Results 11  20
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28
Geodesic Embeddings and Planar Graphs
, 2002
"... Schnyder labelings are known to have close links to order dimension and drawings of planar graphs. It was observed by Ezra Miller that geodesic embeddings of planar graphs are another class of combinatorial or geometric objects closely linked to Schnyder labelings. We aim to contribute to a better u ..."
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Cited by 9 (6 self)
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Schnyder labelings are known to have close links to order dimension and drawings of planar graphs. It was observed by Ezra Miller that geodesic embeddings of planar graphs are another class of combinatorial or geometric objects closely linked to Schnyder labelings. We aim to contribute to a better understanding of the connections between these objects. In this article we prove a characterization of 3connected planar graphs as those graphs admitting rigid geodesic embeddings, a bijection between Schnyder labelings and rigid geodesic embeddings, a strong version of the BrightwellTrotter theorem.
Schnyder woods and orthogonal surfaces
 In Proceedings of Graph Drawing
, 2006
"... In this paper we study connections between planar graphs, Schnyder woods, and orthogonal surfaces. Schnyder woods and the face counting approach have important applications in graph drawing and the dimension theory of orders. Orthogonal surfaces explain connections between these seemingly unrelated ..."
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Cited by 7 (3 self)
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In this paper we study connections between planar graphs, Schnyder woods, and orthogonal surfaces. Schnyder woods and the face counting approach have important applications in graph drawing and the dimension theory of orders. Orthogonal surfaces explain connections between these seemingly unrelated notions. We use these connections for an intuitive proof of the BrightwellTrotter Theorem which says, that the face lattice of a 3polytope minus one face has order dimension three. Our proof yields a linear time algorithm for the construction of the three linear orders that realize the face lattice. Coplanar orthogonal surfaces are in correspondence with a large class of convex straight line drawings of 3connected planar graphs. We show that Schnyder’s face counting approach with weighted faces can be used to construct all coplanar orthogonal surfaces and hence the corresponding drawings. Appropriate weights are computable in linear time. 1
Adjacency posets of planar graphs
 DISCRETE MATH
"... In this paper, we show that the dimension of the adjacency poset of a planar graph is at most 8. From below, we show that there is a planar graph whose adjacency poset has dimension 5. We then show that the dimension of the adjacency poset of an outerplanar graph is at most 5. From below, we show t ..."
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Cited by 4 (3 self)
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In this paper, we show that the dimension of the adjacency poset of a planar graph is at most 8. From below, we show that there is a planar graph whose adjacency poset has dimension 5. We then show that the dimension of the adjacency poset of an outerplanar graph is at most 5. From below, we show that there is an outerplanar graph whose adjacency poset has dimension 4. We also show that the dimension of the adjacency poset of a planar bipartite graph is at most 4. This result is best possible. More generally, the dimension of the adjacency poset of a graph is bounded as a function of its genus and so is the dimension of the vertexface poset of such a graph.
Schnyder Woods for Higher Genus Triangulated Surfaces
 SCG'08
, 2008
"... Schnyder woods are a well known combinatorial structure for planar graphs, which yields a decomposition into 3 vertexspanning trees. Our goal is to extend definitions and algorithms for Schnyder woods designed for planar graphs (corresponding to combinatorial surfaces with the topology of the sphere ..."
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Cited by 4 (2 self)
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Schnyder woods are a well known combinatorial structure for planar graphs, which yields a decomposition into 3 vertexspanning trees. Our goal is to extend definitions and algorithms for Schnyder woods designed for planar graphs (corresponding to combinatorial surfaces with the topology of the sphere, i.e., of genus 0) to the more general case of graphs embedded on surfaces of arbitrary genus. First, we define a new traversal order of the vertices of a triangulated surface of genus g together with an orientation and coloration of the edges that extends the one proposed by Schnyder for the planar case. As a byproduct we show how some recent schemes for compression and compact encoding of graphs can be extended to higher genus. All the algorithms presented here have linear time complexity.
Empty Rectangles and Graph Dimension
, 2006
"... Abstract We consider rectangle graphs whose edges are defined by pairs of points in diagonally opposite corners of empty axisaligned rectangles. The maximum number of edges of such a graph on n points is shown to be ⌊ 1 4 n2 + n − 2⌋. This number also has other interpretations: • It is the maximum ..."
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Cited by 3 (2 self)
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Abstract We consider rectangle graphs whose edges are defined by pairs of points in diagonally opposite corners of empty axisaligned rectangles. The maximum number of edges of such a graph on n points is shown to be ⌊ 1 4 n2 + n − 2⌋. This number also has other interpretations: • It is the maximum number of edges of a graph of dimension [3 ↕↕4], i.e., of a graph with a realizer of the form π1, π2, π1, π2. • It is the number of 1faces in a special Scarf complex. The last of these interpretations allows to deduce the maximum number of empty axisaligned rectangles spanned by 4element subsets of a set of n points. Moreover, it follows that the extremal point sets for the two problems coincide. We investigate the maximum number of of edges of a graph of dimension [3 ↕ 4], i.e., of a graph with a realizer of the form π1, π2, π3, π3. This maximum is shown to be 1 4 n2 + O(n). Box graphs are defined as the 3dimensional analog of rectangle graphs. The maximum number of edges of such a graph on n points is shown to be 7 16 n2 + o(n 2). Mathematics Subject Classifications (2000). 05C10, 68R10, 06A07. 1
SCHNYDER DECOMPOSITIONS FOR REGULAR PLANE GRAPHS AND APPLICATION TO DRAWING
"... Abstract. Schnyder woods are decompositions of simple triangulations into three edgedisjoint spanning trees crossing each other in a specific way. In this article, we define a generalization of Schnyder woods to dangulations (plane graphs with faces of degree d) for all d ≥ 3. A Schnyder decomposi ..."
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Cited by 3 (2 self)
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Abstract. Schnyder woods are decompositions of simple triangulations into three edgedisjoint spanning trees crossing each other in a specific way. In this article, we define a generalization of Schnyder woods to dangulations (plane graphs with faces of degree d) for all d ≥ 3. A Schnyder decomposition is a set of d spanning forests crossing each other in a specific way, and such that each internal edge is part of exactly d − 2 of the spanning forests. We show that a Schnyder decomposition exists if and only if the girth of the dangulation is d. As in the case of Schnyder woods (d = 3), there are alternative formulationsintermsoforientations (“fractional ” orientations when d ≥ 5)and in terms of cornerlabellings. Moreover, the set of Schnyder decompositions on a fixed dangulation of girth d is a distributive lattice. We also show that the structures dual to Schnyder decompositions (on dregular plane graphs of mincut d rooted at a vertex v ∗ ) are decompositions into d spanning trees rooted atv ∗ such that each edge not incidentto v ∗ isused in opposite directions by two trees. Additionally, for even values of d, we show that a subclass of Schnyder decompositions, which are called even, enjoy additional properties that yield a reduced formulation; in the case d = 4, these correspond to wellstudied structures on simple quadrangulations (2orientations and partitions into 2 spanning trees). In the case d = 4, the dual of even Schnyder decompositions yields (planar) orthogonal and straightline drawing algorithms. For a 4regular plane graph G of mincut 4 with n vertices plus a marked vertex v, the vertices of G\v are placed on a (n−1)×(n−1) grid according to a permutation pattern, and in the orthogonal drawing each of the 2n−2 edges of G\v has exactly one bend. Embedding also the marked vertex v is doable at the cost of two additional rows and columns and 8 additional bends for the 4 edges incident to v. We propose a further compaction step for the drawing algorithm and show that the obtained gridsize is strongly concentrated around 25n/32 ×25n/32 for a uniformly random instance with n vertices. 1.
On the number of planar orientations with prescribed degrees
, 2008
"... We deal with the asymptotic enumeration of combinatorial structures on planar maps. Prominent instances of such problems are the enumeration of spanning trees, bipartite perfect matchings, and ice models. The notion of orientations with outdegrees prescribed by a function α: V → N unifies many diffe ..."
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Cited by 3 (2 self)
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We deal with the asymptotic enumeration of combinatorial structures on planar maps. Prominent instances of such problems are the enumeration of spanning trees, bipartite perfect matchings, and ice models. The notion of orientations with outdegrees prescribed by a function α: V → N unifies many different combinatorial structures, including the afore mentioned. We call these orientations αorientations. The main focus of this paper are bounds for the maximum number of αorientations that a planar map with n vertices can have, for different instances of α. We give examples of triangulations with 2.37 n Schnyder woods, 3connected planar maps with 3.209 n Schnyder woods and inner triangulations with 2.91 n bipolar orientations. These lower bounds are accompanied by upper bounds of 3.56 n, 8 n and 3.97 n respectively. We also show that for any planar map M and any α the number of αorientations is bounded from above by 3.73 n and describe a family of maps which have at least 2.598 n αorientations.
Orthogonal Surfaces and their CPorders
, 2007
"... Orthogonal surfaces are nice mathematical objects which have interesting connections to various fields, e.g., integer programming, monomial ideals and order dimension. While orthogonal surfaces in one or two dimensions are rather trivial already the three dimensional case has a rich structure with c ..."
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Cited by 2 (2 self)
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Orthogonal surfaces are nice mathematical objects which have interesting connections to various fields, e.g., integer programming, monomial ideals and order dimension. While orthogonal surfaces in one or two dimensions are rather trivial already the three dimensional case has a rich structure with connections to Schnyder woods, planar graphs and 3polytopes. Our objective is to detect more of the structure of orthogonal surfaces in four and higher dimensions. In particular we are driven by the question which nongeneric orthogonal surfaces have a polytopal structure. We review the state of knowledge of the 3dimensional situation. On that basis we introduce terminology for higher dimensional orthogonal surfaces and continue with the study of characteristic points and the cporders of orthogonal surfaces, i.e., the dominance orders on the characteristic points. In the generic case these orders are (almost) face lattices of polytopes. Examples show that in general cporders can lack key properties of face lattices. We investigate extra requirements which may help to have cporders which are face lattices. Finally, we turn the focus and ask for the realizability of polytopes on orthogonal surfaces. There are criteria which prevent large classes of simplicial polytopes from being realizable. On the other hand we identify some families of polytopes which can be realized on orthogonal surfaces.
Regular Labelings and Geometric Structures
, 2010
"... Three types of geometric structure—grid triangulations, rectangular subdivisions, and orthogonal polyhedra— can each be described combinatorially by a regular labeling: an assignment of colors and orientations to the edges of an associated maximal or nearmaximal planar graph. We briefly survey the ..."
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Cited by 2 (1 self)
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Three types of geometric structure—grid triangulations, rectangular subdivisions, and orthogonal polyhedra— can each be described combinatorially by a regular labeling: an assignment of colors and orientations to the edges of an associated maximal or nearmaximal planar graph. We briefly survey the connections and analogies between these three kinds of labelings, and their uses in designing efficient geometric algorithms.