Related papers: Bayesian group finder based on marked point proces…
We construct a galaxy groups catalogue from the public 100K data release of the 2dF galaxy redshift survey. The group identification is carried out using a slightly modified version of the group finding algorithm developed by Huchra &…
We analyze the 2-point correlation function (2PCF) of galaxy groups identified from the 2-degree Field Galaxy Redshift Survey with the halo based group finder recently developed by Yang et al (2004b). With this group catalogue we are able…
The Universe at the present epoch is found to be a network of matter over-dense and under-dense regions. To date, this picture of the Universe is best revealed through cosmological large-volume simulations and large-scale galaxy redshift…
Clusters of galaxies are the most massive objects in the Universe and mapping their location is an important astronomical problem. This paper describes an algorithm (based on statistical signal processing methods), a software architecture…
Galaxy groups and clusters are the main tools used to test cosmological models and to study the environmental effect of galaxy formation. This work provides a catalogue of galaxy groups and clusters, as well as potentially merging systems…
Machine learning, algorithms to extract empirical knowledge from data, can be used to classify data, which is one of the most common tasks in observational astronomy. In this paper, we focus on Bayesian data classification algorithms using…
We create a new catalogue of groups and clusters for the 2dF GRS final release sample. We show that the variable linking length friends-of-friends (FoF) algorithms used so far yield groups with sizes that grow systematically with distance…
We have developed a method for detecting clusters in large imaging surveys, based on the detection of structures in galaxy density maps made in slices of photometric redshifts. This method was first applied to the Canada France Hawaii…
Numerous methods for finding clusters at moderate to high redshifts have been proposed in recent years, at wavelengths ranging from radio to X-rays. In this paper we describe a new method for detecting clusters in two-band optical/near-IR…
Bayesian model-based clustering is a widely applied procedure for discovering groups of related observations in a dataset. These approaches use Bayesian mixture models, estimated with MCMC, which provide posterior samples of the model…
In the theoretical framework of hierarchical structure formation, galaxy clusters evolve through continuous accretion and mergers of substructures. Cosmological simulations have revealed the best picture of the Universe as a 3-D filamentary…
Probabilistic cross-identification has been successfully applied to a number of problems in astronomy from matching simple point sources to associating stars with unknown proper motions and even radio observations with realistic morphology.…
A galaxy group catalog is constructed from the 2MASS Redshift Survey (2MRS) with the use of a halo-based group finder. The halo mass associated with a group is estimated using a `GAP' method based on the luminosity of the central galaxy and…
We present a Bayesian inference approach to estimating the cumulative mass profile and mean squared velocity profile of a globular cluster given the spatial and kinematic information of its stars. Mock globular clusters with a range of…
Galaxy clusters are the largest gravitationally bound systems, and they continue their growth through mergers in a hierarchical {\Lambda}CDM Universe. Therefore, we can describe the merger stage of a cluster as the dynamical state of…
We describe an automated method for detecting clusters of galaxies in imaging and redshift galaxy surveys. The Adaptive Matched Filter (AMF) method utilizes galaxy positions, magnitudes, and---when available---photometric or spectroscopic…
Cosmic voids contain higher-order cosmological information and are of interest for astroparticle physics. Finding genuine matter underdensities in sparse galaxy surveys is, however, an underconstrained problem. Traditional void finding…
Clusters of galaxies are important laboratories for understanding both galaxy evolution and constraining cosmological quantities. Any analysis of clusters, however, is best done when one can reliably determine which galaxies are members of…
A new method is presented for modelling the physical properties of galaxy clusters. Our technique moves away from the traditional approach of assuming specific parameterised functional forms for the variation of physical quantities within…
We use a modified version of the halo-based group finder developed by Yang et al. to select galaxy groups from the Sloan Digital Sky Survey (SDSS DR4). In the first step, a combination of two methods is used to identify the centers of…