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Peculiar velocities arise from gravitational instability, and thus are linked to the surrounding distribution of matter. In order to understand the motion of the Local Group with respect to the Cosmic Microwave Background, a deep all-sky map of the galaxy distribution is required. Here we present a new redshift compilation of 69~160 galaxies, dubbed 2M++, to map large-scale structures of the Local Universe over nearly the whole sky, and reaching depths of K <= 12.5, or 200 Mpc/h. The target catalogue is based on the Two-Micron-All-Sky Extended Source Catalog (2MASS-XSC). The primary sources of redshifts are the 2MASS Redshift Survey, the 6dF galaxy redshift survey and the Sloan Digital Sky Survey (DR7). We assess redshift completeness in each region and compute the weights required to correct for redshift incompleteness and apparent magnitude limits, and discuss corrections for incompleteness in the Zone of Avoidance. We present the density field for this survey, and discuss the importance of large-scale structures such as the Shapley Concentration.
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 power-spec
We describe the construction of an all-sky galaxy catalogue, using SuperCOSMOS scans of Schmidt photographic plates from the UKST and POSS2 surveys. The photographic photometry is calibrated using SDSS data, with results that are linear to 2% or bett
We present redshift distribution estimates of galaxies selected from the fourth data release of the Kilo-Degree Survey over an area of $sim1000$ deg$^2$ (KiDS-1000). These redshift distributions represent one of the crucial ingredients for weak gravi
Using the complete GAMA-I survey covering ~142 sq. deg. to r=19.4, of which ~47 sq. deg. is to r=19.8, we create the GAMA-I galaxy group catalogue (G3Cv1), generated using a friends-of-friends (FoF) based grouping algorithm. Our algorithm has been te
The DMASS sample is a photometric sample from the DES Year 1 data set designed to replicate the properties of the CMASS sample from BOSS, in support of a joint analysis of DES and BOSS beyond the small overlapping area. In this paper, we present the