327 research outputs found
How to Walk Your Dog in the Mountains with No Magic Leash
We describe a -approximation algorithm for computing the
homotopic \Frechet distance between two polygonal curves that lie on the
boundary of a triangulated topological disk. Prior to this work, algorithms
were known only for curves on the Euclidean plane with polygonal obstacles.
A key technical ingredient in our analysis is a -approximation
algorithm for computing the minimum height of a homotopy between two curves. No
algorithms were previously known for approximating this parameter.
Surprisingly, it is not even known if computing either the homotopic \Frechet
distance, or the minimum height of a homotopy, is in NP
Meshing Deforming Spacetime for Visualization and Analysis
We introduce a novel paradigm that simplifies the visualization and analysis
of data that have a spatially/temporally varying frame of reference. The
primary application driver is tokamak fusion plasma, where science variables
(e.g., density and temperature) are interpolated in a complex magnetic
field-line-following coordinate system. We also see a similar challenge in
rotational fluid mechanics, cosmology, and Lagrangian ocean analysis; such
physics implies a deforming spacetime and induces high complexity in volume
rendering, isosurfacing, and feature tracking, among various visualization
tasks. Without loss of generality, this paper proposes an algorithm to build a
simplicial complex -- a tetrahedral mesh, for the deforming 3D spacetime
derived from two 2D triangular meshes representing consecutive timesteps.
Without introducing new nodes, the resulting mesh fills the gap between 2D
meshes with tetrahedral cells while satisfying given constraints on how nodes
connect between the two input meshes. In the algorithm we first divide the
spacetime into smaller partitions to reduce complexity based on the input
geometries and constraints. We then independently search for a feasible
tessellation of each partition taking nonconvexity into consideration. We
demonstrate multiple use cases for a simplified visualization analysis scheme
with a synthetic case and fusion plasma applications
Maximum Planar Subgraphs and Nice Embeddings: Practical Layout Tools
In automatic graph drawing a given graph has to be layed-out in the plane, usually according to a number of topological and aesthetic constraints. Nice drawings for sparse nonplanar graphs can be achieved by determining a maximum planar subgraph and augmenting an embedding of this graph. This approach appears to be of limited value in practice, because the maximum planar subgraph problem is NP-hard. We attack the maximum planar subgraph problem with a branch-and-cut technique which gives us quite good and in many cases provably optimum solutions for sparse graphs and very dense graphs. In the theoretical part of the paper, the polytope of all planar subgraphs of a graph G is defined and studied. All subgraphs of a graph G, which are subdivisions of K5 or K3,3, turn out to define facets of this polytope. For cliques contained in G, the Euler inequalities turn out to be facet-defining for the planar subgraph polytope. Moreover we introduce the subdivision inequalities, V2k inequalities and flower inequalities all of which are facet-defining for the polytope. Furthermore, the composition of inequalities by 2-sums is investigated. We also present computational experience with a branch-and-cut algorithm for the above problem. Our approach is based on an algorithm which searches for forbidden substructures in a graph that contains a subdivision of K5 or K3,3. These structures give us inequalities which are used as cutting planes. Finally, we try to convince the reader that the computation of maximum planar subgraphs is indeed a practical tool for finding nice embeddings by applying this method to graphs taken from the literature
A simple MAX-CUT algorithm for planar graphs
The max-cut problem asks for partitioning the nodes V of a graph G=(V,E) into two sets (one of which might be empty), such that the sum of weights of edges joining nodes in different partitions is maximum. Whereas for general instances the max-cut problem is NP-hard, it is polynomially solvable for certain classes of graphs. For planar graphs, there exist several polynomial-time methods determining maximum cuts for arbitrary choice of edge weights. Typically, the problem is solved by computing a minimum-weight perfect matching in some associated graph. In this work, we present a new and simple algorithm for determining maximum cuts for arbitrary weighted planar graphs. Its running time can be bounded by O(|V|^(1.5)log|V|), similar to the fastest known methods. However, our transformation yields a much smaller associated graph than that of the known methods. Furthermore, it can be computed fast. As the practical running time strongly depends on the size of the associated graph, it can be expected that our algorithm is considerably faster than the methods known in the literature. More specifically, our program can determine maximum cuts in huge realistic and random planar graphs with up to 10^6 nodes
Recommended from our members
Geometric and Algebraic Combinatorics
The 2015 Oberwolfach meeting “Geometric and Algebraic Combinatorics” was organized by Gil Kalai (Jerusalem), Isabella Novik (Seattle), Francisco Santos (Santander), and Volkmar Welker (Marburg). It covered a wide variety of aspects of Discrete Geometry, Algebraic Combinatorics with geometric flavor, and Topological Combinatorics. Some of the highlights of the conference included (1) counterexamples to the topological Tverberg conjecture, and (2) the latest results around the Heron-Rota-Welsh conjecture
Recommended from our members
Geometric and Topological Combinatorics
The 2007 Oberwolfach meeting “Geometric and Topological Combinatorics” presented a great variety of investigations where topological and algebraic methods are brought into play to solve combinatorial and geometric problems, but also where geometric and combinatorial ideas are applied to topological questions
A simple MAX-CUT algorithm for planar graphs
The max-cut problem asks for partitioning the nodes V of a graph G=(V,E) into two sets (one of which might be empty), such that the sum of weights of edges joining nodes in different partitions is maximum. Whereas for general instances the max-cut problem is NP-hard, it is polynomially solvable for certain classes of graphs. For planar graphs, there exist several polynomial-time methods determining maximum cuts for arbitrary choice of edge weights. Typically, the problem is solved by computing a minimum-weight perfect matching in some associated graph. In this work, we present a new and simple algorithm for determining maximum cuts for arbitrary weighted planar graphs. Its running time can be bounded by O(|V|^(1.5)log|V|), similar to the fastest known methods. However, our transformation yields a much smaller associated graph than that of the known methods. Furthermore, it can be computed fast. As the practical running time strongly depends on the size of the associated graph, it can be expected that our algorithm is considerably faster than the methods known in the literature. More specifically, our program can determine maximum cuts in huge realistic and random planar graphs with up to 10^6 nodes
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