Discrete Differential Geometry: an Applied Introduction
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An Algorithm for the Construction of Intrinsic Delaunay Triangulations with Applications to Digital Geometry Processing
An Algorithm for the Construction of Intrinsic Delaunay Triangulations with Applications to Digital Geometry Processing Matthew Fisher Boris Springborn Peter Schroder¨ Alexander I. Bobenko Caltech TU Berlin Caltech TU Berlin Abstract The discrete Laplace-Beltrami operator plays a prominent role in many Digital Geometry Processing applications ranging from de- noising to parameterization, editing, and physical simulation. The standard discretization uses the cotangents of the angles in the im- mersed mesh which leads to a variety of numerical problems. We advocate the use of the intrinsic Laplace-Beltrami operator. It sat- isfies a local maximum principle, guaranteeing, e.g., that no flipped triangles can occur in parameterizations. It also leads to better con- ditioned linear systems. The intrinsic Laplace-Beltrami operator is based on an intrinsic Delaunay triangulation of the surface. We detail an incremental algorithm to construct such triangulations to- gether with an overlay structure which captures the relationship be- tween the extrinsic and intrinsic triangulations. Using a variety of example meshes we demonstrate the numerical benefits of the in- trinsic Laplace-Beltrami operator. Figure 1: Left: carrier of the (cat head) surface as defined by the original embedded mesh. Right: the intrinsic Delaunay triangu- 1 Introduction lation of the same carrier. Delaunay edges which appear in the original triangulation are shown in white. Some of the original 2 Delaunay triangulations of domains in R play an important role edges are not present anymore (these are shown in black). In their in many numerical computing applications because of the quality stead we see red edges which appear as the result of intrinsic flip- guarantees they make, such as: among all triangulations of the con- ping. -
Combinatorial Laplacian and Rank Aggregation
Combinatorial Laplacian and Rank Aggregation Combinatorial Laplacian and Rank Aggregation Yuan Yao Stanford University ICIAM, Z¨urich,July 16–20, 2007 Joint work with Lek-Heng Lim Combinatorial Laplacian and Rank Aggregation Outline 1 Two Motivating Examples 2 Reflections on Ranking Ordinal vs. Cardinal Global, Local, vs. Pairwise 3 Discrete Exterior Calculus and Combinatorial Laplacian Discrete Exterior Calculus Combinatorial Laplacian Operator 4 Hodge Theory Cyclicity of Pairwise Rankings Consistency of Pairwise Rankings 5 Conclusions and Future Work Combinatorial Laplacian and Rank Aggregation Two Motivating Examples Example I: Customer-Product Rating Example (Customer-Product Rating) m×n m-by-n customer-product rating matrix X ∈ R X typically contains lots of missing values (say ≥ 90%). The first-order statistics, mean score for each product, might suffer from most customers just rate a very small portion of the products different products might have different raters, whence mean scores involve noise due to arbitrary individual rating scales Combinatorial Laplacian and Rank Aggregation Two Motivating Examples From 1st Order to 2nd Order: Pairwise Rankings The arithmetic mean of score difference between product i and j over all customers who have rated both of them, P k (Xkj − Xki ) gij = , #{k : Xki , Xkj exist} is translation invariant. If all the scores are positive, the geometric mean of score ratio over all customers who have rated both i and j, !1/#{k:Xki ,Xkj exist} Y Xkj gij = , Xki k is scale invariant. Combinatorial Laplacian and Rank Aggregation Two Motivating Examples More invariant Define the pairwise ranking gij as the probability that product j is preferred to i in excess of a purely random choice, 1 g = Pr{k : X > X } − . -
Arxiv:1704.04175V1 [Math.DG] 13 Apr 2017 Umnfls[ Submanifolds Mty[ Ometry Eerhr Ncmlxgoer.I at H Loihshe Algorithms to the Aim Fact, the in with Geometry
SAGEMATH EXPERIMENTS IN DIFFERENTIAL AND COMPLEX GEOMETRY DANIELE ANGELLA Abstract. This note summarizes the talk by the author at the workshop “Geometry and Computer Science” held in Pescara in February 2017. We present how SageMath can help in research in Complex and Differential Geometry, with two simple applications, which are not intended to be original. We consider two "classification problems" on quotients of Lie groups, namely, "computing cohomological invariants" [AFR15, LUV14], and "classifying special geo- metric structures" [ABP17], and we set the problems to be solved with SageMath [S+09]. Introduction Complex Geometry is the study of manifolds locally modelled on the linear complex space Cn. A natural way to construct compact complex manifolds is to study the projective geometry n n+1 n of CP = C 0 /C×. In fact, analytic submanifolds of CP are equivalent to algebraic submanifolds [GAGA\ { }]. On the one side, this means that both algebraic and analytic techniques are available for their study. On the other side, this means also that this class of manifolds is quite restrictive. In particular, they do not suffice to describe some Theoretical Physics models e.g. [Str86]. Since [Thu76], new examples of complex non-projective, even non-Kähler manifolds have been investigated, and many different constructions have been proposed. One would study classes of manifolds whose geometry is, in some sense, combinatorically or alge- braically described, in order to perform explicit computations. In this sense, great interest has been deserved to homogeneous spaces of nilpotent Lie groups, say nilmanifolds, whose ge- ometry [Bel00, FG04] and cohomology [Nom54] is encoded in the Lie algebra. -
DISCRETE DIFFERENTIAL GEOMETRY: an APPLIED INTRODUCTION Keenan Crane • CMU 15-458/858 LECTURE 15: CURVATURE
DISCRETE DIFFERENTIAL GEOMETRY: AN APPLIED INTRODUCTION Keenan Crane • CMU 15-458/858 LECTURE 15: CURVATURE DISCRETE DIFFERENTIAL GEOMETRY: AN APPLIED INTRODUCTION Keenan Crane • CMU 15-458/858 Curvature—Overview • Intuitively, describes “how much a shape bends” – Extrinsic: how quickly does the tangent plane/normal change? – Intrinsic: how much do quantities differ from flat case? N T B Curvature—Overview • Driving force behind wide variety of physical phenomena – Objects want to reduce—or restore—their curvature – Even space and time are driven by curvature… Curvature—Overview • Gives a coordinate-invariant description of shape – fundamental theorems of plane curves, space curves, surfaces, … • Amazing fact: curvature gives you information about global topology! – “local-global theorems”: turning number, Gauss-Bonnet, … Curvature—Overview • Geometric algorithms: shape analysis, local descriptors, smoothing, … • Numerical simulation: elastic rods/shells, surface tension, … • Image processing algorithms: denoising, feature/contour detection, … Thürey et al 2010 Gaser et al Kass et al 1987 Grinspun et al 2003 Curvature of Curves Review: Curvature of a Plane Curve • Informally, curvature describes “how much a curve bends” • More formally, the curvature of an arc-length parameterized plane curve can be expressed as the rate of change in the tangent Equivalently: Here the angle brackets denote the usual dot product, i.e., . Review: Curvature and Torsion of a Space Curve •For a plane curve, curvature captured the notion of “bending” •For a space curve we also have torsion, which captures “twisting” Intuition: torsion is “out of plane bending” increasing torsion Review: Fundamental Theorem of Space Curves •The fundamental theorem of space curves tells that given the curvature κ and torsion τ of an arc-length parameterized space curve, we can recover the curve (up to rigid motion) •Formally: integrate the Frenet-Serret equations; intuitively: start drawing a curve, bend & twist at prescribed rate. -
History of Mathematics
Georgia Department of Education History of Mathematics K-12 Mathematics Introduction The Georgia Mathematics Curriculum focuses on actively engaging the students in the development of mathematical understanding by using manipulatives and a variety of representations, working independently and cooperatively to solve problems, estimating and computing efficiently, and conducting investigations and recording findings. There is a shift towards applying mathematical concepts and skills in the context of authentic problems and for the student to understand concepts rather than merely follow a sequence of procedures. In mathematics classrooms, students will learn to think critically in a mathematical way with an understanding that there are many different ways to a solution and sometimes more than one right answer in applied mathematics. Mathematics is the economy of information. The central idea of all mathematics is to discover how knowing some things well, via reasoning, permit students to know much else—without having to commit the information to memory as a separate fact. It is the reasoned, logical connections that make mathematics coherent. The implementation of the Georgia Standards of Excellence in Mathematics places a greater emphasis on sense making, problem solving, reasoning, representation, connections, and communication. History of Mathematics History of Mathematics is a one-semester elective course option for students who have completed AP Calculus or are taking AP Calculus concurrently. It traces the development of major branches of mathematics throughout history, specifically algebra, geometry, number theory, and methods of proofs, how that development was influenced by the needs of various cultures, and how the mathematics in turn influenced culture. The course extends the numbers and counting, algebra, geometry, and data analysis and probability strands from previous courses, and includes a new history strand. -
A Comparison of Differential Calculus and Differential Geometry in Two
1 A Two-Dimensional Comparison of Differential Calculus and Differential Geometry Andrew Grossfield, Ph.D Vaughn College of Aeronautics and Technology Abstract and Introduction: Plane geometry is mainly the study of the properties of polygons and circles. Differential geometry is the study of curves that can be locally approximated by straight line segments. Differential calculus is the study of functions. These functions of calculus can be viewed as single-valued branches of curves in a coordinate system where the horizontal variable controls the vertical variable. In both studies the derivative multiplies incremental changes in the horizontal variable to yield incremental changes in the vertical variable and both studies possess the same rules of differentiation and integration. It seems that the two studies should be identical, that is, isomorphic. And, yet, students should be aware of important differences. In differential geometry, the horizontal and vertical units have the same dimensional units. In differential calculus the horizontal and vertical units are usually different, e.g., height vs. time. There are differences in the two studies with respect to the distance between points. In differential geometry, the Pythagorean slant distance formula prevails, while in the 2- dimensional plane of differential calculus there is no concept of slant distance. The derivative has a different meaning in each of the two subjects. In differential geometry, the slope of the tangent line determines the direction of the tangent line; that is, the angle with the horizontal axis. In differential calculus, there is no concept of direction; instead, the derivative describes a rate of change. In differential geometry the line described by the equation y = x subtends an angle, α, of 45° with the horizontal, but in calculus the linear relation, h = t, bears no concept of direction. -
Geometry-Aware Topological Decompositions of Meshes
UC Irvine UC Irvine Electronic Theses and Dissertations Title Geometry-aware topological decompositions of meshes Permalink https://escholarship.org/uc/item/3vh0q7wn Author Chen, Jia Publication Date 2019 Peer reviewed|Thesis/dissertation eScholarship.org Powered by the California Digital Library University of California UNIVERSITY OF CALIFORNIA, IRVINE Geometry-aware topological decompositions of meshes DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR OF PHILOSOPHY in Computer Science by Jia Chen Dissertation Committee: Professor Gopi Meenakshisundaram, Chair Professor Aditi Majumder Professor Shuang Zhao 2019 Chapter3 c 2016 ACM New York, NY, USA Chapter3 c 2018 ACM New York, NY, USA All other materials c 2019 Jia Chen DEDICATION To my family \. a man who keeps company with glaciers comes to feel tolerably insignificant by and by." { Mark Twain, A Tramp Abroad ii TABLE OF CONTENTS Page LIST OF FIGURESv LIST OF TABLESx LIST OF ALGORITHMS xi ACKNOWLEDGMENTS xii CURRICULUM VITAE xiii ABSTRACT OF THE DISSERTATION xiv 1 Introduction1 1.1 Cycles of topological properties.........................2 1.2 Topological decompositions of meshes......................4 2 Definitions and Background7 2.1 Surfaces and their topological classification...................7 2.2 Primal graph and dual graph embedded on a surface.............8 2.3 Paths and cycles.................................9 2.4 Tunnel and handle cycles............................. 11 3 Iterative localization of handle and tunnel cycles 13 3.1 Related work................................... 14 3.2 Problem formulation............................... 15 3.3 Localizing handle and tunnel cycles....................... 16 3.3.1 Iterative tree-cotree algorithm...................... 16 3.3.2 Cycle tightening.............................. 20 3.3.3 Decoupling composite fundamental cycles............... -
J.M. Sullivan, TU Berlin A: Curves Diff Geom I, SS 2019 This Course Is an Introduction to the Geometry of Smooth Curves and Surf
J.M. Sullivan, TU Berlin A: Curves Diff Geom I, SS 2019 This course is an introduction to the geometry of smooth if the velocity never vanishes). Then the speed is a (smooth) curves and surfaces in Euclidean space Rn (in particular for positive function of t. (The cusped curve β above is not regular n = 2; 3). The local shape of a curve or surface is described at t = 0; the other examples given are regular.) in terms of its curvatures. Many of the big theorems in the DE The lengthR [ : Länge] of a smooth curve α is defined as subject – such as the Gauss–Bonnet theorem, a highlight at the j j len(α) = I α˙(t) dt. (For a closed curve, of course, we should end of the semester – deal with integrals of curvature. Some integrate from 0 to T instead of over the whole real line.) For of these integrals are topological constants, unchanged under any subinterval [a; b] ⊂ I, we see that deformation of the original curve or surface. Z b Z b We will usually describe particular curves and surfaces jα˙(t)j dt ≥ α˙(t) dt = α(b) − α(a) : locally via parametrizations, rather than, say, as level sets. a a Whereas in algebraic geometry, the unit circle is typically be described as the level set x2 + y2 = 1, we might instead This simply means that the length of any curve is at least the parametrize it as (cos t; sin t). straight-line distance between its endpoints. Of course, by Euclidean space [DE: euklidischer Raum] The length of an arbitrary curve can be defined (following n we mean the vector space R 3 x = (x1;:::; xn), equipped Jordan) as its total variation: with with the standard inner product or scalar product [DE: P Xn Skalarproduktp ] ha; bi = a · b := aibi and its associated norm len(α):= TV(α):= sup α(ti) − α(ti−1) : jaj := ha; ai. -
Curvatures of Smooth and Discrete Surfaces
Curvatures of Smooth and Discrete Surfaces John M. Sullivan The curvatures of a smooth curve or surface are local measures of its shape. Here we consider analogous quantities for discrete curves and surfaces, meaning polygonal curves and triangulated polyhedral surfaces. We find that the most useful analogs are those which preserve integral relations for curvature, like the Gauß/Bonnet theorem. For simplicity, we usually restrict our attention to curves and surfaces in euclidean three space E3, although many of the results would easily generalize to other ambient manifolds of arbitrary dimension. Most of the material here is not new; some is even quite old. Although some refer- ences are given, no attempt has been made to give a comprehensive bibliography or an accurate picture of the history of the ideas. 1. Smooth curves, Framings and Integral Curvature Relations A companion article [Sul06] investigated the class of FTC (finite total curvature) curves, which includes both smooth and polygonal curves, as a way of unifying the treatment of curvature. Here we briefly review the theory of smooth curves from the point of view we will later adopt for surfaces. The curvatures of a smooth curve γ (which we usually assume is parametrized by its arclength s) are the local properties of its shape invariant under Euclidean motions. The only first-order information is the tangent line; since all lines in space are equivalent, there are no first-order invariants. Second-order information is given by the osculating circle, and the invariant is its curvature κ = 1/r. For a plane curve given as a graph y = f(x) let us contrast the notions of curvature and second derivative. -
Symplectic Geometry
Vorlesung aus dem Sommersemester 2013 Symplectic Geometry Prof. Dr. Fabian Ziltener TEXed by Viktor Kleen & Florian Stecker Contents 1 From Classical Mechanics to Symplectic Topology2 1.1 Introducing Symplectic Forms.........................2 1.2 Hamiltonian mechanics.............................2 1.3 Overview over some topics of this course...................3 1.4 Overview over some current questions....................4 2 Linear (pre-)symplectic geometry6 2.1 (Pre-)symplectic vector spaces and linear (pre-)symplectic maps......6 2.2 (Co-)isotropic and Lagrangian subspaces and the linear Weinstein Theorem 13 2.3 Linear symplectic reduction.......................... 16 2.4 Linear complex structures and the symplectic linear group......... 17 3 Symplectic Manifolds 26 3.1 Definition, Examples, Contangent bundle.................. 26 3.2 Classical Mechanics............................... 28 3.3 Symplectomorphisms, Hamiltonian diffeomorphisms and Poisson brackets 35 3.4 Darboux’ Theorem and Moser isotopy.................... 40 3.5 Symplectic, (co-)isotropic and Lagrangian submanifolds.......... 44 3.6 Symplectic and Hamiltonian Lie group actions, momentum maps, Marsden– Weinstein quotients............................... 48 3.7 Physical motivation: Symmetries of mechanical systems and Noether’s principle..................................... 52 3.8 Symplectic Quotients.............................. 53 1 From Classical Mechanics to Symplectic Topology 1.1 Introducing Symplectic Forms Definition 1.1. A symplectic form is a non–degenerate and closed 2–form on a manifold. Non–degeneracy means that if ωx(v, w) = 0 for all w ∈ TxM, then v = 0. Closed means that dω = 0. Reminder. A differential k–form on a manifold M is a family of skew–symmetric k– linear maps ×k (ωx : TxM → R)x∈M , which depends smoothly on x. 2n Definition 1.2. We define the standard symplectic form ω0 on R as follows: We 2n 2n 2n 2n identify the tangent space TxR with the vector space R . -
Analytic Vortex Solutions on Compact Hyperbolic Surfaces
Analytic vortex solutions on compact hyperbolic surfaces Rafael Maldonado∗ and Nicholas S. Mantony Department of Applied Mathematics and Theoretical Physics, Wilberforce Road, Cambridge CB3 0WA, U.K. August 27, 2018 Abstract We construct, for the first time, Abelian-Higgs vortices on certain compact surfaces of constant negative curvature. Such surfaces are represented by a tessellation of the hyperbolic plane by regular polygons. The Higgs field is given implicitly in terms of Schwarz triangle functions and analytic solutions are available for certain highly symmetric configurations. 1 Introduction Consider the Abelian-Higgs field theory on a background surface M with metric ds2 = Ω(x; y)(dx2+dy2). At critical coupling the static energy functional satisfies a Bogomolny bound 2 1 Z B Ω 2 E = + jD Φj2 + 1 − jΦj2 dxdy ≥ πN; (1) 2 2Ω i 2 where the topological invariant N (the `vortex number') is the number of zeros of Φ counted with multiplicity [1]. In the notation of [2] we have taken e2 = τ = 1. Equality in (1) is attained when the fields satisfy the Bogomolny vortex equations, which are obtained by completing the square in (1). In complex coordinates z = x + iy these are 2 Dz¯Φ = 0;B = Ω (1 − jΦj ): (2) This set of equations has smooth vortex solutions. As we explain in section 2, analytical results are most readily obtained when M is hyperbolic, having constant negative cur- vature K = −1, a case which is of interest in its own right due to the relation between arXiv:1502.01990v1 [hep-th] 6 Feb 2015 hyperbolic vortices and SO(3)-invariant instantons, [3]. -
HARMONIC FUNCTIONS for BOUNDED and UNBOUNDED P(X)
UNIVERSITY OF JYVASKYL¨ A¨ UNIVERSITAT¨ JYVASKYL¨ A¨ DEPARTMENT OF MATHEMATICS INSTITUT FUR¨ MATHEMATIK AND STATISTICS UND STATISTIK REPORT 130 BERICHT 130 EXISTENCE AND UNIQUENESS OF p(x)-HARMONIC FUNCTIONS FOR BOUNDED AND UNBOUNDED p(x) JUKKA KEISALA JYVASKYL¨ A¨ 2011 UNIVERSITY OF JYVASKYL¨ A¨ UNIVERSITAT¨ JYVASKYL¨ A¨ DEPARTMENT OF MATHEMATICS INSTITUT FUR¨ MATHEMATIK AND STATISTICS UND STATISTIK REPORT 130 BERICHT 130 EXISTENCE AND UNIQUENESS OF p(x)-HARMONIC FUNCTIONS FOR BOUNDED AND UNBOUNDED p(x) JUKKA KEISALA JYVASKYL¨ A¨ 2011 Editor: Pekka Koskela Department of Mathematics and Statistics P.O. Box 35 (MaD) FI{40014 University of Jyv¨askyl¨a Finland ISBN 978-951-39-4299-1 ISSN 1457-8905 Copyright c 2011, Jukka Keisala and University of Jyv¨askyl¨a University Printing House Jyv¨askyl¨a2011 Contents 0 Introduction 3 0.1 Notation and prerequisities . 6 1 Constant p, 1 < p < 1 8 1.1 The direct method of calculus of variations . 10 1.2 Dirichlet energy integral . 10 2 Infinity harmonic functions, p ≡ 1 13 2.1 Existence of solutions . 14 2.2 Uniqueness of solutions . 18 2.3 Minimizing property and related topics . 22 3 Variable p(x), with 1 < inf p(x) < sup p(x) < +1 24 4 Variable p(x) with p(·) ≡ +1 in a subdomain 30 4.1 Approximate solutions uk ...................... 32 4.2 Passing to the limit . 39 5 One-dimensional case, where p is continuous and sup p(x) = +1 45 5.1 Discussion . 45 5.2 Preliminary results . 47 5.3 Measure of fp(x) = +1g is positive . 48 6 Appendix 51 References 55 0 Introduction In this licentiate thesis we study the Dirichlet boundary value problem ( −∆ u(x) = 0; if x 2 Ω; p(x) (0.1) u(x) = f(x); if x 2 @Ω: Here Ω ⊂ Rn is a bounded domain, p :Ω ! (1; 1] a measurable function, f : @Ω ! R the boundary data, and −∆p(x)u(x) is the p(x)-Laplace operator, which is written as p(x)−2 −∆p(x)u(x) = − div jru(x)j ru(x) for finite p(x).