4,462 research outputs found
Validity of the Cauchy-Born rule applied to discrete cellular-scale models of biological tissues.
The development of new models of biological tissues that consider cells in a discrete manner is becoming increasingly popular as an alternative to continuum methods based on partial differential equations, although formal relationships between the discrete and continuum frameworks remain to be established. For crystal mechanics, the discrete-to-continuum bridge is often made by assuming that local atom displacements can be mapped homogeneously from the mesoscale deformation gradient, an assumption known as the Cauchy-Born rule (CBR). Although the CBR does not hold exactly for noncrystalline materials, it may still be used as a first-order approximation for analytic calculations of effective stresses or strain energies. In this work, our goal is to investigate numerically the applicability of the CBR to two-dimensional cellular-scale models by assessing the mechanical behavior of model biological tissues, including crystalline (honeycomb) and noncrystalline reference states. The numerical procedure involves applying an affine deformation to the boundary cells and computing the quasistatic position of internal cells. The position of internal cells is then compared with the prediction of the CBR and an average deviation is calculated in the strain domain. For center-based cell models, we show that the CBR holds exactly when the deformation gradient is relatively small and the reference stress-free configuration is defined by a honeycomb lattice. We show further that the CBR may be used approximately when the reference state is perturbed from the honeycomb configuration. By contrast, for vertex-based cell models, a similar analysis reveals that the CBR does not provide a good representation of the tissue mechanics, even when the reference configuration is defined by a honeycomb lattice. The paper concludes with a discussion of the implications of these results for concurrent discrete and continuous modeling, adaptation of atom-to-continuum techniques to biological tissues, and model classification
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
Alpha, Betti and the Megaparsec Universe: on the Topology of the Cosmic Web
We study the topology of the Megaparsec Cosmic Web in terms of the
scale-dependent Betti numbers, which formalize the topological information
content of the cosmic mass distribution. While the Betti numbers do not fully
quantify topology, they extend the information beyond conventional cosmological
studies of topology in terms of genus and Euler characteristic. The richer
information content of Betti numbers goes along the availability of fast
algorithms to compute them.
For continuous density fields, we determine the scale-dependence of Betti
numbers by invoking the cosmologically familiar filtration of sublevel or
superlevel sets defined by density thresholds. For the discrete galaxy
distribution, however, the analysis is based on the alpha shapes of the
particles. These simplicial complexes constitute an ordered sequence of nested
subsets of the Delaunay tessellation, a filtration defined by the scale
parameter, . As they are homotopy equivalent to the sublevel sets of
the distance field, they are an excellent tool for assessing the topological
structure of a discrete point distribution. In order to develop an intuitive
understanding for the behavior of Betti numbers as a function of , and
their relation to the morphological patterns in the Cosmic Web, we first study
them within the context of simple heuristic Voronoi clustering models.
Subsequently, we address the topology of structures emerging in the standard
LCDM scenario and in cosmological scenarios with alternative dark energy
content. The evolution and scale-dependence of the Betti numbers is shown to
reflect the hierarchical evolution of the Cosmic Web and yields a promising
measure of cosmological parameters. We also discuss the expected Betti numbers
as a function of the density threshold for superlevel sets of a Gaussian random
field.Comment: 42 pages, 14 figure
The Spine of the Cosmic Web
We present the SpineWeb framework for the topological analysis of the Cosmic
Web and the identification of its walls, filaments and cluster nodes. Based on
the watershed segmentation of the cosmic density field, the SpineWeb method
invokes the local adjacency properties of the boundaries between the watershed
basins to trace the critical points in the density field and the separatrices
defined by them. The separatrices are classified into walls and the spine, the
network of filaments and nodes in the matter distribution. Testing the method
with a heuristic Voronoi model yields outstanding results. Following the
discussion of the test results, we apply the SpineWeb method to a set of
cosmological N-body simulations. The latter illustrates the potential for
studying the structure and dynamics of the Cosmic Web.Comment: Accepted for publication HIGH-RES version:
http://skysrv.pha.jhu.edu/~miguel/SpineWeb
The VOISE Algorithm: a Versatile Tool for Automatic Segmentation of Astronomical Images
The auroras on Jupiter and Saturn can be studied with a high sensitivity and
resolution by the Hubble Space Telescope (HST) ultraviolet (UV) and
far-ultraviolet (FUV) Space Telescope spectrograph (STIS) and Advanced Camera
for Surveys (ACS) instruments. We present results of automatic detection and
segmentation of Jupiter's auroral emissions as observed by HST ACS instrument
with VOronoi Image SEgmentation (VOISE). VOISE is a dynamic algorithm for
partitioning the underlying pixel grid of an image into regions according to a
prescribed homogeneity criterion. The algorithm consists of an iterative
procedure that dynamically constructs a tessellation of the image plane based
on a Voronoi Diagram, until the intensity of the underlying image within each
region is classified as homogeneous. The computed tessellations allow the
extraction of quantitative information about the auroral features such as mean
intensity, latitudinal and longitudinal extents and length scales. These
outputs thus represent a more automated and objective method of characterising
auroral emissions than manual inspection.Comment: 9 pages, 7 figures; accepted for publication in MNRA
Validity of the Cauchy-Born rule applied to discrete cellular-scale models of biological tissues
The development of new models of biological tissues that consider cells in a discrete manner is becoming increasingly popular as an alternative to PDE-based continuum methods, although formal relationships between the discrete and continuum frameworks remain to be established. For crystal mechanics, the discrete-to-continuum bridge is often made by assuming that local atom displacements can be mapped homogeneously from the mesoscale deformation gradient, an assumption known as the Cauchy-Born rule (CBR). Although the CBR does not hold exactly for non-crystalline materials, it may still be used as a first order approximation for analytic calculations of effective stresses or strain energies. In this work, our goal is to investigate numerically the applicability of the CBR to 2-D cellular-scale models by assessing the mechanical behaviour of model biological tissues, including crystalline (honeycomb) and non-crystalline reference states. The numerical procedure consists in precribing an affine deformation on the boundary cells and computing the position of internal cells. The position of internal cells is then compared with the prediction of the CBR and an average deviation is calculated in the strain domain. For centre-based models, we show that the CBR holds exactly when the deformation gradient is relatively small and the reference stress-free configuration is defined by a honeycomb lattice. We show further that the CBR may be used approximately when the reference state is perturbed from the honeycomb configuration. By contrast, for vertex-based models, a similar analysis reveals that the CBR does not provide a good representation of the tissue mechanics, even when the reference configuration is defined by a honeycomb lattice. The paper concludes with a discussion of the implications of these results for concurrent discrete/continuous modelling, adaptation of atom-to-continuum (AtC) techniques to biological tissues and model classification
Green-Schwarz Automorphisms and 6D SCFTs
All known interacting 6D superconformal field theories (SCFTs) have a tensor
branch which includes anti-chiral two-forms and a corresponding lattice of
string charges. Automorphisms of this lattice preserve the Dirac pairing and
specify discrete global and gauge symmetries of the 6D theory. In this paper we
compute this automorphism group for 6D SCFTs. This discrete data determines the
geometric structure of the moduli space of vacua. Upon compactification, these
automorphisms generate Seiberg-like dualities, as well as additional theories
in discrete quotients by the 6D global symmetries. When a perturbative
realization is available, these discrete quotients correspond to including
additional orientifold planes in the string construction.Comment: v2: 66 pages, 5 figures, updated references and clarifications adde
The persistent cosmic web and its filamentary structure I: Theory and implementation
We present DisPerSE, a novel approach to the coherent multi-scale
identification of all types of astrophysical structures, and in particular the
filaments, in the large scale distribution of matter in the Universe. This
method and corresponding piece of software allows a genuinely scale free and
parameter free identification of the voids, walls, filaments, clusters and
their configuration within the cosmic web, directly from the discrete
distribution of particles in N-body simulations or galaxies in sparse
observational catalogues. To achieve that goal, the method works directly over
the Delaunay tessellation of the discrete sample and uses the DTFE density
computed at each tracer particle; no further sampling, smoothing or processing
of the density field is required.
The idea is based on recent advances in distinct sub-domains of computational
topology, which allows a rigorous application of topological principles to
astrophysical data sets, taking into account uncertainties and Poisson noise.
Practically, the user can define a given persistence level in terms of
robustness with respect to noise (defined as a "number of sigmas") and the
algorithm returns the structures with the corresponding significance as sets of
critical points, lines, surfaces and volumes corresponding to the clusters,
filaments, walls and voids; filaments, connected at cluster nodes, crawling
along the edges of walls bounding the voids. The method is also interesting as
it allows for a robust quantification of the topological properties of a
discrete distribution in terms of Betti numbers or Euler characteristics,
without having to resort to smoothing or having to define a particular scale.
In this paper, we introduce the necessary mathematical background and
describe the method and implementation, while we address the application to 3D
simulated and observed data sets to the companion paper.Comment: A higher resolution version is available at
http://www.iap.fr/users/sousbie together with complementary material.
Submitted to MNRA
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