β-Skeleton analysis of the cosmic web

@article{Fang2019SkeletonAO,
  title={$\beta$-Skeleton analysis of the cosmic web},
  author={Feng Fang and Jaime E. Forero-Romero and Graziano Rossi and Xiao-Dong Li and Longlong Feng},
  journal={Monthly Notices of the Royal Astronomical Society},
  year={2019}
}
The $\beta$-skeleton is a mathematical method to construct graphs from a set of points that has been widely applied in the areas of image analysis, machine learning, visual perception, and pattern recognition. In this work, we apply the $\beta$-skeleton to study the cosmic web. We use this tool on observed and simulated data to identify the filamentary structures and characterize the statistical properties of the skeleton. In particular, we compare the $\beta$-skeletons built from SDSS-III… 
View PDF on arXiv
7 Citations
Background Citations
3
Methods Citations
5

Figures from this paper

7 Citations

The Four Cosmic Tidal Web Elements from the β-skeleton

A fast Machine Learning-based approach to infer the underlying dark matter tidal cosmic web environment of a galaxy distribution from its β-skeleton graph, and makes one of the highest ranking random forest models available on a public repository for future reference and reuse.

Cosmological parameter estimation from large-scale structure deep learning

CNN can be more promising than people expected in deriving tight cosmological constraints from the cosmic large scale structure and exhibits robustness against smoothing, masking, random noise, global variation, rotation, reflection, and simulation resolution.

Using the Mark Weighted Correlation Functions to Improve the Constraints on Cosmological Parameters

We used the mark weighted correlation functions (MCFs), W(s), to study the large-scale structure of the universe. We studied five types of MCFs with the weighting scheme ρα, where ρ is the local…

The cosmic web through the lens of graph entropy

The information theory entropy of a graph as a scalar is explored and it is argued that this entropy can be used as a discrete analogue of scalars used to quantify the connectivity in continuous density fields.

Constraining cosmology with big data statistics of cosmological graphs

Three simple graph-topological measures can effectively discriminate among the five model universes produced by cosmological N-body simulations, and are directly related with the usual n-points correlation functions of the cosmic density field.

Cosmic Velocity Field Reconstruction Using AI

We develop a deep-learning technique to infer the nonlinear velocity field from the dark matter density field. The deep-learning architecture we use is a “U-net” style convolutional neural network,…

Large-scale structures in the ΛCDM Universe: network analysis and machine learning

An analysis of the Cosmic Web as a complex network, which is built on a $\Lambda$CDM cosmological simulation, shows that it is not possible to give a good prediction of the topology of Cosmic Web based only on coordinates and velocities of nodes, yet network metrics can give a hint about the topological landscape of matter distribution.

References

SHOWING 1-10 OF 43 REFERENCES

The Topology of the Cosmic Web in Terms of Persistent Betti Numbers

We introduce a multiscale topological description of the Megaparsec web-like cosmic matter distribution. Betti numbers and topological persistence offer a powerful means of describing the rich…

Tracing the cosmic web

The cosmic web is one of the most striking features of the distribution of galaxies and dark matter on the largest scales in the Universe. It is composed of dense regions packed full of galaxies,…

The persistent cosmic web and its filamentary structure I: Theory and implementation

The method is 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.

PRECISION COSMOGRAPHY WITH STACKED VOIDS

We present a purely geometrical method for probing the expansion history of the universe from the observation of the shape of stacked voids in spectroscopic redshift surveys. Our method is an…

The Crust and the beta-Skeleton: Combinatorial Curve Reconstruction

Two different graphs are given that, in this sense, reconstruct smooth curves: a simple new construction which is called the crust, and the β-skeleton, using a specific value of β.

A Dynamical Classification of the Cosmic Web

In this paper, we propose a new dynamical classification of the cosmic web. Each point in space is classified in one of four possible web types: voids, sheets, filaments and knots. The classification…

Cosmological constraints from the redshift dependence of the Alcock–Paczynski test and volume effect: galaxy two-point correlation function

We propose a method using the redshift dependence of the Alcock-Paczynski (AP) test and volume effect to measure the cosmic expansion history. The galaxy two-point correlation function as a function…

A measurement of the Alcock–Paczyński effect using cosmic voids in the SDSS

We perform an Alcock-Paczynski test using stacked cosmic voids identified in the SDSS Data Release 7 main sample and Data Release 10 LOWZ and CMASS samples. We find ~1,500 voids out to redshift $0.6$…

Cosmic web alignments with the shape, angular momentum and peculiar velocities of dark matter haloes

We study the alignment of dark matter haloes with the cosmic web characterized by the tidal and velocity shear fields. We focus on the alignment of their shape, angular momentum and peculiar…

The darkness that shaped the void: dark energy and cosmic voids

We assess the sensitivity of void shapes to the nature of dark energy that was pointed out in recent studies and also investigate whether or not void shapes are useable as an observational probe in…