43 research outputs found

    On the geometric dilation of closed curves, graphs, and point sets

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    The detour between two points u and v (on edges or vertices) of an embedded planar graph whose edges are curves is the ratio between the shortest path in in the graph between u and v and their Euclidean distance. The maximum detour over all pairs of points is called the geometric dilation. Ebbers-Baumann, Gruene and Klein have shown that every finite point set is contained in a planar graph whose geometric dilation is at most 1.678, and some point sets require graphs with dilation at least pi/2 = 1.57... We prove a stronger lower bound of 1.00000000001*pi/2 by relating graphs with small dilation to a problem of packing and covering the plane by circular disks. The proof relies on halving pairs, pairs of points dividing a given closed curve C in two parts of equal length, and their minimum and maximum distances h and H. Additionally, we analyze curves of constant halving distance (h=H), examine the relation of h to other geometric quantities and prove some new dilation bounds.Comment: 31 pages, 16 figures. The new version is the extended journal submission; it includes additional material from a conference submission (ref. [6] in the paper

    Geometric Dilation and Halving Distance

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    Let us consider the network of streets of a city represented by a geometric graph G in the plane. The vertices of G represent the crossroads and the edges represent the streets. The latter do not have to be straight line segments, they may be curved. If one wants to drive from a place p to some other place q, normally the length of the shortest path along streets, d_G(p,q), is bigger than the airline distance (Euclidean distance) |pq|. The (relative) DETOUR is defined as delta_G(p,q) := d_G(p,q)/|pq|. The supremum of all these ratios is called the GEOMETRIC DILATION of G. It measures the quality of the network. A small dilation value guarantees that there is no bigger detour between any two points. Given a finite point set S, we would like to know the smallest possible dilation of any graph that contains the given points on its edges. We call this infimum the DILATION of S and denote it by delta(S). The main results of this thesis are - a general upper bound to the dilation of any finite point set S, delta(S) - a lower bound for a specific set P, delta(P)>(1+10^(-11))pi/2, which approximately equals 1.571 In order to achieve these results, we first consider closed curves. Their dilation depends on the HALVING PAIRS, pairs of points which divide the closed curve in two parts of equal length. In particular the distance between the two points is essential, the HALVING DISTANCE. A transformation technique based on halving pairs, the HALVING PAIR TRANSFORMATION, and the curve formed by the midpoints of the halving pairs, the MIDPOINT CURVE, help us to derive lower bounds to dilation. For constructing graphs of small dilation, we use ZINDLER CURVES. These are closed curves of constant halving distance. To give a structured overview, the mathematical apparatus for deriving the main results of this thesis includes - upper bound: * the construction of certain Zindler curves to generate a periodic graph of small dilation * an embedding argument based on a number theoretical result by Dirichlet - lower bound: * the formulation and analysis of the halving pair transformation * a stability result for the dilation of closed curves based on this transformation and the midpoint curve * the application of a disk-packing result In addition, this thesis contains - a detailed analysis of the dilation of closed curves - a collection of inequalities, which relate halving distance to other important quantities from convex geometry, and their proofs; including four new inequalities - the rediscovery of Zindler curves and a compact presentation of their properties - a proof of the applied disk packing result.Geometrische Dilation und Halbierungsabstand Man kann das von den Straßen einer Stadt gebildete Netzwerk durch einen geometrischen Graphen in der Ebene darstellen. Die Knoten dieses Graphen repräsentieren die Kreuzungen und die Kanten sind die Straßen. Letztere müssen nicht geradlinig sein, sondern können beliebig gekrümmt sein. Wenn man nun von einem Ort p zu einem anderen Ort q fahren möchte, dann ist normalerweise die Länge des kürzesten Pfades über Straßen, d_G(p,q), länger als der Luftlinienabstand (euklidischer Abstand) |pq|. Der (relative) UMWEG (DETOUR) ist definiert als delta_G(p,q) := d_G(p,q)/|pq|. Das Supremum all dieser Brüche wird GEOMETRISCHE DILATION (GEOMETRIC DILATION) von G genannt. Es ist ein Maß für die Qualität des Straßennetzes. Ein kleiner Dilationswert garantiert, dass es keinen größeren Umweg zwischen beliebigen zwei Punkten gibt. Für eine gegebene endliche Punktmenge S würden wir nun gerne bestimmen, was der kleinste Dilationswert ist, den wir mit einem Graphen erreichen können, der die gegebenen Punkte auf seinen Kanten enthält. Dieses Infimum nennen wir die DILATION von S und schreiben kurz delta(S). Die Haupt-Ergebnisse dieser Arbeit sind - eine allgemeine obere Schranke für die Dilation jeder beliebigen endlichen Punktmenge S: delta(S) - eine untere Schranke für eine bestimmte Menge P: delta(P)>(1+10^(-11))pi/2, was ungefähr der Zahl 1.571 entspricht Um diese Ergebnisse zu erreichen, betrachten wir zunächst geschlossene Kurven. Ihre Dilation hängt von sogenannten HALBIERUNGSPAAREN (HALVING PAIRS) ab. Das sind Punktpaare, die die geschlossene Kurve in zwei Teile gleicher Länge teilen. Besonders der Abstand der beiden Punkte ist von Bedeutung, der HALBIERUNGSABSTAND (HALVING DISTANCE). Eine auf den Halbierungspaaren aufbauende Transformation, die HALBIERUNGSPAARTRANSFORMATION (HALVING PAIR TRANSFORMATION), und die von den Mittelpunkten der Halbierungspaare gebildete Kurve, die MITTELPUNKTKURVE (MIDPOINT CURVE), helfen uns untere Dilationsschranken herzuleiten. Zur Konstruktion von Graphen mit kleiner Dilation benutzen wir ZINDLERKURVEN (ZINDLER CURVES). Dies sind geschlossene Kurven mit konstantem Halbierungspaarabstand. Die mathematischen Hilfsmittel, mit deren Hilfe wir schließlich die Hauptresultate beweisen, sind unter anderem - obere Schranke: * die Konstruktion von bestimmten Zindlerkurven, mit denen periodische Graphen kleiner Dilation gebildet werden können * ein Einbettungsargument, das einen zahlentheoretischen Satz von Dirichlet benutzt - untere Schranke: * die Definition und Analyse der Halbierungspaartransformation * ein Stabilitätsresultat für die Dilation geschlossener Kurven, das auf dieser Transformation und der Mittelpunktkurve basiert * die Anwendung eines Kreispackungssatzes Zusätzlich enthält diese Dissertation - eine detaillierte Analyse der Dilation geschlossener Kurven - eine Sammlung von Ungleichungen, die den Halbierungsabstand zu anderen wichtigen Größen der Konvexgeometrie in Beziehung setzen, und ihre Beweise; inklusive vier neuer Ungleichungen - die Wiederentdeckung von Zindlerkurven und eine kompakte Darstellung ihrer Eigenschaften - einen Beweis des angewendeten Kreispackungssatzes

    Zindler-type hypersurfaces in R^4

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    In this paper the definition of Zindler-type hypersurfaces is introduced in R4\mathbb{R}^4 as a generalization of planar Zindler curves. After recalling some properties of planar Zindler curves, it is shown that Zindler hypersurfaces satisfy similar properties. Techniques from quaternions and symplectic geometry are used. Moreover, each Zindler hypersurface is fibrated by space Zindler curves that correspond, in the convex case, to some space curves of constant width lying on the associated hypersurface of constant width and with the same symplectic area

    Algorithmic and Combinatorial Results in Selection and Computational Geometry

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    This dissertation investigates two sets of algorithmic and combinatorial problems. Thefirst part focuses on the selection problem under the pairwise comparison model. For the classic “median of medians” scheme, contrary to the popular belief that smaller group sizes cause superlinear behavior, several new linear time algorithms that utilize small groups are introduced. Then the exact number of comparisons needed for an optimal selection algorithm is studied. In particular, the implications of a long standing conjecture known as Yao’s hypothesis are explored. For the multiparty model, we designed low communication complexity protocols for selecting an exact or an approximate median of data that is distributed among multiple players. In the second part, three computational geometry problems are studied. For the longestspanning tree with neighborhoods, approximation algorithms are provided. For the stretch factor of polygonal chains, upper bounds are proved and almost matching lower bound constructions in \mathbb{R}^2 and higher dimensions are developed. For the piercing number τ and independence number ν of a family of axis-parallel rectangles in the plane, a lower bound construction for ν = 4 that matches Wegner’s conjecture is analyzed. The previous matching construction for ν = 3, due to Wegner himself, dates back to 1968

    Dilation, Transport, Visibility and Fault-Tolerant Algorithms

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    Connecting some points in the plane by a road network is equivalent to constructing a finite planar graph G whose vertex set contains a predefined set of vertices (i. e., the possible destinations in the road network). The dilation between two vertices p and q of graph G is defined as the Euclidean length of a shortest path in G from p to q, divided by the Euclidean distance from p to q. That is, given a point set P, the goal is to place some additional crossing vertices C such that there exists a planar graph G = (P ∪ C, E) whose dilation is small. Here, the dilation of G is defined as the maximum dilation between two vertices in G. We show that, except for some special point sets P, there is a lower bound Δ(P) > 1, depending on P, on the dilation of any finite graph containing P in its vertex set. The transportation problem is the problem of finding a transportation plan that minimizes the total transport cost. We are given a set of suppliers, and each supplier produces a fixed amount of some commodity, say, bread. Furthermore, there is a set of customers, and each customer has some demand of bread, such that the total demand equals the amount of bread the suppliers produce. The task is to assign each unit of bread produced to some customer, such that the total transportation cost becomes a minimum. A first idea is to assign each unit of bread to the client to which the transport cost of this unit is minimal. Clearly, this gives rise to a transportation plan which minimizes the total transportation cost. However, it is likely that not every customer will obtain the required amount of bread. Therefore, we need to use a different algorithm for distributing the supplier's bread. We show that if the bread produced by the suppliers is given by a continuous probability density function and the set of customers is discrete, then every optimal transport plan can be characterized by a unique additively weighted Voronoi diagram for the customers. When managing the construction process of a building by a digital model of the building, it is necessary to compute essential parts between walls of the building. Given two walls A and B, the essential part between A and B is the set of line segments s where one endpoint belongs to A, the other endpoint belongs to B, and s does not intersect A or B. We give an algorithm that computes, in linear time, the essential parts between A and B. Our algorithm is based on computing the visibility polygon of A and of B, and two shortest paths connecting points of A with points of B. We conclude the thesis by giving fault-tolerant algorithms for some fundamental geometric problems. We assume that a basic primitive operation used by an algorithm fails with some small probability p. Depending on the results of the primitive operations, it is possible that the algorithm will not work correctly. For example, one faulty comparison when executing a sorting algorithm can result in some numbers being placed far away from their true positions. An algorithm is called tolerant, if with high probability a good answer is given, if the error probability p is small. We provide tolerant algorithms that find the maximum of n numbers, search for a key in a sorted sequence of n keys, sort a set of n numbers, and solve Linear Programming in R2

    Retinal vessel analysis:flicker reproducibility, methodological standardisations and practical limitations

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    The Retinal Vessel Analyser (RVA) is a commercially available ophthalmoscopic instrument capable of acquiring vessel diameter fluctuations in real time and in high temporal resolution. Visual stimulation by means of flickering light is a unique exploration tool of neurovascular coupling in the human retina. Vessel reactivity as mediated by local vascular endothelial vasodilators and vasoconstrictors can be assessed non-invasively, in vivo. In brief, the work in this thesis • deals with interobserver and intraobserver reproducibility of the flicker responses in healthy volunteers • explains the superiority of individually analysed reactivity parameters over vendorgenerated output • links in static retinal measures with dynamic ones • highlights practical limitations in the use of the RVA that may undermine its clinical usefulness • provides recommendations for standardising measurements in terms of vessel location and vessel segment length and • presents three case reports of essential hypertensives in a -year follow-up. Strict standardisation of measurement procedures is a necessity when utilising the RVA system. Agreement between research groups on implemented protocols needs to be met, before it could be considered a clinically useful tool in detecting or predicting microvascular dysfunction

    Complex-tone pitch representations in the human auditory system.

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    The hyperboloid model of hyperbolic geometry

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    The main goal of this thesis is to introduce and develop the hyperboloid model of Hyperbolic Geometry. In order to do that, some time is spent on Neutral Geometry as well as Euclidean Geometry; these are used to build several models of Hyperbolic Geometry. At this point the hyperboloid model is introduced, related to the other models visited, and developed using some concepts from physics as aids. After the development of the hyperboloid model, Fuchsian groups are briefly discussed and the more familiar models of Hyperbolic Geometry are further investigated --Document
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