35 research outputs found
Multi-core computation of transfer matrices for strip lattices in the Potts model
The transfer-matrix technique is a convenient way for studying strip lattices
in the Potts model since the compu- tational costs depend just on the periodic
part of the lattice and not on the whole. However, even when the cost is
reduced, the transfer-matrix technique is still an NP-hard problem since the
time T(|V|, |E|) needed to compute the matrix grows ex- ponentially as a
function of the graph width. In this work, we present a parallel
transfer-matrix implementation that scales performance under multi-core
architectures. The construction of the matrix is based on several repetitions
of the deletion- contraction technique, allowing parallelism suitable to
multi-core machines. Our experimental results show that the multi-core
implementation achieves speedups of 3.7X with p = 4 processors and 5.7X with p
= 8. The efficiency of the implementation lies between 60% and 95%, achieving
the best balance of speedup and efficiency at p = 4 processors for actual
multi-core architectures. The algorithm also takes advantage of the lattice
symmetry, making the transfer matrix computation to run up to 2X faster than
its non-symmetric counterpart and use up to a quarter of the original space
Veamy: an extensible object-oriented C++ library for the virtual element method
This paper summarizes the development of Veamy, an object-oriented C++
library for the virtual element method (VEM) on general polygonal meshes, whose
modular design is focused on its extensibility. The linear elastostatic and
Poisson problems in two dimensions have been chosen as the starting stage for
the development of this library. The theory of the VEM, upon which Veamy is
built, is presented using a notation and a terminology that resemble the
language of the finite element method (FEM) in engineering analysis. Several
examples are provided to demonstrate the usage of Veamy, and in particular, one
of them features the interaction between Veamy and the polygonal mesh generator
PolyMesher. A computational performance comparison between VEM and FEM is also
conducted. Veamy is free and open source software
Generic Face Animation
International audienceIn computer vision, the animation of objects has attracted a lot attention, specially the animations of 3D face models. The animation of face models requires in general to manually adapt each generic movement (open/close mouth) to each specific head geometry. In this work we propose a technique for the animation of any face model avoiding most of the manual intervention. In order to achieve this we assume that: (1) faces, despite obvious differences are quite similar and a single generic model can be used to simplify deformations and (2) using this face model, a simple interpolation technique can be used, with minimal manual intervention. Several examples are presented to verify the realism of the obtained animations
Animation of generic 3D Head models driven by speech
International audienceIn this paper, a system for speech-driven animation of generic 3D head models is presented. The system is based on the inversion of a joint Audio-Visual Hidden Markov Model to estimate the visual information from speech data. Estimated visual speech features are used to animate a simple face model. The animation of a more complex head model is then obtained by automatically mapping the deformation of the simple model to it. The proposed algorithm allows the animation of 3D head models of arbitrary complexity through a simple setup procedure. The resulting animation is evaluated in terms of intelligibility of visual speech through subjective tests, showing a promising performance
A 3D Voronoi+Gapper Galaxy Cluster Finder in Redshift Space to z∼ 0.2 I: an Algorithm Optimized for the 2dFGRS
This paper is the first in a series, presenting a new galaxy cluster finder based on a three-dimensional Voronoi Tesselation plus a maximum likelihood estimator, followed by gapping-filtering in radial velocity(VoML+G). The scientific aim of the series is a reassessment of the diversity of optical clusters in the local universe. A mock galaxy database mimicking the southern strip of the magnitude(blue)-limited 2dF Galaxy Redshift Survey (2dFGRS), for the redshift range 0.009 N g ≥ 5, and 14% with N g < 5. The ensemble of VoML+G clusters has a ~59% completeness and a ~66% purity, whereas the subsample with N g ≥ 10, to z ~ 0.14, has greatly improved mean rates of ~75% and ~90%, respectively. The VoML+G cluster velocity dispersions are found to be compatible with those corresponding to "Millennium clusters" over the 300–1000 km s−1 interval, i.e., for cluster halo masses in excess of ~3.0 × 1013 M ⊙ h −1
A 3D Voronoi+Gapper Galaxy Cluster Finder in Redshift Space to z ∼ 0.2. II. An Abundant Cluster Population Dominated by Late-type Galaxies Unveiled
We identify 1901 galaxy clusters (N g ≥ 2) with the VoML+G algorithm (Paper I) on the Two-Degree Field Galaxy Redshift Survey. We present the 341 clusters with at least 10 galaxies that are within 0.009 < z < 0.14 (the Catalog), of which 254 (~75%) have counterparts in the literature (NED), with the remainder (87) plausibly "new" because of incompleteness of previous searches or unusual galaxy contents. The 207 clusters within z = 0.04–0.09 are used to study the properties of the galaxy systems in the nearby universe, including their galaxy contents parameterized by the late-type galaxy fractions (f L ). For this nearly complete cluster subsample, we find the following: (i) 63% are dominated by early-type galaxies (i.e., the late-type-poor clusters, f L < 0.5) with corresponding mean multiplicity and logarithmic virial mass (in units of M ⊙) of 22 ± 1 and 12.91 ± 0.04, respectively; and (ii) 37% are dominated by late-type galaxies (i.e., the late-type-rich clusters, f L ≥ 0.5) with corresponding mean multiplicity and logarithmic virial mass (in units of M ⊙) of 15.7 ± 0.9 and 12.66 ± 0.07, respectively. The statistical analysis of the late-type fraction distribution supports, with a 3σ confidence level, the presence of two population components. It is suggested that the late-type-poor galaxy systems reflect and extend the class of Abell-APM-EDCC clusters and that the late-type-rich systems (~one-third of the total) belong to a new, previously unappreciated class. The late-type-rich clusters, on average high mass-to-light ratio systems, appear to be more clustered on large scales than the late-type-poor clusters. A class of late-type-rich clusters is not predicted by current theory
A 3D Voronoi+Gapper Galaxy Cluster Finder in Redshift Space to z
This paper is the first in a series, presenting a new galaxy cluster finder based on a three-dimensional Voronoi Tesselation plus a maximum likelihood estimator, followed by gapping-filtering in radial velocity(VoML+G). The scientific aim of the series is a reassessment of the diversity of optical clusters in the local universe. A mock galaxy database mimicking the southern strip of the magnitude(blue)-limited 2dF Galaxy Redshift Survey (2dFGRS), for the redshift range 0.009 N g ≥ 5, and 14% with N g < 5. The ensemble of VoML+G clusters has a ~59% completeness and a ~66% purity, whereas the subsample with N g ≥ 10, to z ~ 0.14, has greatly improved mean rates of ~75% and ~90%, respectively. The VoML+G cluster velocity dispersions are found to be compatible with those corresponding to "Millennium clusters" over the 300–1000 km s−1 interval, i.e., for cluster halo masses in excess of ~3.0 × 1013 M ⊙ h −1
3D NOffset mixed-element mesh generator approach
In this paper we present a new approach to generate a mixed mesh with elements aligned to boundary/interfaces wherever is
required. A valid element is: (a) any convex co-spherical element that fulfills the requirements of the underlying numerical
method and (b) any element that satisfies domain specific geometric features of the model. The algorithm is based on the
normal offsetting approach to generate coarse elements aligned to the boundary/interfaces. Those elements are later refined
to accomplish layer density requirements. The main steps of the algorithm are described in detail and examples are given to
illustrate the already implemented parts. As far as possible, we contrast this algorithm with previous approaches