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Geometric Manifolds
Wintersemester 2015/2016 University of Heidelberg Geometric Structures on Manifolds Geometric Manifolds by Stephan Schmitt Contents Introduction, first Definitions and Results 1 Manifolds - The Group way .................................... 1 Geometric Structures ........................................ 2 The Developing Map and Completeness 4 An introductory discussion of the torus ............................. 4 Definition of the Developing map ................................. 6 Developing map and Manifolds, Completeness 10 Developing Manifolds ....................................... 10 some completeness results ..................................... 10 Some selected results 11 Discrete Groups .......................................... 11 Stephan Schmitt INTRODUCTION, FIRST DEFINITIONS AND RESULTS Introduction, first Definitions and Results Manifolds - The Group way The keystone of working mathematically in Differential Geometry, is the basic notion of a Manifold, when we usually talk about Manifolds we mean a Topological Space that, at least locally, looks just like Euclidean Space. The usual formalization of that Concept is well known, we take charts to ’map out’ the Manifold, in this paper, for sake of Convenience we will take a slightly different approach to formalize the Concept of ’locally euclidean’, to formulate it, we need some tools, let us introduce them now: Definition 1.1. Pseudogroups A pseudogroup on a topological space X is a set G of homeomorphisms between open sets of X satisfying the following conditions: • The Domains of the elements g 2 G cover X • The restriction of an element g 2 G to any open set contained in its Domain is also in G. • The Composition g1 ◦ g2 of two elements of G, when defined, is in G • The inverse of an Element of G is in G. • The property of being in G is local, that is, if g : U ! V is a homeomorphism between open sets of X and U is covered by open sets Uα such that each restriction gjUα is in G, then g 2 G Definition 1.2. -
Affine Connections and Second-Order Affine Structures
Affine connections and second-order affine structures Filip Bár Dedicated to my good friend Tom Rewwer on the occasion of his 35th birthday. Abstract Smooth manifolds have been always understood intuitively as spaces with an affine geometry on the infinitesimal scale. In Synthetic Differential Geometry this can be made precise by showing that a smooth manifold carries a natural struc- ture of an infinitesimally affine space. This structure is comprised of two pieces of data: a sequence of symmetric and reflexive relations defining the tuples of mu- tual infinitesimally close points, called an infinitesimal structure, and an action of affine combinations on these tuples. For smooth manifolds the only natural infin- itesimal structure that has been considered so far is the one generated by the first neighbourhood of the diagonal. In this paper we construct natural infinitesimal structures for higher-order neighbourhoods of the diagonal and show that on any manifold any symmetric affine connection extends to a second-order infinitesimally affine structure. Introduction A deeply rooted intuition about smooth manifolds is that of spaces that become linear spaces in the infinitesimal neighbourhood of each point. On the infinitesimal scale the geometry underlying a manifold is thus affine geometry. To make this intuition precise requires a good theory of infinitesimals as well as defining precisely what it means for two points on a manifold to be infinitesimally close. As regards infinitesimals we make use of Synthetic Differential Geometry (SDG) and adopt the neighbourhoods of the diagonal from Algebraic Geometry to define when two points are infinitesimally close. The key observations on how to proceed have been made by Kock in [8]: 1) The first neighbourhood arXiv:1809.05944v2 [math.DG] 29 Aug 2020 of the diagonal exists on formal manifolds and can be understood as a symmetric, reflexive relation on points, saying when two points are infinitesimal neighbours, and 2) we can form affine combinations of points that are mutual neighbours. -
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. -
EXOTIC SPHERES and CURVATURE 1. Introduction Exotic
BULLETIN (New Series) OF THE AMERICAN MATHEMATICAL SOCIETY Volume 45, Number 4, October 2008, Pages 595–616 S 0273-0979(08)01213-5 Article electronically published on July 1, 2008 EXOTIC SPHERES AND CURVATURE M. JOACHIM AND D. J. WRAITH Abstract. Since their discovery by Milnor in 1956, exotic spheres have pro- vided a fascinating object of study for geometers. In this article we survey what is known about the curvature of exotic spheres. 1. Introduction Exotic spheres are manifolds which are homeomorphic but not diffeomorphic to a standard sphere. In this introduction our aims are twofold: First, to give a brief account of the discovery of exotic spheres and to make some general remarks about the structure of these objects as smooth manifolds. Second, to outline the basics of curvature for Riemannian manifolds which we will need later on. In subsequent sections, we will explore the interaction between topology and geometry for exotic spheres. We will use the term differentiable to mean differentiable of class C∞,and all diffeomorphisms will be assumed to be smooth. As every graduate student knows, a smooth manifold is a topological manifold that is equipped with a smooth (differentiable) structure, that is, a smooth maximal atlas. Recall that an atlas is a collection of charts (homeomorphisms from open neighbourhoods in the manifold onto open subsets of some Euclidean space), the domains of which cover the manifold. Where the chart domains overlap, we impose a smooth compatibility condition for the charts [doC, chapter 0] if we wish our manifold to be smooth. Such an atlas can then be extended to a maximal smooth atlas by including all possible charts which satisfy the compatibility condition with the original maps. -
Vector Fields
Vector Calculus Independent Study Unit 5: Vector Fields A vector field is a function which associates a vector to every point in space. Vector fields are everywhere in nature, from the wind (which has a velocity vector at every point) to gravity (which, in the simplest interpretation, would exert a vector force at on a mass at every point) to the gradient of any scalar field (for example, the gradient of the temperature field assigns to each point a vector which says which direction to travel if you want to get hotter fastest). In this section, you will learn the following techniques and topics: • How to graph a vector field by picking lots of points, evaluating the field at those points, and then drawing the resulting vector with its tail at the point. • A flow line for a velocity vector field is a path ~σ(t) that satisfies ~σ0(t)=F~(~σ(t)) For example, a tiny speck of dust in the wind follows a flow line. If you have an acceleration vector field, a flow line path satisfies ~σ00(t)=F~(~σ(t)) [For example, a tiny comet being acted on by gravity.] • Any vector field F~ which is equal to ∇f for some f is called a con- servative vector field, and f its potential. The terminology comes from physics; by the fundamental theorem of calculus for work in- tegrals, the work done by moving from one point to another in a conservative vector field doesn’t depend on the path and is simply the difference in potential at the two points. -
Lecture Notes on Foliation Theory
INDIAN INSTITUTE OF TECHNOLOGY BOMBAY Department of Mathematics Seminar Lectures on Foliation Theory 1 : FALL 2008 Lecture 1 Basic requirements for this Seminar Series: Familiarity with the notion of differential manifold, submersion, vector bundles. 1 Some Examples Let us begin with some examples: m d m−d (1) Write R = R × R . As we know this is one of the several cartesian product m decomposition of R . Via the second projection, this can also be thought of as a ‘trivial m−d vector bundle’ of rank d over R . This also gives the trivial example of a codim. d- n d foliation of R , as a decomposition into d-dimensional leaves R × {y} as y varies over m−d R . (2) A little more generally, we may consider any two manifolds M, N and a submersion f : M → N. Here M can be written as a disjoint union of fibres of f each one is a submanifold of dimension equal to dim M − dim N = d. We say f is a submersion of M of codimension d. The manifold structure for the fibres comes from an atlas for M via the surjective form of implicit function theorem since dfp : TpM → Tf(p)N is surjective at every point of M. We would like to consider this description also as a codim d foliation. However, this is also too simple minded one and hence we would call them simple foliations. If the fibres of the submersion are connected as well, then we call it strictly simple. (3) Kronecker Foliation of a Torus Let us now consider something non trivial. -
Introduction to a Line Integral of a Vector Field Math Insight
Introduction to a Line Integral of a Vector Field Math Insight A line integral (sometimes called a path integral) is the integral of some function along a curve. One can integrate a scalar-valued function1 along a curve, obtaining for example, the mass of a wire from its density. One can also integrate a certain type of vector-valued functions along a curve. These vector-valued functions are the ones where the input and output dimensions are the same, and we usually represent them as vector fields2. One interpretation of the line integral of a vector field is the amount of work that a force field does on a particle as it moves along a curve. To illustrate this concept, we return to the slinky example3 we used to introduce arc length. Here, our slinky will be the helix parameterized4 by the function c(t)=(cost,sint,t/(3π)), for 0≤t≤6π, Imagine that you put a small-magnetized bead on your slinky (the bead has a small hole in it, so it can slide along the slinky). Next, imagine that you put a large magnet to the left of the slink, as shown by the large green square in the below applet. The magnet will induce a magnetic field F(x,y,z), shown by the green arrows. Particle on helix with magnet. The red helix is parametrized by c(t)=(cost,sint,t/(3π)), for 0≤t≤6π. For a given value of t (changed by the blue point on the slider), the magenta point represents a magnetic bead at point c(t). -
Math 600 Day 6: Abstract Smooth Manifolds
Math 600 Day 6: Abstract Smooth Manifolds Ryan Blair University of Pennsylvania Tuesday September 28, 2010 Ryan Blair (U Penn) Math 600 Day 6: Abstract Smooth Manifolds Tuesday September 28, 2010 1 / 21 Outline 1 Transition to abstract smooth manifolds Partitions of unity on differentiable manifolds. Ryan Blair (U Penn) Math 600 Day 6: Abstract Smooth Manifolds Tuesday September 28, 2010 2 / 21 A Word About Last Time Theorem (Sard’s Theorem) The set of critical values of a smooth map always has measure zero in the receiving space. Theorem Let A ⊂ Rn be open and let f : A → Rp be a smooth function whose derivative f ′(x) has maximal rank p whenever f (x) = 0. Then f −1(0) is a (n − p)-dimensional manifold in Rn. Ryan Blair (U Penn) Math 600 Day 6: Abstract Smooth Manifolds Tuesday September 28, 2010 3 / 21 Transition to abstract smooth manifolds Transition to abstract smooth manifolds Up to this point, we have viewed smooth manifolds as subsets of Euclidean spaces, and in that setting have defined: 1 coordinate systems 2 manifolds-with-boundary 3 tangent spaces 4 differentiable maps and stated the Chain Rule and Inverse Function Theorem. Ryan Blair (U Penn) Math 600 Day 6: Abstract Smooth Manifolds Tuesday September 28, 2010 4 / 21 Transition to abstract smooth manifolds Now we want to define differentiable (= smooth) manifolds in an abstract setting, without assuming they are subsets of some Euclidean space. Many differentiable manifolds come to our attention this way. Here are just a few examples: 1 tangent and cotangent bundles over smooth manifolds 2 Grassmann manifolds 3 manifolds built by ”surgery” from other manifolds Ryan Blair (U Penn) Math 600 Day 6: Abstract Smooth Manifolds Tuesday September 28, 2010 5 / 21 Transition to abstract smooth manifolds Our starting point is the definition of a topological manifold of dimension n as a topological space Mn in which each point has an open neighborhood homeomorphic to Rn (locally Euclidean property), and which, in addition, is Hausdorff and second countable. -
INTRODUCTION to ALGEBRAIC GEOMETRY 1. Preliminary Of
INTRODUCTION TO ALGEBRAIC GEOMETRY WEI-PING LI 1. Preliminary of Calculus on Manifolds 1.1. Tangent Vectors. What are tangent vectors we encounter in Calculus? 2 0 (1) Given a parametrised curve α(t) = x(t); y(t) in R , α (t) = x0(t); y0(t) is a tangent vector of the curve. (2) Given a surface given by a parameterisation x(u; v) = x(u; v); y(u; v); z(u; v); @x @x n = × is a normal vector of the surface. Any vector @u @v perpendicular to n is a tangent vector of the surface at the corresponding point. (3) Let v = (a; b; c) be a unit tangent vector of R3 at a point p 2 R3, f(x; y; z) be a differentiable function in an open neighbourhood of p, we can have the directional derivative of f in the direction v: @f @f @f D f = a (p) + b (p) + c (p): (1.1) v @x @y @z In fact, given any tangent vector v = (a; b; c), not necessarily a unit vector, we still can define an operator on the set of functions which are differentiable in open neighbourhood of p as in (1.1) Thus we can take the viewpoint that each tangent vector of R3 at p is an operator on the set of differential functions at p, i.e. @ @ @ v = (a; b; v) ! a + b + c j ; @x @y @z p or simply @ @ @ v = (a; b; c) ! a + b + c (1.2) @x @y @z 3 with the evaluation at p understood. -
Hausdorff Morita Equivalence of Singular Foliations
Hausdorff Morita Equivalence of singular foliations Alfonso Garmendia∗ Marco Zambony Abstract We introduce a notion of equivalence for singular foliations - understood as suitable families of vector fields - that preserves their transverse geometry. Associated to every singular foliation there is a holonomy groupoid, by the work of Androulidakis-Skandalis. We show that our notion of equivalence is compatible with this assignment, and as a consequence we obtain several invariants. Further, we show that it unifies some of the notions of transverse equivalence for regular foliations that appeared in the 1980's. Contents Introduction 2 1 Background on singular foliations and pullbacks 4 1.1 Singular foliations and their pullbacks . .4 1.2 Relation with pullbacks of Lie groupoids and Lie algebroids . .6 2 Hausdorff Morita equivalence of singular foliations 7 2.1 Definition of Hausdorff Morita equivalence . .7 2.2 First invariants . .9 2.3 Elementary examples . 11 2.4 Examples obtained by pushing forward foliations . 12 2.5 Examples obtained from Morita equivalence of related objects . 15 3 Morita equivalent holonomy groupoids 17 3.1 Holonomy groupoids . 17 arXiv:1803.00896v1 [math.DG] 2 Mar 2018 3.2 Morita equivalent holonomy groupoids: the case of projective foliations . 21 3.3 Pullbacks of foliations and their holonomy groupoids . 21 3.4 Morita equivalence for open topological groupoids . 27 3.5 Holonomy transformations . 29 3.6 Further invariants . 30 3.7 A second look at Hausdorff Morita equivalence of singular foliations . 31 4 Further developments 33 4.1 An extended equivalence for singular foliations . 33 ∗KU Leuven, Department of Mathematics, Celestijnenlaan 200B box 2400, BE-3001 Leuven, Belgium. -
DIFFERENTIAL GEOMETRY COURSE NOTES 1.1. Review of Topology. Definition 1.1. a Topological Space Is a Pair (X,T ) Consisting of A
DIFFERENTIAL GEOMETRY COURSE NOTES KO HONDA 1. REVIEW OF TOPOLOGY AND LINEAR ALGEBRA 1.1. Review of topology. Definition 1.1. A topological space is a pair (X; T ) consisting of a set X and a collection T = fUαg of subsets of X, satisfying the following: (1) ;;X 2 T , (2) if Uα;Uβ 2 T , then Uα \ Uβ 2 T , (3) if Uα 2 T for all α 2 I, then [α2I Uα 2 T . (Here I is an indexing set, and is not necessarily finite.) T is called a topology for X and Uα 2 T is called an open set of X. n Example 1: R = R × R × · · · × R (n times) = f(x1; : : : ; xn) j xi 2 R; i = 1; : : : ; ng, called real n-dimensional space. How to define a topology T on Rn? We would at least like to include open balls of radius r about y 2 Rn: n Br(y) = fx 2 R j jx − yj < rg; where p 2 2 jx − yj = (x1 − y1) + ··· + (xn − yn) : n n Question: Is T0 = fBr(y) j y 2 R ; r 2 (0; 1)g a valid topology for R ? n No, so you must add more open sets to T0 to get a valid topology for R . T = fU j 8y 2 U; 9Br(y) ⊂ Ug: Example 2A: S1 = f(x; y) 2 R2 j x2 + y2 = 1g. A reasonable topology on S1 is the topology induced by the inclusion S1 ⊂ R2. Definition 1.2. Let (X; T ) be a topological space and let f : Y ! X. -
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.