Related papers: Bayesian group finder based on marked point proces…
Joint lensing and dynamical mass profile determinations of galaxy clusters are an excellent tool to constrain modification of gravity at cosmological scales. However, search for tiny departures from General Relativity calls for an accurate…
We investigate the clustering properties of loose groups in the Perseus--Pisces redshift Survey (PPS). Previous analyses based on CfA and SSRS surveys led to apparently contradictory results. We investigate the source of such discrepancies,…
We present a galaxy group-finding algorithm, the Photo-z Probability Peaks (P3) algorithm, optimized for locating small galaxy groups using photometric redshift data by searching for peaks in the signal-to-noise of the local overdensity of…
Context. Gravitational collapse theory and numerical simulations suggest that the velocity field within large-scale galaxy filaments is dominated by motions along the filaments. Aims. Our aim is to check whether observational data reveal…
Galaxy cluster counts in bins of mass and redshift have been shown to be a competitive probe to test cosmological models. This method requires an efficient blind detection of clusters from surveys with a well-known selection function and…
We present a Bayesian hierarchical framework to analyze photometric galaxy survey data with stellar population synthesis (SPS) models. Our method couples robust modeling of spectral energy distributions with a population model and a noise…
This work describes a full Bayesian analysis of the Nearby Universe as traced by galaxies of the 2M++ survey. The analysis is run in two sequential steps. The first step self-consistently derives the luminosity dependent galaxy biases, the…
The two-point correlation function has been the standard statistic for quantifying how galaxies are clustered. The statistic uses the positions of galaxies, but not their properties. Clustering as a function of galaxy property, be it type,…
We describe an empirical Bayesian approach to determine the most likely size of an astronomical population of sources of which only a small subset are observed above some limiting flux density threshold. The method is most naturally applied…
We present a general probabilistic formalism for cross-identifying astronomical point sources in multiple observations. Our Bayesian approach, symmetric in all observations, is the foundation of a unified framework for object matching,…
Combining our knowledge of halo structure and internal kinematics from cosmological dark matter simulations and the distribution of halo interlopers in projected phase space measured in cosmological galaxy simulations, we develop MAGGIE, a…
Bi-clustering is a useful approach in analyzing biological data when observations come from heterogeneous groups and have a large number of features. We outline a general Bayesian approach in tackling bi-clustering problems in moderate to…
We describe and apply a simple prescription for defining connected structures in galaxy redshift surveys. The method is based upon two passes with a friends-of-friends groupfinder. The first pass uses a cylindrical linking volume to find…
We have performed a detailed analysis of the ability of the friends-of-friends algorithm in identifying real galaxy systems in deep surveys such as the future Javalambre Physics of the Accelerating Universe Astrophysical Survey. Our…
In this work we introduce a new method to perform the identification of groups of galaxies and present results of the identification of galaxy groups in the Seventh Data Release of the Sloan Digital Sky Survey (SDSS-DR7). Our methodology…
We analyse the effects of galaxy interactions on star formation in groups and clusters of galaxies with virial masses in the range $10^{13} - 10 ^{15} M_{\odot}$. We find a trend for galaxy-galaxy interactions to be less efficient in…
Context. Clusters of galaxies are important for cosmology and astrophysics. They may be discovered through either the summed optical/IR radiation originating from their member galaxies or via X-ray emission originating from the hot…
We present the first public release of our Bayesian inference tool, Bayes-X, for the analysis of X-ray observations of galaxy clusters. We illustrate the use of Bayes-X by analysing a set of four simulated clusters at z=0.2-0.9 as they…
Clustering is a crucial task in various domains of knowledge, including medicine, epidemiology, genomics, environmental science, economics, and visual sciences, among others. Methodologies for inferring the number of clusters have often…
Two algorithms for the identification of galaxy groups from redshift surveys are tested by application to simulated data derived from N-body simulation. The accuracy of the membership assignments by these algorithms is studied in a…