Synthetic Differential Geometry
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
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. -
1.2 Topological Tensor Calculus
PH211 Physical Mathematics Fall 2019 1.2 Topological tensor calculus 1.2.1 Tensor fields Finite displacements in Euclidean space can be represented by arrows and have a natural vector space structure, but finite displacements in more general curved spaces, such as on the surface of a sphere, do not. However, an infinitesimal neighborhood of a point in a smooth curved space1 looks like an infinitesimal neighborhood of Euclidean space, and infinitesimal displacements dx~ retain the vector space structure of displacements in Euclidean space. An infinitesimal neighborhood of a point can be infinitely rescaled to generate a finite vector space, called the tangent space, at the point. A vector lives in the tangent space of a point. Note that vectors do not stretch from one point to vector tangent space at p p space Figure 1.2.1: A vector in the tangent space of a point. another, and vectors at different points live in different tangent spaces and so cannot be added. For example, rescaling the infinitesimal displacement dx~ by dividing it by the in- finitesimal scalar dt gives the velocity dx~ ~v = (1.2.1) dt which is a vector. Similarly, we can picture the covector rφ as the infinitesimal contours of φ in a neighborhood of a point, infinitely rescaled to generate a finite covector in the point's cotangent space. More generally, infinitely rescaling the neighborhood of a point generates the tensor space and its algebra at the point. The tensor space contains the tangent and cotangent spaces as a vector subspaces. A tensor field is something that takes tensor values at every point in a space. -
Differential Forms Diff Geom II, WS 2015/16
J.M. Sullivan, TU Berlin B: Differential Forms Diff Geom II, WS 2015/16 B. DIFFERENTIAL FORMS instance, if S has k elements this gives a k-dimensional vector space with S as basis. We have already seen one-forms (covector fields) on a Given vector spaces V and W, let F be the free vector space over the set V × W. (This consists of formal sums manifold. In general, a k-form is a field of alternating k- P linear forms on the tangent spaces of a manifold. Forms ai(vi, wi) but ignores all the structure we have on the set are the natural objects for integration: a k-form can be in- V × W.) Now let R ⊂ F be the linear subspace spanned by tegrated over an oriented k-submanifold. We start with ten- all elements of the form: sor products and the exterior algebra of multivectors. (v + v0, w) − (v, w) − (v0, w), (v, w + w0) − (v, w) − (v, w0), (av, w) − a(v, w), (v, aw) − a(v, w). B1. Tensor products These correspond of course to the bilinearity conditions Recall that, if V, W and X are vector spaces, then a map we started with. The quotient vector space F/R will be the b: V × W → X is called bilinear if tensor product V ⊗ W. We have started with all possible v ⊗ w as generators and thrown in just enough relations to b(v + v0, w) = b(v, w) + b(v0, w), make the map (v, w) 7→ v ⊗ w be bilinear. b(v, w + w0) = b(v, w) + b(v, w0), The tensor product is commutative: there is a natural linear isomorphism V⊗W → W⊗V such that v⊗w 7→ w⊗v. -
Vector Calculus and Differential Forms with Applications To
Vector Calculus and Differential Forms with Applications to Electromagnetism Sean Roberson May 7, 2015 PREFACE This paper is written as a final project for a course in vector analysis, taught at Texas A&M University - San Antonio in the spring of 2015 as an independent study course. Students in mathematics, physics, engineering, and the sciences usually go through a sequence of three calculus courses before go- ing on to differential equations, real analysis, and linear algebra. In the third course, traditionally reserved for multivariable calculus, stu- dents usually learn how to differentiate functions of several variable and integrate over general domains in space. Very rarely, as was my case, will professors have time to cover the important integral theo- rems using vector functions: Green’s Theorem, Stokes’ Theorem, etc. In some universities, such as UCSD and Cornell, honors students are able to take an accelerated calculus sequence using the text Vector Cal- culus, Linear Algebra, and Differential Forms by John Hamal Hubbard and Barbara Burke Hubbard. Here, students learn multivariable cal- culus using linear algebra and real analysis, and then they generalize familiar integral theorems using the language of differential forms. This paper was written over the course of one semester, where the majority of the book was covered. Some details, such as orientation of manifolds, topology, and the foundation of the integral were skipped to save length. The paper should still be readable by a student with at least three semesters of calculus, one course in linear algebra, and one course in real analysis - all at the undergraduate level. -
6.10 the Generalized Stokes's Theorem
6.10 The generalized Stokes’s theorem 645 6.9.2 In the text we proved Proposition 6.9.7 in the special case where the mapping f is linear. Prove the general statement, where f is only assumed to be of class C1. n m 1 6.9.3 Let U R be open, f : U R of class C , and ξ a vector field on m ⊂ → R . a. Show that (f ∗Wξ)(x)=W . Exercise 6.9.3: The matrix [Df(x)]!ξ(x) adj(A) of part c is the adjoint ma- b. Let m = n. Show that if [Df(x)] is invertible, then trix of A. The equation in part b (f ∗Φ )(x) = det[Df(x)]Φ 1 . is unsatisfactory: it does not say ξ [Df(x)]− ξ(x) how to represent (f ∗Φ )(x) as the ξ c. Let m = n, let A be a square matrix, and let A be the matrix obtained flux of a vector field when the n n [j,i] × from A by erasing the jth row and the ith column. Let adj(A) be the matrix matrix [Df(x)] is not invertible. i+j whose (i, j)th entry is (adj(A))i,j =( 1) det A . Show that Part c deals with this situation. − [j,i] A(adj(A)) = (det A)I and f ∗Φξ(x)=Φadj([Df(x)])ξ(x) 6.10 The generalized Stokes’s theorem We worked hard to define the exterior derivative and to define orientation of manifolds and of boundaries. Now we are going to reap some rewards for our labor: a higher-dimensional analogue of the fundamental theorem of calculus, Stokes’s theorem. -
Jet Fitting 3: a Generic C++ Package for Estimating the Differential Properties on Sampled Surfaces Via Polynomial Fitting Frédéric Cazals, Marc Pouget
Jet fitting 3: A Generic C++ Package for Estimating the Differential Properties on Sampled Surfaces via Polynomial Fitting Frédéric Cazals, Marc Pouget To cite this version: Frédéric Cazals, Marc Pouget. Jet fitting 3: A Generic C++ Package for Estimating the Differential Properties on Sampled Surfaces via Polynomial Fitting. ACM Transactions on Mathematical Software, Association for Computing Machinery, 2008, 35 (3). inria-00329731 HAL Id: inria-00329731 https://hal.inria.fr/inria-00329731 Submitted on 2 Mar 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Jet fitting 3: A Generic C++ Package for Estimating the Differential Properties on Sampled Surfaces via Polynomial Fitting FRED´ ERIC´ CAZALS INRIA Sophia-Antipolis, France. and MARC POUGET INRIA Nancy Gand Est - LORIA, France. 3 Surfaces of R are ubiquitous in science and engineering, and estimating the local differential properties of a surface discretized as a point cloud or a triangle mesh is a central building block in Computer Graphics, Computer Aided Design, Computational Geometry, Computer Vision. One strategy to perform such an estimation consists of resorting to polynomial fitting, either interpo- lation or approximation, but this route is difficult for several reasons: choice of the coordinate system, numerical handling of the fitting problem, extraction of the differential properties. -