How does the grouping scheme affect the Wiener Filter reconstruction of the local Universe?

Monthly Notices of the Royal Astronomical Society

2018

Self Cite

To study the full formation and evolution history of galaxy clusters and their population, high resolution simulations of the latter are flourishing. However comparing observed clusters to the simulated ones on a one-to-one basis to refine the models and theories down to the details is non trivial. The large variety of clusters limits the comparisons between observed and numerical clusters. Simulations resembling the local Universe down to the cluster scales permit pushing the limit. Simulated and observed clusters can be matched on a one-to-one basis for direct comparisons provided that clusters are well reproduced besides being in the proper large scale environment. Comparing random and local-Universe like simulations obtained with differently grouped observational catalogs of peculiar velocities, this paper shows that the grouping scheme used to remove non-linear motions in the catalogs that constrain the simulations affects the quality of the numerical clusters. With a less aggressive grouping scheme -galaxies still falling onto clusters are preserved -combined with a bias minimization scheme, the mass of the dark matter halos, simulacra for 5 local clusters -Virgo, Centaurus, Coma, Hydra and Perseus -is increased by 39% closing the gap with observational mass estimates. Simulacra are found on average in 89% of the simulations, an increase of 5% with respect to the previous grouping scheme. The only exception is Perseus. Since the Perseus-Pisces region is not well covered by the used peculiar velocity catalog, the latest release let us foresee a better simulacrum for Perseus in a near future.

Section: The Local Large Scale Structuresupporting

confidence: 92%

Section: Introductionsupporting

confidence: 81%

Galaxy clusters in simulations of the local Universe: a matter of constraints

Sorce

Monthly Notices of the Royal Astronomical Society

2018

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“…The proper grouping of galaxies is a prerequisite for detecting the large-scale structure filaments that connect galaxy groups and clusters (Tempel et al 2014a(Tempel et al , 2016b. Additionally, proper grouping is essential in order to reconstruct the matter and velocity field via Wiener Filtering (Sorce & Tempel 2017).…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Merging groups and clusters of galaxies from the SDSS data

Tuvikene

Kipper

et al. 2017

A&A

Context. Galaxy groups and clusters are the main tools used to test cosmological models and to study the environmental effect of galaxy formation. Aims. This work provides a catalogue of galaxy groups and clusters, as well as potentially merging systems based on the SDSS main galaxy survey. Methods. We identified galaxy groups and clusters using the modified friends-of-friends (FoF) group finder designed specifically for flux-limited galaxy surveys. The FoF group membership is refined by multimodality analysis to find subgroups and by using the group virial radius and escape velocity to expose unbound galaxies. We look for merging systems by comparing distances between group centres with group radii. Results. The analysis results in a catalogue of 88 662 galaxy groups with at least two members. Among them are 6873 systems with at least six members which we consider to be more reliable groups. We find 498 group mergers with up to six groups. We performed a brief comparison with some known clusters in the nearby Universe, including the Coma cluster and Abell 1750. The Coma cluster in our catalogue is a merging system with six distinguishable subcomponents. In the case of Abell 1750 we find a clear sign of filamentary infall toward this cluster. Our analysis of mass-to-light ratio (M/L) of galaxy groups reveals that M/L slightly increases with group richness.

“…In recent years, several new group catalogues for 2MRS have been constructed (Tully 2015b;Lu et al 2016;Saulder et al 2016;Tempel et al 2016a;Kourkchi & Tully 2017;Lim et al 2017). The 2MRS groups have been used in many studies, including the reconstruction of the local Universe via constrained simulations (Sorce & Tempel 2017, to measure the gas content of galaxy groups (Hess & Wilcots 2013), to analyse the galaxy properties in poor groups of galaxies (Tovmassian & Plionis 2009) or to measure the intergalactic medium in fossil galaxy groups (Miraghaei et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Bayesian group finder based on marked point processes

Kruuse

Kipper

et al. 2018

A&A

Self Cite

Context. 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.