Photometric redshift galaxies as tracers of the filamentary network

Galaxy filaments are the dominant feature in the overall structure of the cosmic web. The study of the filamentary web is an important aspect in understanding galaxy evolution and the evolution of matter in the Universe. A map of the filamentary structure is an adequate probe of the web. We propose that photometric redshift galaxies are significantly positively associated with the filamentary structure detected from the spatial distribution of spectroscopic redshift galaxies. The catalogues of spectroscopic and photometric galaxies are seen as point-process realisations in a sphere, and the catalogue of filamentary spines is proposed to be a realisation of a random set in a sphere. The positive association between these sets was studied using a bivariate $J-$function, which is a summary statistics studying clustering. A quotient $D$ was built to estimate the distance distribution of the filamentary spine to galaxies in comparison to the distance distribution of the filamentary spine to random points in $3-$dimensional Euclidean space. This measure gives a physical distance scale to the distances between filamentary spines and the studied sets of galaxies. The bivariate $J-$function shows a statistically significant clustering effect in between filamentary spines and photometric redshift galaxies. The quotient $D$ confirms the previous result that smaller distances exist with higher probability between the photometric galaxies and filaments. The trend of smaller distances between the objects grows stronger at higher redshift. Additionally, the quotient $D$ for photometric galaxies gives a rough estimate for the filamentary spine width of about $1$~Mpc. Photometric redshift galaxies are positively associated with filamentary spines detected from the spatial distribution of spectroscopic galaxies.Comment: Accepted to Astronomy & Astrophysics. 13 pages and 9 figure

The bivariate J-function to analyse positive association between galaxies and galaxy filaments

International audienceThe compelling and intrinsic network of galaxies builds up a complex structure for the Universe. In this work positive association between long bridging structures named galaxy filaments and a photometric redshift galaxy dataset is under investigation. Possible positive association is studied by the use of a bivariate J-function.Le réseau de filaments formé par la position des galaxies est une des structures les plus fascinantes dans notre Univers. Dans cet article, nous étudions des possibles associations entre le réseau de filaments déjà détecté et des nouvelles observations. Ces observations très récentes sont obtenues à partir des mesures du décalage vers le rouge photométrique. L'utilisation de la fonction J-bivariée tend à indiquer une association positive entre les filaments existants et les nouvelles observations

Bayesian group finder based on marked point processes. Method and feasibility study using the 2MRS data set

International audienceContext. Galaxy groups and clusters are formidable cosmological probes. They permit the studying of the environmental effects on galaxy formation. A reliable detection of galaxy groups is an open problem and is important for ongoing and future cosmological surveys.Aims. We propose a probabilistic galaxy group detection algorithm based on marked point processes with interactions.Methods. The pattern of galaxy groups in a catalogue is seen as a random set of interacting objects. The positions and the interactions of these objects are governed by a probability density. The parameters of the probability density were chosen using a priori knowledge. The estimator of the unknown cluster pattern is given by the configuration of objects maximising the proposed probability density. Adopting the Bayesian framework, the proposed probability density is maximised using a simulated annealing (SA) algorithm. At fixed temperature, the SA algorithm is a Monte Carlo sampler of the probability density. Hence, the method provides “for free” additional information such as the probabilities that a point or two points in the observation domain belong to the cluster pattern, respectively. These supplementary tools allow the construction of tests and techniques to validate and to refine the detection result.Results. To test the feasibility of the proposed methodology, we applied it to the well-studied 2MRS data set. Compared to previously published Friends-of-Friends (FoF) group finders, the proposed Bayesian group finder gives overall similar results. However for specific applications, like the reconstruction of the local Universe, the details of the grouping algorithms are important.Conclusions. The proposed Bayesian group finder is tested on a galaxy redshift survey, but more detailed analyses are needed to understand the actual capabilities of the algorithm regarding upcoming cosmological surveys. The presented mathematical framework permits adapting it easily for other data sets (in astronomy and in other fields of sciences). In cosmology, one promising application is the detection of galaxy groups in photometric galaxy redshift surveys, while taking into account the full photometric redshift posteriors.Key words: methods: data analysis / methods: statistical / galaxies: groups: general / galaxies: clusters: general / catalogs / large-scale structure of Universe⋆ Galaxy group catalogue for 2MRS is only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/618/A8