Constructing Discrete Morse Functions

Total Page:16

File Type:pdf, Size:1020Kb

Constructing Discrete Morse Functions Thomas Lewiner Constructing Discrete Morse Functions MsC Thesis DEPARTMENT OF MATHEMATICS Post{graduate program in Applied Mathematics Rio de Janeiro July 2002 Thomas Lewiner Constructing Discrete Morse Functions MsC Thesis Thesis presented to the Post{graduate Program in Applied Mathematics of the Mathematics Department, PUC{Rio as partial ful¯llment of the requirements for the degree of Master in Applied Mathematics Advisor : Prof. H¶elioC^ortesVieira Lopes Co{Advisor: Prof. Geovan Tavares dos Santos Rio de Janeiro July 2002 Thomas Lewiner Constructing Discrete Morse Functions Thesis presented to the Post{graduate Program in Applied Mathematics of the Mathematics Department, PUC{Rio as partial ful¯llment of the requirements for the degree of Mas- ter in Applied Mathematics. Approved by the Examinating Comission: Prof. H¶elioC^ortesVieira Lopes Advisor Department of Mathematics | PUC{Rio Prof. Geovan Tavares dos Santos Co{Advisor Department of Mathematics | PUC{Rio Prof. Luis Carlos Pacheco R. Velho IMPA Prof. Jorge Stol¯ UNICAMP Prof. Ney Augusto Dumont Coordinator of the Science and Engineering Center | PUC{Rio Rio de Janeiro, 10 de July de 2002 All rights reserved. Thomas Lewiner He graduated from the Ecole Polytechnique (Paris, France) in Algebra and Computer Science, and in Theoretical Phy- sics. He specialized himself at the Ecole Sup¶erieure des T¶el¶ecommunications (Paris, France) in Signal and Image Pro- cessing, and in Project Management. He worked for Inventel in wireless telecommunication systems based on BlueTooth technology. During his master preparation, he developed with his advisors tools oc computational topology. Ficha Catalogr¶a¯ca Lewiner, Thomas Constructing Discrete Morse Functions/ Thomas Lewi- ner; advisor: H¶elioC^ortesVieira Lopes; co{advisor: Geovan Tavares dos Santos. | Rio de Janeiro : PUC{Rio, Depart- ment of Mathematics, 2002. v., 89 f: il. ; 29,7 cm 1. MsC Thesis - Pontif¶³ciaUniversidade Cat¶olicado Rio de Janeiro, Department of Mathematics. Bibliography included. 1. Mathematics { Thesis. 2. Morse Theory. 3. Forman Theory. 4. Computacional Topology. 5. Computacional Ge- ometry. 6. Geometric Modelling. 6. Discrete Mathematics. I. Lopes, H¶elioC^ortesVieira. II. Santos, Geovan Tavares dos. III. Pontif¶³cia Universidade Cat¶olicado Rio de Ja- neiro. Department of Mathematics. IV. Title. CDD: 510 Acknowledgments To my advisors Professors H¶elio Lopes and Geovan Tavares for the support, the everyday kindness and the incentive for the realisation of this work. To the CNPq and the PUC{Rio, for the ¯nancial support, without which this work would not have been realized. To my grand{mothers, who su®ered the most of my expatriation. To my mother and father, sisters and all my family. To my colleagues of the PUC{Rio, who have me loved this place. To the professors Marcos da Silvera, Jean{Marie Nicolas and Anne Germa who o®ered me the opportunity of this cooperation. To the people of the Mathematic departament for the constant help, particularly to Ana Cristina, Creuza and Sinesio. Abstract Lewiner, Thomas; Lopes, H¶elioC^ortesVieira; Santos, Geovan Ta- vares dos. Constructing Discrete Morse Functions. Rio de Janeiro, 2002. 89p. MsC Thesis | Department of Mathematics, Pontif¶³ciaUniversidade Cat¶olicado Rio de Janeiro. Morse theory has been considered a powerful tool in its applications to computational topology, computer graphics and geometric modeling. It was originally formulated for smooth manifolds. Recently, Robin Forman formulated a version of this theory for discrete structures such as cell complexes. It opens up several categories of interesting objects (particularly meshes) to applications of Morse theory. Once a Morse function has been de¯ned on a manifold, then information about its topology can be deduced from its critical elements. The purpose of this work is to design an algorithm to de¯ne optimal discrete Morse functions on general cell complex, where optimality entails having the least number of critical elements. This problem is proven here to be MAX{ SNP hard. However, we provide a linear algorithm that, for the case of 2{manifolds, always reaches optimality. Moreover, we proved various results on the structure of a discrete Morse function. In particular, we provide an equivalent representation by hyperfo- rests. From this point of view, we designed a construction of discrete Morse functions for general cell complexes of arbitrary ¯nite dimension. The re- sulting algorithm is quadratic in time and, although not guaranteed to be optimal, gives optimal answers in most of the practical cases. Keywords Morse Theory; Forman Theory; Computational Topology; Computatio- nal Geometry; Solid Modeling; Discrete Mathematics. Contents Foreword 12 I Introduction 14 I.1 Motivations and applications 14 I.2 Results 16 I.3 Outline 17 II Preliminaries 18 II.1 Discrete structures 18 II.2 Basic concepts of algebraic topology 23 III Forman's discrete Morse theory 31 III.1 Discrete gradient vector ¯eld 31 III.2 Discrete Morse functions 35 III.3 Topological properties 39 III.4 Optimality in discrete Morse functions 42 IV Optimal discrete Morse functions on surfaces 45 IV.1 Optimality conditions 45 IV.2 Algorithm 47 IV.3 First extension to non{manifolds 50 IV.4 Proof and analysis 51 IV.5 Mixing with geometry 52 IV.6 Results 53 V Structure of a discrete Morse function 55 V.1 Layers of a combinatorial vector ¯eld 55 V.2 Discrete Morse functions, acyclic matchings and hyperforests 58 V.3 Discrete Morse numbers as topological invariants for 3{manifolds 63 VI Constructing discrete Morse functions 65 VI.1 Data structure 65 VI.2 Algorithms for constructing discrete Morse functions out of hyper- forests 66 VI.3 Optimality considerations 69 VI.4 Di®erent heuristics 71 VI.5 Results 76 VII Future Works 85 Bibliography 86 List of ¯gures II.1 An 8-squares cylinder model. 18 II.2 The 0/1 graph of an 8-squares cylinder (¯gure II.1): nodes represents vertices, links represents edges. 19 II.3 A tree extracted from the graph of ¯gure II.2. 19 II.4 A bipartite representation of the graph of ¯gure II.2. 20 II.5 A matching on the graph of ¯gure II.4. 20 II.6 The dual graph of ¯gure II.1. 20 II.7 A tree extracted from the graph of ¯gure II.6. 20 II.8 A hypergraph example. 21 II.9 The dual hypergraph of the graph of ¯gure II.2. 21 II.10 A triangulated torus. 24 II.11 A construction of a torus with 4 cells. 24 II.12 The Hasse diagram of a simple cell complex. 25 II.13 The Hasse diagram of a non{PL torus. 26 II.14 A non{manifold example: non{regular edge. 26 II.15 Another non{manifold example: the neighborhood of the points of the dangling edge is homeomorphic to R. 26 II.16 A part of a triangulation and its dual. 27 II.17 Cycles in a 1{cell complex are circuits. 28 II.18 The cycles of a map are around seas (holes), where lands are faces and frontiers are edges. 28 II.19 An elementary collapse. 30 II.20 The collapse of a tetrahedra onto a point. 30 III.1 An example of a combinatorial vector ¯eld. 32 III.2 The closed V {path of the combinatorial vector ¯eld of ¯gure III.1 (in red). 32 III.3 Examples of discrete gradient vector ¯eld. 33 III.4 Hasse diagram of the examples of ¯gure III.3. 33 III.5 The Hasse diagram of the combinatorial vector ¯eld of ¯gure III.1, and the circuit of its closed V {path (in red). 34 III.6 Canceling critical cells 34 III.7 Examples of discrete Morse functions 36 III.8 A discrete gradient vector ¯eld and its corresponding discrete Morse function. 37 III.9 Re¯ning a discrete gradient vector ¯eld: all the new vertices, edges and faces are paired easily. 37 III.10The Hasse diagram of an optimal discrete gradient vector ¯eld on a Segment and on a Triangle. 38 III.11The Hasse diagram of the cartesian product of the discrete gradient vector ¯elds of ¯gure III.10. 38 III.12Steps of the collapse of a simple cell complex. 39 III.13The critical steps of the extension of a torus. 41 III.14The number of matchings in the Hasse diagram is ¯nite. 42 III.15A \gadget" used in E¸gecio¸gluand Gonzalez proof. 43 IV.1 Examples of surfaces without boundary. 45 IV.2 Examples of surfaces with a non{empty boundary. 46 IV.3 EdgeBreaker mesh compression codes on a triangulated torus. 48 IV.4 The resulting face{spanning tree T and its complement graph G. 48 IV.5 Loop added at step 2 to a face{spanning tree T of ¯gure II.1 (no critical cell) 48 IV.6 The discrete Morse function on the spanning tree T of ¯gure IV.3 (1 critical face). 48 IV.7 The complement graph G of the cylinder model and its discrete Morse function (1 critical vertex and 1 critical edge). 49 IV.8 The discrete Morse function on the complement graph G of ¯gure IV.3 (1 critical vertex and 2 critical edges). 49 IV.9 A non{manifold complex with a dangling edge (on the left) and its critical cells (on the right): 1 critical vertex and 2 critical faces. 50 IV.10A non{manifold complex with a corner vertex (on the left) and its critical cells (on the right): 1 critical vertex and 2 critical faces. 50 IV.11A non{manifold complex with a non{regular edge (on the left) and its critical cells (on the right): 1 critical vertex and 2 critical faces. 50 IV.12Two discrete gradient vector ¯elds on a 2{sphere, both with 2 critical cells. 52 IV.13Execution time vs. the number of cells of the cell complex K: the complexity is linear.
Recommended publications
  • Persistent Homology of Unweighted Complex Networks Via Discrete
    www.nature.com/scientificreports OPEN Persistent homology of unweighted complex networks via discrete Morse theory Received: 17 January 2019 Harish Kannan1, Emil Saucan2,3, Indrava Roy1 & Areejit Samal 1,4 Accepted: 6 September 2019 Topological data analysis can reveal higher-order structure beyond pairwise connections between Published: xx xx xxxx vertices in complex networks. We present a new method based on discrete Morse theory to study topological properties of unweighted and undirected networks using persistent homology. Leveraging on the features of discrete Morse theory, our method not only captures the topology of the clique complex of such graphs via the concept of critical simplices, but also achieves close to the theoretical minimum number of critical simplices in several analyzed model and real networks. This leads to a reduced fltration scheme based on the subsequence of the corresponding critical weights, thereby leading to a signifcant increase in computational efciency. We have employed our fltration scheme to explore the persistent homology of several model and real-world networks. In particular, we show that our method can detect diferences in the higher-order structure of networks, and the corresponding persistence diagrams can be used to distinguish between diferent model networks. In summary, our method based on discrete Morse theory further increases the applicability of persistent homology to investigate the global topology of complex networks. In recent years, the feld of topological data analysis (TDA) has rapidly grown to provide a set of powerful tools to analyze various important features of data1. In this context, persistent homology has played a key role in bring- ing TDA to the fore of modern data analysis.
    [Show full text]
  • Graph Reconstruction by Discrete Morse Theory Arxiv:1803.05093V2 [Cs.CG] 21 Mar 2018
    Graph Reconstruction by Discrete Morse Theory Tamal K. Dey,∗ Jiayuan Wang,∗ Yusu Wang∗ Abstract Recovering hidden graph-like structures from potentially noisy data is a fundamental task in modern data analysis. Recently, a persistence-guided discrete Morse-based framework to extract a geometric graph from low-dimensional data has become popular. However, to date, there is very limited theoretical understanding of this framework in terms of graph reconstruction. This paper makes a first step towards closing this gap. Specifically, first, leveraging existing theoretical understanding of persistence-guided discrete Morse cancellation, we provide a simplified version of the existing discrete Morse-based graph reconstruction algorithm. We then introduce a simple and natural noise model and show that the aforementioned framework can correctly reconstruct a graph under this noise model, in the sense that it has the same loop structure as the hidden ground-truth graph, and is also geometrically close. We also provide some experimental results for our simplified graph-reconstruction algorithm. 1 Introduction Recovering hidden structures from potentially noisy data is a fundamental task in modern data analysis. A particular type of structure often of interest is the geometric graph-like structure. For example, given a collection of GPS trajectories, recovering the hidden road network can be modeled as reconstructing a geometric graph embedded in the plane. Given the simulated density field of dark matters in universe, finding the hidden filamentary structures is essentially a problem of geometric graph reconstruction. Different approaches have been developed for reconstructing a curve or a metric graph from input data. For example, in computer graphics, much work have been done in extracting arXiv:1803.05093v2 [cs.CG] 21 Mar 2018 1D skeleton of geometric models using the medial axis or Reeb graphs [10, 29, 20, 16, 22, 7].
    [Show full text]
  • Arxiv:2012.08669V1 [Math.CT] 15 Dec 2020 2 Preface
    Sheaf Theory Through Examples (Abridged Version) Daniel Rosiak December 12, 2020 arXiv:2012.08669v1 [math.CT] 15 Dec 2020 2 Preface After circulating an earlier version of this work among colleagues back in 2018, with the initial aim of providing a gentle and example-heavy introduction to sheaves aimed at a less specialized audience than is typical, I was encouraged by the feedback of readers, many of whom found the manuscript (or portions thereof) helpful; this encouragement led me to continue to make various additions and modifications over the years. The project is now under contract with the MIT Press, which would publish it as an open access book in 2021 or early 2022. In the meantime, a number of readers have encouraged me to make available at least a portion of the book through arXiv. The present version represents a little more than two-thirds of what the professionally edited and published book would contain: the fifth chapter and a concluding chapter are missing from this version. The fifth chapter is dedicated to toposes, a number of more involved applications of sheaves (including to the \n- queens problem" in chess, Schreier graphs for self-similar groups, cellular automata, and more), and discussion of constructions and examples from cohesive toposes. Feedback or comments on the present work can be directed to the author's personal email, and would of course be appreciated. 3 4 Contents Introduction 7 0.1 An Invitation . .7 0.2 A First Pass at the Idea of a Sheaf . 11 0.3 Outline of Contents . 20 1 Categorical Fundamentals for Sheaves 23 1.1 Categorical Preliminaries .
    [Show full text]
  • RGB Image-Based Data Analysis Via Discrete Morse Theory and Persistent Homology
    RGB IMAGE-BASED DATA ANALYSIS 1 RGB image-based data analysis via discrete Morse theory and persistent homology Chuan Du*, Christopher Szul,* Adarsh Manawa, Nima Rasekh, Rosemary Guzman, and Ruth Davidson** Abstract—Understanding and comparing images for the pur- uses a combination of DMT for the partitioning and skeletoniz- poses of data analysis is currently a very computationally ing (in other words finding the underlying topological features demanding task. A group at Australian National University of) images using differences in grayscale values as the distance (ANU) recently developed open-source code that can detect function for DMT and PH calculations. fundamental topological features of a grayscale image in a The data analysis methods we have developed for analyzing computationally feasible manner. This is made possible by the spatial properties of the images could lead to image-based fact that computers store grayscale images as cubical cellular complexes. These complexes can be studied using the techniques predictive data analysis that bypass the computational require- of discrete Morse theory. We expand the functionality of the ments of machine learning, as well as lead to novel targets ANU code by introducing methods and software for analyzing for which key statistical properties of images should be under images encoded in red, green, and blue (RGB), because this study to boost traditional methods of predictive data analysis. image encoding is very popular for publicly available data. Our The methods in [10], [11] and the code released with them methods allow the extraction of key topological information from were developed to handle grayscale images. But publicly avail- RGB images via informative persistence diagrams by introducing able image-based data is usually presented in heat-map data novel methods for transforming RGB-to-grayscale.
    [Show full text]
  • Persistence in Discrete Morse Theory
    Persistence in discrete Morse theory Dissertation zur Erlangung des mathematisch-naturwissenschaftlichen Doktorgrades Doctor rerum naturalium der Georg-August-Universität Göttingen vorgelegt von Ulrich Bauer aus München Göttingen 2011 D7 Referent: Prof. Dr. Max Wardetzky Koreferent: Prof. Dr. Robert Schaback Weiterer Referent: Prof. Dr. Herbert Edelsbrunner Tag der mündlichen Prüfung: 12.5.2011 Contents 1 Introduction1 1.1 Overview................................. 1 1.2 Related work ............................... 7 1.3 Acknowledgements ........................... 8 2 Discrete Morse theory 11 2.1 CW complexes .............................. 11 2.2 Discrete vector fields .......................... 12 2.3 The Morse complex ........................... 15 2.4 Morse and pseudo-Morse functions . 17 2.5 Symbolic perturbation ......................... 20 2.6 Level and order subcomplexes .................... 23 2.7 Straight-line homotopies of discrete Morse functions . 28 2.8 PL functions and discrete Morse functions . 29 2.9 Morse theory for general CW complexes . 34 3 Persistent homology of discrete Morse functions 41 3.1 Birth, death, and persistence pairs . 42 3.2 Duality and persistence ........................ 44 3.3 Stability of persistence diagrams ................... 45 4 Optimal topological simplification of functions on surfaces 51 4.1 Topological denoising by simplification . 51 4.2 The persistence hierarchy ....................... 53 4.3 The plateau function .......................... 59 4.4 Checking the constraint ........................ 62 5 Efficient computation of topological simplifications 67 5.1 Defining a consistent total order .................... 68 iii Contents 5.2 Computing persistence pairs ..................... 68 5.3 Extracting the gradient vector field . 70 5.4 Constructing the simplified function . 70 5.5 Correctness of the algorithm ...................... 71 6 Discussion 75 6.1 Computational results ......................... 75 6.2 Relation to simplification of persistence diagrams .
    [Show full text]
  • Introduction to Topological Data Analysis Julien Tierny
    Introduction to Topological Data Analysis Julien Tierny To cite this version: Julien Tierny. Introduction to Topological Data Analysis. Doctoral. France. 2017. cel-01581941 HAL Id: cel-01581941 https://hal.archives-ouvertes.fr/cel-01581941 Submitted on 5 Sep 2017 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. Sorbonne Universités, UPMC Univ Paris 06 Laboratoire d’Informatique de Paris 6 Julien Tierny Introduction to Topological Data Analysis Sorbonne Universités, UPMC Univ Paris 06 Laboratoire d’Informatique de Paris 6 UMR UPMC/CNRS 7606 – Tour 26 4 Place Jussieu – 75252 Paris Cedex 05 – France Notations X Topological space ¶X Boundary of a topological space M Manifold Rd Euclidean space of dimension d s, t d-simplex, face of a d-simplex v, e, t, T Vertex, edge, triangle and tetrahedron Lk(s), St(s) Link and star of a simplex Lkd(s), Std(s) d-simplices of the link and the star of a simplex K Simplicial complex T Triangulation M Piecewise linear manifold bi i-th Betti number c Euler characteristic th ai i barycentric coordinates of a point p relatively
    [Show full text]
  • Calculating Persistent Homology Using Discrete Morse Theory
    CALCULATING PERSISTENT HOMOLOGY USING DISCRETE MORSE THEORY NEHA LINGAREDDY ABSTRACT. In this expository paper, we explore how the fundamental shape of a high- dimensional data set can be studied mathematically. First, as an elementary example of recovering the topological features of a space using continuous functions, we introduce the field of Morse theory. Next, for use on simpler spaces called simplicial complexes, we describe a combinatorial variant of Morse theory - discrete Morse theory. Then, to understand how we derive simplicial complexes from a set of points, we describe the field of persistent homology and show how discrete Morse theory can be used to simplify cal- culations in persistent homology. We end the paper with explaining specific algorithms using discrete Morse theory that show increases in the efficiency of calculating persistent homology. Some familiarity with Topology and Linear Algebra is assumed. CONTENTS 1. Introduction 1 2. Morse theory basics 3 3. Simplicial complexes 5 4. Discrete Morse theory 7 4.1. Discrete Morse functions 7 4.2. Gradient vector fields 10 4.3. Morse matchings 13 5. Persistent homology 14 6. Persistent homology and discrete Morse theory 17 7. Computing optimal Morse matchings 18 8. Conclusion 18 9. Acknowledgments 19 10. Bibliography 19 References 19 1. INTRODUCTION A fundamental problem in topological data analysis (TDA) is how, when given a high- dimensional data set, one can gather the shape and features of the data. As a data set is often plagued with issues such as noise and non-uniform sampling, it is hard to quantify how discrete points in a data set can gather into a global structure.
    [Show full text]
  • Discrete Morse Theory and Localization
    JID:JPAA AID:5884 /FLA [m3L; v1.235; Prn:30/04/2018; 13:23] P.1 (1-30) Journal of Pure and Applied Algebra ••• (••••) •••–••• Contents lists available at ScienceDirect Journal of Pure and Applied Algebra www.elsevier.com/locate/jpaa Discrete Morse theory and localization Vidit Nanda a r t i c l e i n f o a b s t r a c t Article history: Incidence relations among the cells of a regular CW complex produce a poset- Received 14 August 2017 enriched category of entrance paths whose classifying space is homotopy-equivalent Received in revised form 26 March to that complex. We show here that each acyclic partial matching (in the sense of 2018 discrete Morse theory) of the cells corresponds precisely to a homotopy-preserving Available online xxxx localization of the associated entrance path category. Restricting attention further Communicated by C.A. Weibel to the full localized subcategory spanned by critical cells, we obtain the discrete flow category whose classifying space is also shown to lie in the homotopy class of the original CW complex. This flow category forms a combinatorial and computable counterpart to the one described by Cohen, Jones and Segal in the context of smooth Morse theory. © 2018 Elsevier B.V. All rights reserved. 1. Introduction To the reader who desires a quick summary of this work, we recommend a brief glance at Fig. 1. Illustrated there is a regular CW complex X along with a simple operation which removes two cells x and y, where y is a face of x (written x >y).
    [Show full text]
  • Merge Trees in Discrete Morse Theory Benjamin Johnson Ursinus College, [email protected]
    Ursinus College Digital Commons @ Ursinus College Mathematics Summer Fellows Student Research 7-19-2019 Merge Trees in Discrete Morse Theory Benjamin Johnson Ursinus College, [email protected] Follow this and additional works at: https://digitalcommons.ursinus.edu/math_sum Part of the Discrete Mathematics and Combinatorics Commons, and the Geometry and Topology Commons Click here to let us know how access to this document benefits oy u. Recommended Citation Johnson, Benjamin, "Merge Trees in Discrete Morse Theory" (2019). Mathematics Summer Fellows. 12. https://digitalcommons.ursinus.edu/math_sum/12 This Paper is brought to you for free and open access by the Student Research at Digital Commons @ Ursinus College. It has been accepted for inclusion in Mathematics Summer Fellows by an authorized administrator of Digital Commons @ Ursinus College. For more information, please contact [email protected]. Merge trees Benjamin Johnson May 2019 Abstract The field of topological data analysis seeks to use techniques in topol- ogy to study large data sets. The hope is that rather than single quantities that summarize the data, such as mean or standard deviation, informa- tion about the data can be learned by studying the overall “shape” of the data. One way to summarize this data is through a merge tree. Merge trees can be thought of as keeping track of certain clusters of data and determining when they merge together. In this paper, we will study merge trees induced by a discrete Morse function on a tree. Under a suitable notion of equivalence of merge trees, we then count the number of merge trees that can be induced on a star graph.
    [Show full text]
  • A User's Guide to Discrete Morse Theory
    S´eminaire Lotharingien de Combinatoire 48 (2002), Article B48c A USER’S GUIDE TO DISCRETE MORSE THEORY ROBIN FORMAN Abstract. A number of questions from a variety of areas of mathematics lead one to the problem of analyzing the topology of a simplicial complex. However, there are few general techniques available to aid us in this study. On the other hand, some very general theories have been developed for the study of smooth manifolds. One of the most powerful, and useful, of these theories is Morse Theory. In this paper we present a combinatorial adaptation of Morse Theory, which we call discrete Morse Theory, that may be applied to any simplicial complex (or more general cell complex). The goal of this paper is to present an overview of the subject of discrete Morse Theory that is sufficient both to understand the major applications of the theory to combinatorics, and to apply the the theory to new problems. We will not be presenting theorems in their most recent or most general form, and simple examples will often take the place of proofs. We hope to convey the fact that the theory is really very simple, and there is not much that one needs to know before one can become a “user”. 0. Introduction A number of questions from a variety of areas of mathematics lead one to the problem of analyzing the topology of a simplicial complex. We will see some examples in these notes. However, there are few general techniques available to aid us in this study. On the other hand, some very general theories have been developed for the study of smooth manifolds.
    [Show full text]
  • Morse Theory for Cell Complexes*
    Advances in Mathematics AI1650 Advances in Mathematics 134, 90145 (1998) Article No. AI971650 Morse Theory for Cell Complexes* Robin Forman Department of Mathematics, Rice University, Houston, Texas 77251 Received July 20, 1995 0. INTRODUCTION In this paper we will present a very simple discrete Morse theory for CW complexes. In addition to proving analogues of the main theorems of Morse theory, we also present discrete analogues of such (seemingly) intrinsically smooth notions as the gradient vector field and the gradient flow associated to a Morse function. Using this, we define a Morse complex, a differential complex built out of the critical points of our discrete Morse function which has the same homology as the underlying manifold. This Morse theory takes on particular significance in the context of PL manifolds. To clarify this statement, we take a small historical digression. In 1961, Smale proved the h-cobordism theorem for smooth manifolds (and hence its corollary, the Poincare conjecture in dimension 5) using a combination of handlebody theory and Morse theory [Sm2]. In [Mi2], Milnor presented a completely Morse theoretic proof of the h-cobordism theorem. In ([Ma], [Ba], [St]) Mazur, Barden and Stallings generalized Smale's theorem by replacing Smale's hypothesis that the cobordism be simply-connected by a weaker simple-homotopy condition. Along the way, this more general theorem (the s-cobordism theorem) was extended to other categories of manifolds. In particular, a PL s-cobordism theorem was established. In this case, it was necessary to work completely within the context of handlebody theory. The Morse theory presented in this paper can be used to give a Morse theoretic proof of the PL s-cobordism theorem, along the lines of the proof in [Mi2].
    [Show full text]
  • The Zero-Energy Ground States of Supersymmetric Lattice Models
    The zero-energy ground states of supersymmetric lattice models Ruben La July 10, 2018 Bachelor thesis Mathematics and Physics & Astronomy Supervisor: prof. dr. Kareljan Schoutens, prof. dr. Sergey Shadrin 1 Institute of Physics Korteweg-de Vries Institute for Mathematics Faculty of Sciences University of Amsterdam Abstract This thesis focusses on studying the ground states of a few supersymmetric lattice models: the one-dimensional zig-zag ladder [Hui10], the Nicolai model [Nic76] and the Z2 Nicolai model [SKN17], and the two-dimensional triangular lattice model [HMM+12]. The main objective is to derive the ground state generating function of these models. Furthermore, we aim to study the behaviour of the ground states at different filling fractions and to give expressions for a few of the ground states. The first part of the thesis introduces some of the preliminary concepts from homology theory that will be used to count the number of ground states. In particular, we formulate the homo- logical perturbation lemma [Cra04], which is one of the main ingredients for the computation of the number of ground states. Afterwards, the notion of supersymmetric lattice models will be introduced and some of its key features shall be discussed, especially the features concerning the ground states. In particular, a strong relation between the ground states of supersymmetric lattice models and the homology of the supercharge shall be discussed. Using techniques from homology theory, we can derive relations for the ground state generating functions of the lattice models mentioned above. For the zig-zag ladder, we shall give an expression in closed form for the ground state generating function, for which a recurrence relation was already known [Hui10].
    [Show full text]