论文标题
语音深度调查中的Galaxy-Galaxy镜头
Galaxy-galaxy lensing in the VOICE deep survey
论文作者
论文摘要
语音成像数据的多频段光度法，与Chandra Deep South（CDFS）区域的4.9 v $^2 $重叠，可以使形状测量和光度红移估计成为弱透镜分析的两个基本量。 $ mag_ {ab} $的深度高达$ r $ band的26.1（5 $σ$限制）。我们根据较低红移（0.10 <$ z_l $ <0.35）的星系围绕星系周围的星系 - 盖亚测量值来估计过量的表面密度（ESD； $Δς$），而我们选择背景来源的较高红移范围为0.3至1.5。前景星系根据其颜色（蓝色/红色）分为两个主要类别，每个类别都被进一步分为高/低恒星质量箱。然后，通过对信号进行建模来估计样品的光环质量，并且参数的后部是通过Mote Carlo Markov链（MCMC）过程进行的样品。我们将结果与现有的恒星质量关系（SHMR）进行了比较，并发现蓝色低恒星质量箱（中位$ m _*= 10^{8.31} M_ \ odot $）与SHMR关系的偏差与其他三个样本符合经验曲线的一致。我们将这一差异解释为低质量蓝矮星人群的低星形成效率的影响。
The multi-band photometry of the VOICE imaging data, overlapping with 4.9 deg$^2$ of the Chandra Deep Field South (CDFS) area, enables both shape measurement and photometric redshift estimation to be the two essential quantities for weak lensing analysis. The depth of $mag_{AB}$ is up to 26.1 (5$σ$ limiting) in $r$-band. We estimate the Excess Surface Density (ESD; $ΔΣ$) based on galaxy-galaxy measurements around galaxies at lower redshift (0.10<$z_l$<0.35) while we select the background sources to be at higher redshift ranging from 0.3 to 1.5. The foreground galaxies are divided into two major categories according to their colour (blue/red), each of which has been further divided into high/low stellar mass bins. Then the halo masses of the samples are estimated by modelling the signals, and the posterior of the parameters are samples via Mote Carlo Markov Chain (MCMC) process. We compare our results with the existing Stellar-to-Halo Mass Relation (SHMR) and find that the blue low stellar mass bin (median $M_*=10^{8.31}M_\odot$) deviates from the SHMR relation whereas all other three samples agrees well with empirical curves. We interpret this discrepancy as the effect of a low star formation efficiency of the low-mass blue dwarf galaxy population dominated in the VOICE-CDFS area.
