5,279 research outputs found
The Delaunay Hierarchy
International audienceWe propose a new data structure to compute the Delaunay triangulation of a set of points in the plane. It combines good worst case complexity, fast behavior on real data, small memory occupation and the possibility of fully dynamic insertions and deletions. The location structure is organized into several levels. The lowest level just consists of the triangulation, then each level contains the triangulation of a small sample of the level below. Point location is done by walking in a triangulation to determine the nearest neighbor of the query at that level, then the walk restarts from that neighbor at the level below. Using a small subset (3%) to sample a level allows a small memory occupation; the walk and the use of the nearest neighbor to change levels quickly locate the query
A Fast Algorithm for Well-Spaced Points and Approximate Delaunay Graphs
We present a new algorithm that produces a well-spaced superset of points
conforming to a given input set in any dimension with guaranteed optimal output
size. We also provide an approximate Delaunay graph on the output points. Our
algorithm runs in expected time , where is the
input size, is the output point set size, and is the ambient dimension.
The constants only depend on the desired element quality bounds.
To gain this new efficiency, the algorithm approximately maintains the
Voronoi diagram of the current set of points by storing a superset of the
Delaunay neighbors of each point. By retaining quality of the Voronoi diagram
and avoiding the storage of the full Voronoi diagram, a simple exponential
dependence on is obtained in the running time. Thus, if one only wants the
approximate neighbors structure of a refined Delaunay mesh conforming to a set
of input points, the algorithm will return a size graph in
expected time. If is superlinear in , then we
can produce a hierarchically well-spaced superset of size in
expected time.Comment: Full versio
Generation of Vorticity and Velocity Dispersion by Orbit Crossing
We study the generation of vorticity and velocity dispersion by orbit
crossing using cosmological numerical simulations, and calculate the
backreaction of these effects on the evolution of large-scale density and
velocity divergence power spectra. We use Delaunay tessellations to define the
velocity field, showing that the power spectra of velocity divergence and
vorticity measured in this way are unbiased and have better noise properties
than for standard interpolation methods that deal with mass weighted
velocities. We show that high resolution simulations are required to recover
the correct large-scale vorticity power spectrum, while poor resolution can
spuriously amplify its amplitude by more than one order of magnitude. We
measure the scalar and vector modes of the stress tensor induced by orbit
crossing using an adaptive technique, showing that its vector modes lead, when
input into the vorticity evolution equation, to the same vorticity power
spectrum obtained from the Delaunay method. We incorporate orbit crossing
corrections to the evolution of large scale density and velocity fields in
perturbation theory by using the measured stress tensor modes. We find that at
large scales (k~0.1 h/Mpc) vector modes have very little effect in the density
power spectrum, while scalar modes (velocity dispersion) can induce percent
level corrections at z=0, particularly in the velocity divergence power
spectrum. In addition, we show that the velocity power spectrum is smaller than
predicted by linear theory until well into the nonlinear regime, with little
contribution from virial velocities.Comment: 27 pages, 14 figures. v2: reorganization of the material, new
appendix. Accepted by PR
Improved Incremental Randomized Delaunay Triangulation
We propose a new data structure to compute the Delaunay triangulation of a
set of points in the plane. It combines good worst case complexity, fast
behavior on real data, and small memory occupation.
The location structure is organized into several levels. The lowest level
just consists of the triangulation, then each level contains the triangulation
of a small sample of the levels below. Point location is done by marching in a
triangulation to determine the nearest neighbor of the query at that level,
then the march restarts from that neighbor at the level below. Using a small
sample (3%) allows a small memory occupation; the march and the use of the
nearest neighbor to change levels quickly locate the query.Comment: 19 pages, 7 figures Proc. 14th Annu. ACM Sympos. Comput. Geom.,
106--115, 199
Essential Constraints of Edge-Constrained Proximity Graphs
Given a plane forest of points, we find the minimum
set of edges such that the edge-constrained minimum spanning
tree over the set of vertices and the set of constraints contains .
We present an -time algorithm that solves this problem. We
generalize this to other proximity graphs in the constraint setting, such as
the relative neighbourhood graph, Gabriel graph, -skeleton and Delaunay
triangulation. We present an algorithm that identifies the minimum set
of edges of a given plane graph such that for , where is the
constraint -skeleton over the set of vertices and the set of
constraints. The running time of our algorithm is , provided that the
constrained Delaunay triangulation of is given.Comment: 24 pages, 22 figures. A preliminary version of this paper appeared in
the Proceedings of 27th International Workshop, IWOCA 2016, Helsinki,
Finland. It was published by Springer in the Lecture Notes in Computer
Science (LNCS) serie
A Cosmic Watershed: the WVF Void Detection Technique
On megaparsec scales the Universe is permeated by an intricate filigree of
clusters, filaments, sheets and voids, the Cosmic Web. For the understanding of
its dynamical and hierarchical history it is crucial to identify objectively
its complex morphological components. One of the most characteristic aspects is
that of the dominant underdense Voids, the product of a hierarchical process
driven by the collapse of minor voids in addition to the merging of large ones.
In this study we present an objective void finder technique which involves a
minimum of assumptions about the scale, structure and shape of voids. Our void
finding method, the Watershed Void Finder (WVF), is based upon the Watershed
Transform, a well-known technique for the segmentation of images. Importantly,
the technique has the potential to trace the existing manifestations of a void
hierarchy. The basic watershed transform is augmented by a variety of
correction procedures to remove spurious structure resulting from sampling
noise. This study contains a detailed description of the WVF. We demonstrate
how it is able to trace and identify, relatively parameter free, voids and
their surrounding (filamentary and planar) boundaries. We test the technique on
a set of Kinematic Voronoi models, heuristic spatial models for a cellular
distribution of matter. Comparison of the WVF segmentations of low noise and
high noise Voronoi models with the quantitatively known spatial characteristics
of the intrinsic Voronoi tessellation shows that the size and shape of the
voids are succesfully retrieved. WVF manages to even reproduce the full void
size distribution function.Comment: 24 pages, 15 figures, MNRAS accepted, for full resolution, see
http://www.astro.rug.nl/~weygaert/tim1publication/watershed.pd
Adaptive, Anisotropic and Hierarchical cones of Discrete Convex functions
We address the discretization of optimization problems posed on the cone of
convex functions, motivated in particular by the principal agent problem in
economics, which models the impact of monopoly on product quality. Consider a
two dimensional domain, sampled on a grid of N points. We show that the cone of
restrictions to the grid of convex functions is in general characterized by N^2
linear inequalities; a direct computational use of this description therefore
has a prohibitive complexity. We thus introduce a hierarchy of sub-cones of
discrete convex functions, associated to stencils which can be adaptively,
locally, and anisotropically refined. Numerical experiments optimize the
accuracy/complexity tradeoff through the use of a-posteriori stencil refinement
strategies.Comment: 35 pages, 11 figures. (Second version fixes a small bug in Lemma 3.2.
Modifications are anecdotic.
The Multiscale Morphology Filter: Identifying and Extracting Spatial Patterns in the Galaxy Distribution
We present here a new method, MMF, for automatically segmenting cosmic
structure into its basic components: clusters, filaments, and walls.
Importantly, the segmentation is scale independent, so all structures are
identified without prejudice as to their size or shape. The method is ideally
suited for extracting catalogues of clusters, walls, and filaments from samples
of galaxies in redshift surveys or from particles in cosmological N-body
simulations: it makes no prior assumptions about the scale or shape of the
structures.}Comment: Replacement with higher resolution figures. 28 pages, 17 figures. For
Full Resolution Version see:
http://www.astro.rug.nl/~weygaert/tim1publication/miguelmmf.pd
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