3,610 research outputs found

    On Visibility Representations of Non-planar Graphs

    Get PDF
    A rectangle visibility representation (RVR) of a graph consists of an assignment of axis-aligned rectangles to vertices such that for every edge there exists a horizontal or vertical line of sight between the rectangles assigned to its endpoints. Testing whether a graph has an RVR is known to be NP-hard. In this paper, we study the problem of finding an RVR under the assumption that an embedding in the plane of the input graph is fixed and we are looking for an RVR that reflects this embedding. We show that in this case the problem can be solved in polynomial time for general embedded graphs and in linear time for 1-plane graphs (i.e., embedded graphs having at most one crossing per edge). The linear time algorithm uses a precise list of forbidden configurations, which extends the set known for straight-line drawings of 1-plane graphs. These forbidden configurations can be tested for in linear time, and so in linear time we can test whether a 1-plane graph has an RVR and either compute such a representation or report a negative witness. Finally, we discuss some extensions of our study to the case when the embedding is not fixed but the RVR can have at most one crossing per edge

    Witness (Delaunay) Graphs

    Get PDF
    Proximity graphs are used in several areas in which a neighborliness relationship for input data sets is a useful tool in their analysis, and have also received substantial attention from the graph drawing community, as they are a natural way of implicitly representing graphs. However, as a tool for graph representation, proximity graphs have some limitations that may be overcome with suitable generalizations. We introduce a generalization, witness graphs, that encompasses both the goal of more power and flexibility for graph drawing issues and a wider spectrum for neighborhood analysis. We study in detail two concrete examples, both related to Delaunay graphs, and consider as well some problems on stabbing geometric objects and point set discrimination, that can be naturally described in terms of witness graphs.Comment: 27 pages. JCCGG 200

    Witness Gabriel Graphs

    Get PDF
    We consider a generalization of the Gabriel graph, the witness Gabriel graph. Given a set of vertices P and a set of witnesses W in the plane, there is an edge ab between two points of P in the witness Gabriel graph GG-(P,W) if and only if the closed disk with diameter ab does not contain any witness point (besides possibly a and/or b). We study several properties of the witness Gabriel graph, both as a proximity graph and as a new tool in graph drawing.Comment: 23 pages. EuroCG 200

    Who witnesses The Witness? Finding witnesses in The Witness is hard and sometimes impossible

    Full text link
    We analyze the computational complexity of the many types of pencil-and-paper-style puzzles featured in the 2016 puzzle video game The Witness. In all puzzles, the goal is to draw a simple path in a rectangular grid graph from a start vertex to a destination vertex. The different puzzle types place different constraints on the path: preventing some edges from being visited (broken edges); forcing some edges or vertices to be visited (hexagons); forcing some cells to have certain numbers of incident path edges (triangles); or forcing the regions formed by the path to be partially monochromatic (squares), have exactly two special cells (stars), or be singly covered by given shapes (polyominoes) and/or negatively counting shapes (antipolyominoes). We show that any one of these clue types (except the first) is enough to make path finding NP-complete ("witnesses exist but are hard to find"), even for rectangular boards. Furthermore, we show that a final clue type (antibody), which necessarily "cancels" the effect of another clue in the same region, makes path finding Σ2\Sigma_2-complete ("witnesses do not exist"), even with a single antibody (combined with many anti/polyominoes), and the problem gets no harder with many antibodies. On the positive side, we give a polynomial-time algorithm for monomino clues, by reducing to hexagon clues on the boundary of the puzzle, even in the presence of broken edges, and solving "subset Hamiltonian path" for terminals on the boundary of an embedded planar graph in polynomial time.Comment: 72 pages, 59 figures. Revised proof of Lemma 3.5. A short version of this paper appeared at the 9th International Conference on Fun with Algorithms (FUN 2018

    New Classes of Distributed Time Complexity

    Full text link
    A number of recent papers -- e.g. Brandt et al. (STOC 2016), Chang et al. (FOCS 2016), Ghaffari & Su (SODA 2017), Brandt et al. (PODC 2017), and Chang & Pettie (FOCS 2017) -- have advanced our understanding of one of the most fundamental questions in theory of distributed computing: what are the possible time complexity classes of LCL problems in the LOCAL model? In essence, we have a graph problem Π\Pi in which a solution can be verified by checking all radius-O(1)O(1) neighbourhoods, and the question is what is the smallest TT such that a solution can be computed so that each node chooses its own output based on its radius-TT neighbourhood. Here TT is the distributed time complexity of Π\Pi. The time complexity classes for deterministic algorithms in bounded-degree graphs that are known to exist by prior work are Θ(1)\Theta(1), Θ(logn)\Theta(\log^* n), Θ(logn)\Theta(\log n), Θ(n1/k)\Theta(n^{1/k}), and Θ(n)\Theta(n). It is also known that there are two gaps: one between ω(1)\omega(1) and o(loglogn)o(\log \log^* n), and another between ω(logn)\omega(\log^* n) and o(logn)o(\log n). It has been conjectured that many more gaps exist, and that the overall time hierarchy is relatively simple -- indeed, this is known to be the case in restricted graph families such as cycles and grids. We show that the picture is much more diverse than previously expected. We present a general technique for engineering LCL problems with numerous different deterministic time complexities, including Θ(logαn)\Theta(\log^{\alpha}n) for any α1\alpha\ge1, 2Θ(logαn)2^{\Theta(\log^{\alpha}n)} for any α1\alpha\le 1, and Θ(nα)\Theta(n^{\alpha}) for any α<1/2\alpha <1/2 in the high end of the complexity spectrum, and Θ(logαlogn)\Theta(\log^{\alpha}\log^* n) for any α1\alpha\ge 1, 2Θ(logαlogn)\smash{2^{\Theta(\log^{\alpha}\log^* n)}} for any α1\alpha\le 1, and Θ((logn)α)\Theta((\log^* n)^{\alpha}) for any α1\alpha \le 1 in the low end; here α\alpha is a positive rational number

    Triangle-free intersection graphs of line segments with large chromatic number

    Full text link
    In the 1970s, Erdos asked whether the chromatic number of intersection graphs of line segments in the plane is bounded by a function of their clique number. We show the answer is no. Specifically, for each positive integer kk, we construct a triangle-free family of line segments in the plane with chromatic number greater than kk. Our construction disproves a conjecture of Scott that graphs excluding induced subdivisions of any fixed graph have chromatic number bounded by a function of their clique number.Comment: Small corrections, bibliography updat

    Piercing axis-parallel boxes

    Get PDF
    Let \F be a finite family of axis-parallel boxes in Rd\R^d such that \F contains no k+1k+1 pairwise disjoint boxes. We prove that if \F contains a subfamily \M of kk pairwise disjoint boxes with the property that for every F\in \F and M\in \M with FMF \cap M \neq \emptyset, either FF contains a corner of MM or MM contains 2d12^{d-1} corners of FF, then \F can be pierced by O(k)O(k) points. One consequence of this result is that if d=2d=2 and the ratio between any of the side lengths of any box is bounded by a constant, then \F can be pierced by O(k)O(k) points. We further show that if for each two intersecting boxes in \F a corner of one is contained in the other, then \F can be pierced by at most O(kloglog(k))O(k\log\log(k)) points, and in the special case where \F contains only cubes this bound improves to O(k)O(k)
    corecore