Characterizations of Planar Lattices by Left-Relations
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Two Poset Polytopes
Discrete Comput Geom 1:9-23 (1986) G eometrv)i.~.reh, ~ ( :*mllmlati~ml © l~fi $1~ter-Vtrlq New Yorklu¢. t¢ Two Poset Polytopes Richard P. Stanley* Department of Mathematics, Massachusetts Institute of Technology, Cambridge, MA 02139 Abstract. Two convex polytopes, called the order polytope d)(P) and chain polytope <~(P), are associated with a finite poset P. There is a close interplay between the combinatorial structure of P and the geometric structure of E~(P). For instance, the order polynomial fl(P, m) of P and Ehrhart poly- nomial i(~9(P),m) of O(P) are related by f~(P,m+l)=i(d)(P),m). A "transfer map" then allows us to transfer properties of O(P) to W(P). In particular, we transfer known inequalities involving linear extensions of P to some new inequalities. I. The Order Polytope Our aim is to investigate two convex polytopes associated with a finite partially ordered set (poset) P. The first of these, which we call the "order polytope" and denote by O(P), has been the subject of considerable scrutiny, both explicit and implicit, Much of what we say about the order polytope will be essentially a review of well-known results, albeit ones scattered throughout the literature, sometimes in a rather obscure form. The second polytope, called the "chain polytope" and denoted if(P), seems never to have been previously considered per se. It is a special case of the vertex-packing polytope of a graph (see Section 2) but has many special properties not in general valid or meaningful for graphs. -
Coms: Complexes of Oriented Matroids Hans-Jürgen Bandelt, Victor Chepoi, Kolja Knauer
COMs: Complexes of Oriented Matroids Hans-Jürgen Bandelt, Victor Chepoi, Kolja Knauer To cite this version: Hans-Jürgen Bandelt, Victor Chepoi, Kolja Knauer. COMs: Complexes of Oriented Matroids. Journal of Combinatorial Theory, Series A, Elsevier, 2018, 156, pp.195–237. hal-01457780 HAL Id: hal-01457780 https://hal.archives-ouvertes.fr/hal-01457780 Submitted on 6 Feb 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. COMs: Complexes of Oriented Matroids Hans-J¨urgenBandelt1, Victor Chepoi2, and Kolja Knauer2 1Fachbereich Mathematik, Universit¨atHamburg, Bundesstr. 55, 20146 Hamburg, Germany, [email protected] 2Laboratoire d'Informatique Fondamentale, Aix-Marseille Universit´eand CNRS, Facult´edes Sciences de Luminy, F-13288 Marseille Cedex 9, France victor.chepoi, kolja.knauer @lif.univ-mrs.fr f g Abstract. In his seminal 1983 paper, Jim Lawrence introduced lopsided sets and featured them as asym- metric counterparts of oriented matroids, both sharing the key property of strong elimination. Moreover, symmetry of faces holds in both structures as well as in the so-called affine oriented matroids. These two fundamental properties (formulated for covectors) together lead to the natural notion of \conditional oriented matroid" (abbreviated COM). -
Algorithms for Incremental Planar Graph Drawing and Two-Page Book Embeddings
Algorithms for Incremental Planar Graph Drawing and Two-page Book Embeddings Inaugural-Dissertation zur Erlangung des Doktorgrades der Mathematisch-Naturwissenschaftlichen Fakult¨at der Universit¨at zu Koln¨ vorgelegt von Martin Gronemann aus Unna Koln¨ 2015 Berichterstatter (Gutachter): Prof. Dr. Michael Junger¨ Prof. Dr. Markus Chimani Prof. Dr. Bettina Speckmann Tag der m¨undlichenPr¨ufung: 23. Juni 2015 Zusammenfassung Diese Arbeit besch¨aftigt sich mit zwei Problemen bei denen es um Knoten- ordnungen in planaren Graphen geht. Hierbei werden als erstes Ordnungen betrachtet, die als Grundlage fur¨ inkrementelle Zeichenalgorithmen dienen. Solche Algorithmen erweitern in der Regel eine vorhandene Zeichnung durch schrittweises Hinzufugen¨ von Knoten in der durch die Ordnung gegebene Rei- henfolge. Zu diesem Zweck kommen im Gebiet des Graphenzeichnens verschie- dene Ordnungstypen zum Einsatz. Einigen dieser Ordnungen fehlen allerdings gewunschte¨ oder sogar fur¨ einige Algorithmen notwendige Eigenschaften. Diese Eigenschaften werden genauer untersucht und dabei ein neuer Typ von Ord- nung entwickelt, die sogenannte bitonische st-Ordnung, eine Ordnung, welche Eigenschaften kanonischer Ordnungen mit der Flexibilit¨at herk¨ommlicher st- Ordnungen kombiniert. Die zus¨atzliche Eigenschaft bitonisch zu sein erm¨oglicht es, eine st-Ordnung wie eine kanonische Ordnung zu verwenden. Es wird gezeigt, dass fur¨ jeden zwei-zusammenh¨angenden planaren Graphen eine bitonische st-Ordnung in linearer Zeit berechnet werden kann. Im Ge- gensatz zu kanonischen Ordnungen, k¨onnen st-Ordnungen naturgem¨aß auch fur¨ gerichtete Graphen verwendet werden. Diese F¨ahigkeit ist fur¨ das Zeichnen von aufw¨artsplanaren Graphen von besonderem Interesse, da eine bitonische st-Ordnung unter Umst¨anden es erlauben wurde,¨ vorhandene ungerichtete Zei- chenverfahren fur¨ den gerichteten Fall anzupassen. -
55 GRAPH DRAWING Emilio Di Giacomo, Giuseppe Liotta, Roberto Tamassia
55 GRAPH DRAWING Emilio Di Giacomo, Giuseppe Liotta, Roberto Tamassia INTRODUCTION Graph drawing addresses the problem of constructing geometric representations of graphs, and has important applications to key computer technologies such as soft- ware engineering, database systems, visual interfaces, and computer-aided design. Research on graph drawing has been conducted within several diverse areas, includ- ing discrete mathematics (topological graph theory, geometric graph theory, order theory), algorithmics (graph algorithms, data structures, computational geometry, vlsi), and human-computer interaction (visual languages, graphical user interfaces, information visualization). This chapter overviews aspects of graph drawing that are especially relevant to computational geometry. Basic definitions on drawings and their properties are given in Section 55.1. Bounds on geometric and topological properties of drawings (e.g., area and crossings) are presented in Section 55.2. Sec- tion 55.3 deals with the time complexity of fundamental graph drawing problems. An example of a drawing algorithm is given in Section 55.4. Techniques for drawing general graphs are surveyed in Section 55.5. 55.1 DRAWINGS AND THEIR PROPERTIES TYPES OF GRAPHS First, we define some terminology on graphs pertinent to graph drawing. Through- out this chapter let n and m be the number of graph vertices and edges respectively, and d the maximum vertex degree (i.e., number of edges incident to a vertex). GLOSSARY Degree-k graph: Graph with maximum degree d k. ≤ Digraph: Directed graph, i.e., graph with directed edges. Acyclic digraph: Digraph without directed cycles. Transitive edge: Edge (u, v) of a digraph is transitive if there is a directed path from u to v not containing edge (u, v). -
DA14 Abstracts 27
DA14 Abstracts 27 IP1 [email protected] Shape, Homology, Persistence, and Stability CP0 My personal journey to the fascinating world of geomet- Distributed Computation of Persistent Homology ric forms started 30 years ago with the invention of al- pha shapes in the plane. It took about 10 years before Advances in algorithms for computing persistent homol- we generalized the concept to higher dimensions, we pro- ogy have reduced the computation time drastically – as duced working software with a graphics interface for the long as the algorithm does not exhaust the available mem- 3-dimensional case, and we added homology to the com- ory. Following up on a recently presented parallel method putations. Needless to say that this foreshadowed the in- for persistence computation on shared memory systems, we ception of persistent homology, because it suggested the demonstrate that a simple adaption of the standard reduc- study of filtrations to capture the scale of a shape or data tion algorithm leads to a variant for distributed systems. set. Importantly, this method has fast algorithms. The Our algorithmic design ensures that the data is distributed arguably most useful result on persistent homology is the over the nodes without redundancy; this permits the com- stability of its diagrams under perturbations. putation of much larger instances than on a single machine. The parallelism often speeds up the computation compared Herbert Edelsbrunner to sequential and even parallel shared memory algorithms. Institute of Science and Technology Austria In our experiments, we were able to compute the persis- [email protected] tent homology of filtrations with more than a billion (109) elements within seconds on a cluster with 32 nodes using less than 10GB of memory per node. -
Upright-Quad Drawing of St-Planar Learning Spaces David Eppstein Computer Science Department, University of California, Irvine [email protected]
Journal of Graph Algorithms and Applications http://jgaa.info/ vol. 12, no. 1, pp. 51–72 (2008) Upright-Quad Drawing of st-Planar Learning Spaces David Eppstein Computer Science Department, University of California, Irvine [email protected] Abstract We consider graph drawing algorithms for learning spaces, a type of st-oriented partial cube derived from an antimatroid and used to model states of knowledge of students. We show how to draw any st-planar learning space so all internal faces are convex quadrilaterals with the bot- tom side horizontal and the left side vertical, with one minimal and one maximal vertex. Conversely, every such drawing represents an st-planar learning space. We also describe connections between these graphs and arrangements of translates of a quadrant. Our results imply that an an- timatroid has order dimension two if and only if it has convex dimension two. Article Type Communicated by Submitted Revised Regular paper M. Kaufmann and D. Wagner December 2006 February 2008 A preliminary version of this paper was presented in 2006 at the 14th International Symposium on Graph Drawing in Karlsruhe, Germany. A condensed treatment of this material also appears in Section 11.6 of [10]. Eppstein, Upright-Quad Drawing, JGAA, 12(1) 51–72 (2008) 52 1 Introduction A partial cube is a graph that can be given the geometric structure of a hyper- cube, by assigning the vertices bitvector labels in such a way that the graph distance between any pair of vertices equals the Hamming distance of their la- bels. Partial cubes can be used to describe benzenoid systems in chemistry [13], weak or partial orderings modeling voter preferences in multi-candidate elections [12], integer partitions in number theory [8], flip graphs of point set triangulations [9], and the hyperplane arrangements familiar to computational geometers [15, 7]; see [10] for additional applications. -
Graph Drawing Tutorial
Graph Drawing Tutorial Isabel F. Cruz Worcester Polytechnic Institute Roberto Tamassia Brown University Graph Drawing 0 Introduction Graph Drawing 1 ■ ■ covers), hierarchies), diagrams), diagrams), hierarchies), applications to visualization of andsystemsforthe algorithms, models, 30 53 41 28 27 47 11 16 21 44 15 14 20 18 52 29 17 56 WWW 22 54 38 63 34 58 45 55 51 31 12 Graph Drawing knowledge representation project management 1 9 13 61 32 46 telecommunications database systems 3 43 40 39 36 59 50 (browsing history) ... 62 42 35 37 software engineering 4 graphs 24 2 25 Graph Drawing 26 23 33 48 10 5 6 57 8 19 7 49 60 2 and networks (ER- (PERT (ring (class (isa Drawing Conventions ■ general constraints on the geometric representation of vertices and edges polyline drawing bend planar straight-line drawing orthogonal drawing Graph Drawing 3 Drawing Conventions planar othogonal straight-line drawing abc e d f g strong visibility representation f a c b d e g Graph Drawing 4 Drawing Conventions ■ directed acyclic graphs are usually drawn in such a way that all edges “flow” in the same direction, e.g., from left to right, or from bottom to top ■ such upward drawings effectively visualize hierarchical relationships, such as covering digraphs of ordered sets ■ not every planar acyclic digraph admits a planar upward drawing Graph Drawing 5 Resolution ■ display devices and the human eye have finite resolution ■ examples of resolution rules: ■ integer coordinates for vertices and bends (grid drawings) ■ prescribed minimum distance between vertices ■ prescribed minimum distance between vertices and nonincident edges ■ prescribed minimum angle formed by consecutive incident edges (angular resolution) Graph Drawing 6 Angular Resolution • The angular resolution ρ of a straight- line drawing is the smallest angle formed by two edges incident on the same vertex • High angular resolution is desirable in visualization applications and in the design of optical communication networks. -
A STRWTURE THEORY for Ordiired SETS
Discrete Mathematics 35 (1981) 53-118 North-Holland Publishing Company A STRWTURE THEORY FOR ORDiIRED SETS Dwight DUFFUS l?cpwtmwof Mathematics, Emory U&e&y, Atktnta, GA 30322, USA Ivan RIVAL Department of Mathematics and Stdstics, 7’he Universityof Calgary, Calgary, Alberta, Canada Received 16 December 1980 The theory of ordered sets lies at the confiuence of several branches of mathematics including set theory, lattice theory, combinatorial theory, and even aspects of modern operations research. While ordered sets are ohen peripheral to the mainstream of any of these theories there arise, from time to time. prcblems which are order-theoretic in substance. The aim of this work is to fashion a classification scheme for ordered sets which is aimed at providing a unified vantage point for some of the problems encountered with ordered sets. This classification scheme is based on a structure theory much akin to the familiar subdirect representation theory so useful in general algebra. The novelty of the structure theory lies in the importance that we attach to, and the widespread use that we make of, the concept of retract. At present, some vindication for our clrrssification scheme can be found by examining its effectiveness for totally ordered sets (e.g., well-ordered sets, the rationals, reals, etc.) as well as for those finite orciered sets that arise commonly in combinatorial investigations (e.g., crowns and fences). Preface The theory of ordered sets is today a burgeoning branch of mathematics. It both draws upon and applies to several other branches of mathematics, including algebra, set theory, and combinatorics. -
A29 Integers 9 (2009), 353-374
#A29 INTEGERS 9 (2009), 353-374 COMBINATORIAL PROPERTIES OF THE ANTICHAINS OF A GARLAND Emanuele Munarini Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, 20133 Milano, Italy. [email protected] Received: 5/16/08, Revised: 2/24/09, Accepted: 3/5/09 Abstract In this paper we study some combinatorial properties of the antichains of a garland, or double fence. Specifically, we encode the order ideals and the antichains in terms of words of a regular language, we obtain several enumerative properties (such as generating series, recurrences and explicit formulae), we consider some statistics leading to Riordan matrices, we study the relations between the lattice of ideals and the semilattice of antichains, and finally we give a combinatorial interpretation of the antichains as lattice paths with no peaks and no valleys. 1. Introduction Fences (or zigzag posets), crowns, garlands (or double fences) and several of their generalizations are posets that are very well-known in combinatorics [1, 6, 7, 8, 9, 11, 14, 15, 19, 20, 21, 26] and in the theory of Ockham algebras [2, 3, 4]. Here we are interested in garlands, which can be considered as an extension of fences of even order and of crowns. More precisely, the garland of order n is the partially ordered set defined as follows: is the empty poset, is the chain of length 1 and, for Gn G0 G1 any other n 2, is the poset on 2n elements x , . , x , y , . , y with cover ≥ Gn 1 n 1 n relations x1 < y1, x1 < y2, xi < yi 1, xi < yi, xi < yi+1 for i = 2, . -