73 research outputs found
Jungerman ladders and index 2 constructions for genus embeddings of dense regular graphs
We construct several families of genus embeddings of near-complete graphs
using index 2 current graphs. In particular, we give the first known minimum
genus embeddings of certain families of octahedral graphs, solving a
longstanding conjecture of Jungerman and Ringel, and Hamiltonian cycle
complements, making partial progress on a problem of White. Index 2 current
graphs are also applied to various cases of the Map Color Theorem, in some
cases yielding significantly simpler solutions, e.g., the nonorientable genus
of . We give a complete description of the method, originally
due to Jungerman, from which all these results were obtained.Comment: 23 pages, 21 figures; fixed 2 figures from previous versio
Random Embeddings of Graphs: The Expected Number of Faces in Most Graphs is Logarithmic
A random 2-cell embedding of a connected graph in some orientable surface
is obtained by choosing a random local rotation around each vertex. Under this
setup, the number of faces or the genus of the corresponding 2-cell embedding
becomes a random variable. Random embeddings of two particular graph classes --
those of a bouquet of loops and those of parallel edges connecting two
vertices -- have been extensively studied and are well-understood. However,
little is known about more general graphs despite their important connections
with central problems in mainstream mathematics and in theoretical physics (see
[Lando & Zvonkin, Springer 2004]). There are also tight connections with
problems in computing (random generation, approximation algorithms). The
results of this paper, in particular, explain why Monte Carlo methods (see,
e.g., [Gross & Tucker, Ann. NY Acad. Sci 1979] and [Gross & Rieper, JGT 1991])
cannot work for approximating the minimum genus of graphs.
In his breakthrough work ([Stahl, JCTB 1991] and a series of other papers),
Stahl developed the foundation of "random topological graph theory". Most of
his results have been unsurpassed until today. In our work, we analyze the
expected number of faces of random embeddings (equivalently, the average genus)
of a graph . It was very recently shown [Campion Loth & Mohar, arXiv 2022]
that for any graph , the expected number of faces is at most linear. We show
that the actual expected number of faces is usually much smaller. In
particular, we prove the following results:
1) , for
sufficiently large. This greatly improves Stahl's upper bound for
this case.
2) For random models containing only graphs, whose maximum
degree is at most , we show that the expected number of faces is
.Comment: 44 pages, 6 figure
Recommended from our members
Genus Distributions of Graphs Constructed Through Amalgamations
Graphs are commonly represented as points in space connected by lines. The points in space are the vertices of the graph, and the lines joining them are the edges of the graph. A general definition of a graph is considered here, where multiple edges are allowed between two vertices and an edge is permitted to connect a vertex to itself. It is assumed that graphs are connected, i.e., any vertex in the graph is reachable from another distinct vertex either directly through an edge connecting them or by a path consisting of intermediate vertices and connecting edges. Under this visual representation, graphs can be drawn on various surfaces. The focus of my research is restricted to a class of surfaces that are characterized as compact connected orientable 2-manifolds. The drawings of graphs on surfaces that are of primary interest follow certain prescribed rules. These are called 2-cellular graph embeddings, or simply embeddings. A well-known closed formula makes it easy to enumerate the total number of 2-cellular embeddings for a given graph over all surfaces. A much harder task is to give a surface-wise breakdown of this number as a sequence of numbers that count the number of 2-cellular embeddings of a graph for each orientable surface. This sequence of numbers for a graph is known as the genus distribution of a graph. Prior research on genus distributions of graphs has primarily focused on making calculations of genus distributions for specific families of graphs. These families of graphs have often been contrived, and the methods used for finding their genus distributions have not been general enough to extend to other graph families. The research I have undertaken aims at developing and using a general method that frames the problem of calculating genus distributions of large graphs in terms of a partitioning of the genus distributions of smaller graphs. To this end, I use various operations such as edge-amalgamation, self-edge-amalgamation, and vertex-amalgamation to construct large graphs out of smaller graphs, by coupling their vertices and edges together in certain consistent ways. This method assumes that the partitioned genus distribution of the smaller graphs is known or is easily calculable by computer, for instance, by using the famous Heffter-Edmonds algorithm. As an outcome of the techniques used, I obtain general recurrences and closed-formulas that give genus distributions for infinitely many recursively specifiable graph families. I also give an easily understood method for finding non-trivial examples of distinct graphs having the same genus distribution. In addition to this, I describe an algorithm that computes the genus distributions for a family of graphs known as the 4-regular outerplanar graphs
Schematics of Graphs and Hypergraphs
Graphenzeichnen als ein Teilgebiet der Informatik befasst sich mit dem Ziel Graphen oder deren Verallgemeinerung Hypergraphen geometrisch zu realisieren. BeschrĂ€nkt man sich dabei auf visuelles Hervorheben von wesentlichen Informationen in Zeichenmodellen, spricht man von Schemata. Hauptinstrumente sind Konstruktionsalgorithmen und Charakterisierungen von Graphenklassen, die fĂŒr die Konstruktion geeignet sind. In dieser Arbeit werden Schemata fĂŒr Graphen und Hypergraphen formalisiert und mit den genannten Instrumenten untersucht. In der Dissertation wird zunĂ€chst das âpartial edge drawingâ (kurz: PED) Modell fĂŒr Graphen (bezĂŒglich gradliniger Zeichnung) untersucht. Dabei wird um Kreuzungen im Zentrum der Kante visuell zu eliminieren jede Kante durch ein kreuzungsfreies TeilstĂŒck (= Stummel) am Start- und am Zielknoten ersetzt. Als Standard hat sich eine PED-Variante etabliert, in der das LĂ€ngenverhĂ€ltnis zwischen Stummel und Kante genau 1â4 ist (kurz: 1â4-SHPED). FĂŒr 1â4-SHPEDs werden Konstruktionsalgorithmen, Klassifizierung, Implementierung und Evaluation prĂ€sentiert. AuĂerdem werden PED-Varianten mit festen Knotenpositionen und auf Basis orthogonaler Zeichnungen erforscht. Danach wird das BUS Modell fĂŒr Hypergraphen untersucht, in welchem Hyperkanten durch fette horizontale oder vertikale â als BUS bezeichnete â Segmente reprĂ€sentiert werden. Dazu wird eine vollstĂ€ndige Charakterisierung von planaren Inzidenzgraphen von Hypergraphen angegeben, die eine planare Zeichnung im BUS Modell besitzen, und diverse planare BUS-Varianten mit festen Knotenpositionen werden diskutiert. Zum Schluss wird erstmals eine Punktmenge von subquadratischer GröĂe angegeben, die eine planare Einbettung (Knoten werden auf Punkte abgebildet) von 2-auĂenplanaren Graphen ermöglicht
A new algorithm for recognizing the unknot
The topological underpinnings are presented for a new algorithm which answers
the question: `Is a given knot the unknot?' The algorithm uses the braid
foliation technology of Bennequin and of Birman and Menasco. The approach is to
consider the knot as a closed braid, and to use the fact that a knot is
unknotted if and only if it is the boundary of a disc with a combinatorial
foliation. The main problems which are solved in this paper are: how to
systematically enumerate combinatorial braid foliations of a disc; how to
verify whether a combinatorial foliation can be realized by an embedded disc;
how to find a word in the the braid group whose conjugacy class represents the
boundary of the embedded disc; how to check whether the given knot is isotopic
to one of the enumerated examples; and finally, how to know when we can stop
checking and be sure that our example is not the unknot.Comment: 46 pages. Published copy, also available at
http://www.maths.warwick.ac.uk/gt/GTVol2/paper9.abs.htm
- âŠ