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We extend the halo-based group finder developed by Yang et al. (2005b) to use data {it simultaneously} with either photometric or spectroscopic redshifts. A mock galaxy redshift surveys constructed from a high-resolution N-body simulation is used to evaluate the performance of this extended group finder. For galaxies with magnitude ${rm zle 21}$ and redshift $0<zle 1.0$ in the DESI legacy imaging surveys (The Legacy Surveys), our group finder successfully identifies more than 60% of the members in about $90%$ of halos with mass $ga 10^{12.5}msunh$. Detected groups with mass $ga 10^{12.0}msunh$ have a purity (the fraction of true groups) greater than 90%. The halo mass assigned to each group has an uncertainty of about 0.2 dex at the high mass end $ga 10^{13.5}msunh$ and 0.45 dex at the low mass end. Groups with more than 10 members have a redshift accuracy of $sim 0.008$. We apply this group finder to the Legacy Surveys DR8 and find 6.4 Million groups with at least 3 members. About 500,000 of these groups have at least 10 members. The resulting catalog containing 3D coordinates, richness, halo masses, and total group luminosities, is made publicly available.
In a recent study, we developed a method to model the impact of photometric redshift uncertainty on the two-point correlation function (2PCF). In this method, we can obtain both the intrinsic clustering strength and the photometric redshift errors si
The DESI Legacy Imaging Surveys are a combination of three public projects (the Dark Energy Camera Legacy Survey, the Beijing-Arizona Sky Survey, and the Mayall z-band Legacy Survey) that will jointly image approximately 14,000 deg^2 of the extragala
We characterise the selection cuts and clustering properties of a magnitude-limited sample of bright galaxies that is part of the Bright Galaxy Survey (BGS) of the Dark Energy Spectroscopic Instrument (DESI) using the ninth data release of the Legacy
We have conducted a search for new strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys Data Release 8. We use deep residual neural networks, building on previous work presented in Huang et al. (2020
We present the results of a new search for galaxy-scale strong lensing systems in CFHTLS Wide. Our lens-finding technique involves a preselection of potential lens galaxies, applying simple cuts in size and magnitude. We then perform a Principal Comp