] 3 Cartesian tensors in R Tensor transformation laws, addition, multiplication, contraction, with emphasis on tensors of second rank. Isotropic second and third rank tensors. -
On a Class of Einstein Space-Time Manifolds
Publ. Math. Debrecen 67/3-4 (2005), 471–480 On a class of Einstein space-time manifolds By ADELA MIHAI (Bucharest) and RADU ROSCA (Paris) Abstract. We deal with a general space-time (M,g) with usual differen- tiability conditions and hyperbolic metric g of index 1, which carries 3 skew- symmetric Killing vector fields X, Y , Z having as generative the unit time-like vector field e of the hyperbolic metric g. It is shown that such a space-time (M,g) is an Einstein manifold of curvature −1, which is foliated by space-like hypersur- faces Ms normal to e and the immersion x : Ms → M is pseudo-umbilical. In addition, it is proved that the vector fields X, Y , Z and e are exterior concur- rent vector fields and X, Y , Z define a commutative Killing triple, M admits a Lorentzian transformation which is in an orthocronous Lorentz group and the distinguished spatial 3-form of M is a relatively integral invariant of the vector fields X, Y and Z. 0. Introduction Let (M,g) be a general space-time with usual differentiability condi- tions and hyperbolic metric g of index 1. We assume in this paper that (M,g) carries 3 skew-symmetric Killing vector fields (abbr. SSK) X, Y , Z having as generative the unit time-like vector field e of the hyperbolic metric g (see[R1],[MRV].Therefore,if∇ is the Levi–Civita connection and ∧ means the wedge product of vector Mathematics Subject Classification: 53C15, 53D15, 53C25. Key words and phrases: space-time, skew-symmetric Killing vector field, exterior con- current vector field, orthocronous Lorentz group. -
Generalized Stokes' Theorem
Chapter 4 Generalized Stokes’ Theorem “It is very difficult for us, placed as we have been from earliest childhood in a condition of training, to say what would have been our feelings had such training never taken place.” Sir George Stokes, 1st Baronet 4.1. Manifolds with Boundary We have seen in the Chapter 3 that Green’s, Stokes’ and Divergence Theorem in Multivariable Calculus can be unified together using the language of differential forms. In this chapter, we will generalize Stokes’ Theorem to higher dimensional and abstract manifolds. These classic theorems and their generalizations concern about an integral over a manifold with an integral over its boundary. In this section, we will first rigorously define the notion of a boundary for abstract manifolds. Heuristically, an interior point of a manifold locally looks like a ball in Euclidean space, whereas a boundary point locally looks like an upper-half space. n 4.1.1. Smooth Functions on Upper-Half Spaces. From now on, we denote R+ := n n f(u1, ... , un) 2 R : un ≥ 0g which is the upper-half space of R . Under the subspace n n n topology, we say a subset V ⊂ R+ is open in R+ if there exists a set Ve ⊂ R open in n n n R such that V = Ve \ R+. It is intuitively clear that if V ⊂ R+ is disjoint from the n n n subspace fun = 0g of R , then V is open in R+ if and only if V is open in R . n n Now consider a set V ⊂ R+ which is open in R+ and that V \ fun = 0g 6= Æ. -
4.1 Discrete Differential Geometry
Spring 2015 CSCI 599: Digital Geometry Processing 4.1 Discrete Differential Geometry Hao Li http://cs599.hao-li.com 1 Outline • Discrete Differential Operators • Discrete Curvatures • Mesh Quality Measures 2 Differential Operators on Polygons Differential Properties! • Surface is sufficiently differentiable • Curvatures → 2nd derivatives 3 Differential Operators on Polygons Differential Properties! • Surface is sufficiently differentiable • Curvatures → 2nd derivatives Polygonal Meshes! • Piecewise linear approximations of smooth surface • Focus on Discrete Laplace Beltrami Operator • Discrete differential properties defined over (x) N 4 Local Averaging Local Neighborhood ( x ) of a point !x N • often coincides with mesh vertex vi • n-ring neighborhood ( v ) or local geodesic ball Nn i 5 Local Averaging Local Neighborhood ( x ) of a point !x N • often coincides with mesh vertex vi • n-ring neighborhood ( v ) or local geodesic ball Nn i Neighborhood size! • Large: smoothing is introduced, stable to noise • Small: fine scale variation, sensitive to noise 6 Local Averaging: 1-Ring (x) N x Barycentric cell Voronoi cell Mixed Voronoi cell (barycenters/edgemidpoints) (circumcenters) (circumcenters/midpoint) tight error bound better approximation 7 Barycentric Cells Connect edge midpoints and triangle barycenters! • Simple to compute • Area is 1/3 o triangle areas • Slightly wrong for obtuse triangles 8 Mixed Cells Connect edge midpoints and! • Circumcenters for non-obtuse triangles • Midpoint of opposite edge for obtuse triangles • Better approximation, -
LECTURE 27: the LAPLAST ONE Monday, November 25, 2019 5:23 PM
LECTURE 27: THE LAPLAST ONE Monday, November 25, 2019 5:23 PM Today: Three little remaining topics related to Laplace I- 3 DIMENSIONS Previously: Solved Laplace's equation in 2 dimensions by converting it into polar coordinates. The same idea works in 3 dimensions if you use spherical coordinates. 3 Suppose u = u(x,y,z) solves u xx + u yy + u zz = 0 in R Using spherical coordinates, you eventually get urr + 2 ur + JUNK = 0 r (where r = x 2 + y 2 + z 2 and JUNK doesn't depend on r) If we're looking for radial solutions, we set JUNK = 0 Get u rr + 2 u r = 0 which you can solve to get r u(x,y,z) = -C + C' solves u xx + u yy + u zz = 0 r Finally, setting C = -1/(4π) and C' = 0, you get Fundamental solution of Laplace for n = 3 S(x,y,z) = 1 = 4πr 4π x 2 + y 2 + z 2 Note: In n dimensions, get u rr + n-1 ur = 0 r => u( r ) = -C + C' rn-2 => S(x) = Blah (for some complicated Blah) rn-1 Why fundamental? Because can build up other solutions from this! Fun Fact: A solution of -Δ u = f (Poisson's equation) in R n is u(x) = S(x) * f(x) = S(x -y) f(y) dy (Basically the constant is chosen such that -ΔS = d0 <- Dirac at 0) II - DERIVATION OF LAPLACE Two goals: Derive Laplace's equation, and also highlight an important structure of Δu = 0 A) SETTING n Definition: If F = (F 1, …, F n) is a vector field in R , then div(F) = (F 1)x1 + … + (F n)xn Notice : If u = u(x 1, …, x n), then u = (u x1 , …, u xn ) => div( u) = (u x1 )x1 + … + (u xn )xn = u x1 x1 + … + u xn xn = Δu Fact: Δu = div( u) "divergence structure" In particular, Laplace's equation works very well with the divergence theorem Divergence Theorem: F n dS = div(F) dx bdy D D B) DERIVATION Suppose you have a fluid F that is in equilibrium (think F = temperature or chemical concentration) Equilibrium means that for any region D, the net flux of F is 0. -
Green Gauss Theorem Yesterday, We Continued Discussions on Index Notations That Can Be Used to Represent Tensors
15/02/2017 LECTURE – 15 Green Gauss Theorem Yesterday, we continued discussions on index notations that can be used to represent tensors. In index notations we saw the Gradient of a scalar Divergence of a vector Cross product of vector etc. We also saw that a second rank tensor can be written as a sum of a symmetric & asymmetric tensor. 11 i.e, BBBBB[][] ij22 ij ji ij ji First part is symmetric & second part is asymmetric Today we will briefly discuss about Green Gauss Theorem etc. Green Gauss Theorem relates the volume & surface integrals. The most common form of Gauss’s theorem is the Gauss divergence theorem which you have studied in previous courses. 푛 푣 ds If you have a volume U formed by surface S, the Gauss divergence theorem for a vector v suggest that v.. ndSˆ vdU SU where, S = bounding surface on closed surface U = volumetric domain nˆ = the unit outward normal vector of the elementary surface area ds This Gauss Divergence theorem can also be represented using index notations. v v n dS i dU ii SUxi For any scalar multiple or factor for vector v , say v , the Green Gauss can be represented as (v . nˆ ) dS .( v ) dU SU i.e. (v . nˆ ) dS ( . v ) dU ( v . ) dU SUU v or v n dSi dU v dU i i i SUUxxii Gauss’s theorem is applicable not only to a vector . It can be applied to any tensor B (say) B B n dSij dU B dU ij i ij SUUxxii Stoke’s Theorem Stoke’s theorem relates the integral over an open surface S, to line integral around the surface’s bounding curve (say C) You need to appropriately choose the unit outward normal vector to the surface 푛 푡 dr v. -
A Doubly Nonlocal Laplace Operator and Its Connection to the Classical Laplacian Petronela Radu University of Nebraska - Lincoln, [email protected]
University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Faculty Publications, Department of Mathematics Mathematics, Department of 2019 A Doubly Nonlocal Laplace Operator and Its Connection to the Classical Laplacian Petronela Radu University of Nebraska - Lincoln, [email protected] Kelseys Wells University of Nebraska - Lincoln Follow this and additional works at: https://digitalcommons.unl.edu/mathfacpub Part of the Applied Mathematics Commons, and the Mathematics Commons Radu, Petronela and Wells, Kelseys, "A Doubly Nonlocal Laplace Operator and Its Connection to the Classical Laplacian" (2019). Faculty Publications, Department of Mathematics. 215. https://digitalcommons.unl.edu/mathfacpub/215 This Article is brought to you for free and open access by the Mathematics, Department of at DigitalCommons@University of Nebraska - Lincoln. It has been accepted for inclusion in Faculty Publications, Department of Mathematics by an authorized administrator of DigitalCommons@University of Nebraska - Lincoln. A DOUBLY NONLOCAL LAPLACE OPERATOR AND ITS CONNECTION TO THE CLASSICAL LAPLACIAN PETRONELA RADU, KELSEY WELLS Abstract. In this paper, motivated by the state-based peridynamic frame- work, we introduce a new nonlocal Laplacian that exhibits double nonlocality through the use of iterated integral operators. The operator introduces addi- tional degrees of flexibility that can allow for better representation of physical phenomena at different scales and in materials with different properties. We study mathematical properties of this state-based Laplacian, including connec- tions with other nonlocal and local counterparts. Finally, we obtain explicit rates of convergence for this doubly nonlocal operator to the classical Laplacian as the radii for the horizons of interaction kernels shrink to zero. 1. Introduction Physical phenomena that are beset by discontinuities in the solution, or in the domain, have been challenging to study in the context of classical partial differen- tial equations (PDEs). -
Vector Calculus Applicationsž 1. Introduction 2. the Heat Equation
Vector Calculus Applications 1. Introduction The divergence and Stokes’ theorems (and their related results) supply fundamental tools which can be used to derive equations which can be used to model a number of physical situations. Essentially, these theorems provide a mathematical language with which to express physical laws such as conservation of mass, momentum and energy. The resulting equations are some of the most fundamental and useful in engineering and applied science. In the following sections the derivation of some of these equations will be outlined. The goal is to show how vector calculus is used in applications. Generally speaking, the equations are derived by first using a conservation law in integral form, and then converting the integral form to a differential equation form using the divergence theorem, Stokes’ theorem, and vector identities. The differential equation forms tend to be easier to work with, particularly if one is interested in solving such equations, either analytically or numerically. 2. The Heat Equation Consider a solid material occupying a region of space V . The region has a boundary surface, which we shall designate as S. Suppose the solid has a density and a heat capacity c. If the temperature of the solid at any point in V is T.r; t/, where r x{ y| zkO is the position vector (so that T depends upon x, y, z and t), then theE total heatE eergyD O containedC O C in the solid is • cT dV : V Heat energy can get in or out of the region V by flowing across the boundary S, or it can be generated inside V .