Galaxy bias from the Dark Energy Survey Science Verification data: combining galaxy density maps and weak lensing maps
Galaxy bias from the Dark Energy Survey Science Verification data: combining galaxy density maps and weak lensing maps
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暗能量巡天科学验证数据中的星系偏差：结合星系密度图和弱透镜图
DOI：
10.1093/mnras/stw861
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发表时间：
2016
影响因子：
4.8
通讯作者：
Chang C
中科院分区：
文献类型：
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作者：
Chang C
通过结合暗能量巡天（DES）科学验证（SV）数据的116 deg 2区域的星系密度图和弱透镜剪切图，我们测量了一个星等有限的星系样本的星系偏差的红移演化.该方法首先由阿马拉et al.后来在一篇配套论文中用严格的模拟试验和层析测量的分析处理重新进行了研究。在本工作中，我们将这种方法应用于DES SV数据，测量了ai< 22.5的星系样本的星系偏差。我们发现四个测光红移仓的星系偏差和1σ误差棒分别为1.12 ± 0.19（z= 0.2-0.4），0.97 ± 0.15（z= 0.4-0.6），1.38 ± 0.39（z= 0.6-0.8）和1.45 ± 0.56（z= 0.8-1.0）。这些测量在2σ水平上与使用星系聚类和星系与宇宙微波背景透镜的互相关对相同数据集的测量一致，大多数红移箱在1σ误差条内一致。此外，我们的方法提供了三者中唯一的σ 8独立约束.我们使用模拟星系星表，包括形状噪声，photo-zerrors，和掩蔽效应的主要观测效果的前向模型。我们表明，我们的偏见测量数据是一致的，从模拟预期。随着即将到来的完整DES数据集，我们希望这种方法提供更多的限制，从更传统的方法的星系偏差测量。此外，在我们的测量过程中，我们建立了一个3D质量图，允许进一步探索暗物质分布及其与星系演化的关系。
We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a ∼116 deg2area of the Dark Energy Survey (DES) Science Verification (SV) data. This method was first developed in Amara et al. and later re-examined in a companion paper with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for ai< 22.5 galaxy sample. We find the galaxy bias and 1σ error bars in four photometric redshift bins to be 1.12 ± 0.19 (z= 0.2–0.4), 0.97 ± 0.15 (z= 0.4–0.6), 1.38 ± 0.39 (z= 0.6–0.8), and 1.45 ± 0.56 (z= 0.8–1.0). These measurements are consistent at the 2σ level with measurements on the same data set using galaxy clustering and cross-correlation of galaxies with cosmic microwave background lensing, with most of the redshift bins consistent within the 1σ error bars. In addition, our method provides the only σ8independent constraint among the three. We forward model the main observational effects using mock galaxy catalogues by including shape noise, photo-zerrors, and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Furthermore, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.