The Zero-Energy Ground States of Supersymmetric Lattice Models

Total Page:16

File Type:pdf, Size:1020Kb

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]. For the Nicolai model, the Z2 Nicolai model and the triangular lattice model on a 3 × N lattice with vertical periodicity and open horizontal boundaries, we shall derive a recurrence relation for the ground state generating function, as well as a closed formula for the Z2 Nicolai model and the 3 × N triangular lattice model. Using these results about the generating functions, we shall study the ground states at different filling fractions and derive a few physical quantities such as the expectation of the filling fractions and the filling fraction for which the number of ground states is largest. Finally, we shall give expressions for some of these ground states. For the zig-zag ladder, we will present a few expressions for the ground states at quarter filling and for the Nicolai models, we shall identify all the classical ground states. Title: The zero-energy ground states of supersymmetric lattice models Authors: Ruben La, [email protected], 11039582 Supervisors: prof. dr. Kareljan Schoutens, prof. dr. Sergey Shadrin Second grader: prof. dr. Bernard Nienhuis, prof. dr. Jasper Stokman End date: July 10, 2018 Institute of Physics University of Amsterdam Science Park 904, 1098 XH Amsterdam http://www.iop.uva.nl Korteweg-de Vries Institute for Mathematics University of Amsterdam Science Park 904, 1098 XH Amsterdam http://www.kdvi.uva.nl 2 Contents 1. Introduction 5 1.1. Organisation of the thesis and main goals . .6 1.2. Acknowledgements . .7 2. Preliminaries 8 2.1. Homology and cohomology . .8 2.2. Homological perturbation lemma . 10 3. Supersymmetric lattice models for fermionic particles 11 3.1. Supersymmetry . 11 3.2. Witten index . 13 3.3. Lattice fermions . 13 3.4. Hard-core spinless fermions . 14 3.5. Ground states and relation to homology . 15 3.5.1. Ground state generating function . 15 3.5.2. Relation to the homology of Q ........................ 15 4. One-dimensional supersymmetric models 17 4.1. Zig-zag ladder . 17 4.1.1. Ground states of the zig-zag ladder . 18 4.1.2. Ground states at quarter filling . 20 4.2. State space structure for one-dimensional chains . 20 4.3. Z2 Nicolai model . 22 4.3.1. Ground state generating function of the Z2 Nicolai model . 23 4.3.2. Ground states at different filling fractions . 30 4.3.3. Classical ground states and ground states at 1=3rd and 2=3rd filling . 31 4.3.4. Supersymmetric SYK model . 32 4.4. Nicolai model . 32 4.4.1. Relation to localisation . 33 4.4.2. Ground state generating function of the Nicolai model . 33 4.4.3. Ground states of the Nicolai model at different filling fractions . 35 4.4.4. Classical ground states . 36 5. Two-dimensional supersymmetric models 37 5.1. Triangular lattice model . 37 5.1.1. Current results about the ground states . 37 5.2. Ground states of the 3 × N triangular lattice . 38 5.3. M × N triangular lattice with periodic vertical boundary conditions . 41 6. Conclusion 42 Bibliography 44 3 Populaire samenvatting 46 A. Spectral sequences 48 A.1. Spectral sequences . 48 A.2. Filtrations . 48 A.3. Bicomplexes . 49 A.4. Application to the Nicolai models . 50 4 1. Introduction 1In condensed matter physics, one of the main goals is to understand the physical properties of materials. One of the challenges that a condensed matter physicist encounters is that systems can become complex very quickly when the number of particles in the system is large. The physicist is then forced to make simplifications in order to be able to understand anything about the system. One such simplification is a lattice model. A lattice model is a physical model defined on a lattice that describes many-particle systems and their interactions. The particles of the systems are confined to the lattice sites and are not allowed to move freely in the continuum of space. Studying quantum many-body systems on a lattice was originally motivated by the tight-binding appoximation, which describes valence electrons in a crystal by approximating the electron orbitals by the atomic orbitals of the atoms involved. The associated tight-binding model thus forms a lattice model, with the ions as its lattice sites. The tight- binding model is one of the simplest lattice models, as it does not take the interaction between the electrons into consideration. As such, the tight-binding model does its job quite well in describing materials in which the interactions between the electrons are weak. However, there exist materials for which the valence electrons are strongly interacting. Therefore, we want to have a model that includes the electrostatic repulsion of the electrons. One such model is the Hubbard model. The Hubbard model is described by a Hamiltonian consisting of a nearest- neighbour hopping term parametrised by t and an on-site interaction for electrons with opposite spin parameterised by some interaction strength U. Although the Hubbard model seems very simple, some of its properties are not yet completely understood. For instance, as mentioned in [Hui10], a precisely half-filled system with strong interactions U ≥ t describes a ferromagnet. However, upon doping away from half-filling, the anti-ferromagnetic order is destroyed. This regime of the Hubbard model is not well-understood and is one of the open problems concerning the Hubbard model. One can propose a simpler model than the Hubbard model which still includes the strong interactions between the electrons. A very succesful type of lattice models was introduced in [FSdB03]: N = 2 supersymmetric lattice models. In a nutshell, supersymmetry is a theory originating from particle physics that describes a symmetry between fermions and bosons. The theory states that each elementary fermion forms a pair with a boson, and vice versa. These two particles together are called superpartners. Using this idea, one can introduce the theory of su- persymmetric lattice models, where the supersymmetry relates a many-particle state consisting of an odd number of lattice fermions (a fermionic state) with a many-particle state consisting of an even number of lattice fermions (a bosonic state). Supersymmetric lattice models are equipped with two operators Q and Qy, called supercharges, with the following properties. The operator Q (Qy) removes (adds) one fermion from (to) the system, or the other way around. Both operators square to zero and the Hamiltonian of the system reads H = fQ; Qyg. Su- persymmetric lattice models have a few key features. First of all, the Hamiltonian is positive definite, with which we mean that all the eigenenergies are non-negative. Furthermore, we can 1The information in [Hui10, Introduction] was used as a source for the historic overview of the lattice mod- els (the tight-binding model, the Hubbard model and the supersymmetric lattice models) presented in our Introduction. 5 choose each fermionic energy eigenstate jfi with strictly positive energy in such a way that it forms a doublet with its superpartner jgi = Qjfi, which is a bosonic energy eigenstate whose particle number differs from the original state by precisely 1. The last feature is the most important one and relates the ground state structure to the homology of Q. It is interesting to study the ground state structure of the system, as it allows us to study and derive some interesting physical quantities. For instance studying the degeneracy of the ground states has many implications for the thermodynamics of the system as well as for other properties such as the transport of charge. Furthermore, as shown in [Mor16], there is a connection between the ground states and ergodicity breaking, which in turn is related to many-body localisation, which is one of the current hot topics in condensed matter physics. The last key feature of supersym- metric lattice models is that there exists an explicit isomorphism between the homology of the supercharge Q and the kernel of the Hamiltonian. This allows us to use results from homology theory to study the ground state structure. 1.1. Organisation of the thesis and main goals Studying the ground state structure of supersymmetric lattice models is the main topic of this thesis.
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]
  • Discrete Morse Theory and Classifying Spaces
    Discrete Morse Theory and Classifying Spaces Vidit Nanda, Dai Tamaki, and Kohei Tanaka Abstract The aim of this paper is to develop a refinement of Forman’s discrete Morse theory. To an acyclic partial matching µ on a finite regular CW complex X, Forman introduced a discrete analogue of gradient flows. Although Forman’s gradient flow has been proved to be useful in practical computations of homology groups, it is not sufficient to recover the homotopy type of X. Forman also proved the existence of a CW complex which is homotopy equivalent to X and whose cells are in one-to-one correspondence with the critical cells of µ, but the construction is ad hoc and does not have a combinatorial description. By relaxing the definition of Forman’s gradient flows, we introduce the notion of flow paths, which contains enough information to reconstruct the homotopy type of X, while retaining a combinatorial description. The critical difference from Forman’s gradient flows is the existence of a partial order on the set of flow paths, from which a 2-category C(µ) is constructed. It is shown that the classifying space of C(µ) is homotopy equivalent to X by using homotopy theory of 2-categories. This result can be also regarded as a discrete analogue of the unpublished work of Cohen, Jones, and Segal on Morse theory in early 90’s. Contents 1 Introduction 2 1.1 DiscreteMorseTheory............................... .. 2 1.2 MainResult....................................... 3 1.3 OrganizationofthePaper ............................. .. 4 1.4 Acknowledgments................................... 5 2 Discrete Morse Theory 5 2.1 DiscreteMorseFunctions ............................
    [Show full text]