We use a large K-selected sample of 299 961 galaxies from the REFINE survey, consisting of a combination of data from three of the deepest near-infrared surveys, UKIDSS UDS, COSMOS/UltraVISTA, and CFHTLS-D1/VIDEO, that were homogeneously reduced to obtain photometric redshifts and stellar masses. We detect 2588 candidate galaxy groups up to z = 3.15 at S/N > 1.5. We build a very pure ($\gt 90{{\rm \,per\ cent}}$) sample of 448 candidate groups up to z = 2.5 and study some of their properties. Cluster detection is done using the DElaunay TEssellation ClusTer IdentiFication with photo-z (detectifz) algorithm that we describe. This new group finder algorithm uses the joint probability distribution functions of redshift and stellar-mass of galaxies to detect groups as stellar-mass overdensities in overlapping redshift slices, where density is traced using Monte Carlo realization of the Delaunay Tessellation Field Estimator. We compute the algorithm selection function using mock galaxy catalogues taken from cosmological N-body simulation lightcones. Based on these simulations, we reach a completeness of $\sim \! 80{{\,\rm per\ cent}}$ for clusters (M200 > 1014M⊙) at a purity of $\sim \! 90{{\, \rm per\ cent}}$ at z < 2.5. Using our 403 most massive candidate groups, we constrain the redshift evolution of the group galaxy quenched fraction at 0.12 ≤ z < 2.32, for galaxies with 10.25 < log M⋆/M⊙ < 11 in 0.5 × R200. We find that the quenched fraction in group cores is higher than in the field in the full redshift range considered, the difference growing with decreasing redshift. This indicates either more efficient quenching mechanisms in group cores at lower redshift or pre-processing by cosmic filaments.

中文翻译：

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REFINE 调查中的 DETECTIFz 星系群 – I. z < 2.5 处的群探测和淬火分数演化

我们使用来自 REFINE 调查的 299 961 个星系的大型 K 选择样本，包括来自三个最深近红外调查的数据组合，UKIDSS UDS、COSMOS/UltraVISTA 和 CFHTLS-D1/VIDEO，它们是同质的减少以获得光度学红移和恒星质量。我们检测到 2588 个候选星系群，最高 z = 3.15，S/N > 1.5。我们构建了一个非常纯的 ($\gt 90{{\rm \,per\cent}}$) 样本，包含 448 个候选组，直到 z = 2.5，并研究了它们的一些属性。聚类检测是使用我们描述的带有 photo-z (detectifz) 算法的 DElaunay TEssellation Cluster IdentiFication 完成的。这种新的群定位算法使用星系红移和恒星质量的联合概率分布函数来检测重叠红移切片中恒星质量过密度的群，其中密度是使用 Delaunay Tessellation Field Estimator 的 Monte Carlo 实现来跟踪的。我们使用取自宇宙学 N 体模拟光锥的模拟星系目录来计算算法选择函数。基于这些模拟，我们达到了 $\sim \! 80{{\,\rm per\ cent}}$ 用于簇 (M200 > 1014M⊙)，纯度为 $\sim \! 90{{\, \rm per\ cent}}$ at z < 2.5. 使用我们的 403 个质量最大的候选群，我们将群星系淬火分数的红移演化限制在 0.12 ≤ z <; 2.32，对于 10.25 < 的星系 log M⋆/M⊙ < 11 英寸 0.5 × R200。我们发现，在所考虑的全红移范围内，群核中的淬火分数高于场中，差异随着红移的减小而增大。