Galaxy Cluster Mass Reconstruction Project: II. Quantifying scatter and bias using contrasting mock catalogues
L. Old, R. Wojtak, G. A. Mamon, R. A. Skibba, F. R. Pearce, D. Croton, S. Bamford, P. Behroozi, R. de Carvalho, J. C. Muñoz-Cuartas, D. Gifford, M. E. Gray, A. … 展开作者
L. Old, R. Wojtak, G. A. Mamon, R. A. Skibba, F. R. Pearce, D. Croton, S. Bamford, P. Behroozi, R. de Carvalho, J. C. Muñoz-Cuartas, D. Gifford, M. E. Gray, A. von der Linden, M. R. Merrifield, S. I. Muldrew, V. Müller, R. J. Pearson, T. J. Ponman, E. Rozo, E. Rykoff, A. Saro, T. Sepp, C. Sifón, E. Tempel
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25 pages, 19 figures, 7 tables. Accepted for publication in MNRAS
This article is the second in a series in which we perform an extensive comparison of various galaxy-based cluster mass estimation techniques that utilise the positions, velocities and colours of galaxies. Our aim is to quantify the scatter, systematic bias and completeness of cluster masses derived from a diverse set of 25 galaxy-based methods using two contrasting mock galaxy catalogues based on a sophisticated halo occupation model and a semi-analytic model. Analysing 968 clusters, we find a wide range in the RMS errors in log M200c delivered by the different methods (0.18 to 1.08 dex, i.e., a factor of ~1.5 to 12), with abundance matching and richness methods providing the best results, irrespective of the input model assumptions. In addition, certain methods produce a significant number of catastrophic cases where the mass is under- or over-estimated by a factor greater than 10. Given the steeply falling high-mass end of the cluster mass function, we recommend that richness or abundance matching-based methods are used in conjunction with these methods as a sanity check for studies selecting high mass clusters. We see a stronger correlation of the recovered to input number of galaxies for both catalogues in comparison with the group/cluster mass, however, this does not guarantee that the correct member galaxies are being selected. We do not observe significantly higher scatter for either mock galaxy catalogues. Our results have implications for cosmological analyses that utilise the masses, richnesses, or abundances of clusters, which have different uncertainties when different methods are used.
Mock Observatory: two thousand lightcone mock catalogues of luminous red galaxies from the Hyper Suprime-Cam Survey for the cosmological large-scale analysis
Modeling the HI-Halo Connection: Evolution, Scatter, and a Halo-based Prescription for 21-cm Mock Catalogs
INAF – Astronomical Observatory of Trieste（意大利国家天体物理研究所的里雅斯特天文台）；IFPU – Institute for Fundamental Physics of the Universe（宇宙基础物理研究所）；Observatoire de la Côte d’Azur, Laboratoire Lagrange（蔚蓝海岸天文台拉格朗日实验室）；Department of Physics & Astronomy, University of the Western Cape（西开普大学物理与天文学系）；Tianjin Astrophysics Center, Tianjin Normal University（天津师范大学天津天体物理中心）；Institute of Physics, Laboratory of Astrophysics, EPFL（洛桑联邦理工学院物理研究所天体物理实验室）
The effect of baryons on the positions and velocities of satellite galaxies in the MTNG simulation
Universidad de Sevilla（塞维利亚大学）；Donostia International Physics Center（多诺斯蒂亚国际物理中心）；IKERBASQUE, Basque Foundation for Science（伊卡巴斯基，巴斯克科学基金会）；Institute for Computational Cosmology, Department of Physics, Durham University（杜伦大学物理学院计算宇宙学研究所）；Kavli Institute for Cosmology Cambridge（剑桥卡弗里宇宙学研究所）；Institute of Astronomy（天文学研究所）；Harvard-Smithsonian Center for Astrophysics（哈佛-史密森尼天体物理中心）；Columbia Astrophysics Laboratory, Columbia University（哥伦比亚大学天体物理学实验室）；Max Planck Institute for Astrophysics（马克斯·普朗克天体物理学研究所）
Testing the inference of kinematics from mock JWST NIRSpec/MSA observations of TNG50 galaxies at $z\sim2-6$
Max-Planck-Institut für Astronomie（马克斯·普朗克天文学研究所）；Fakultät für Physik und Astronomie, Universität Heidelberg（海德堡大学物理与天文学院）；Space Telescope Science Institute（太空望远镜科学研究所）
The impact of source and survey modelling on the connection between [O III] emitters and Ly $α$ forest transmission at z ~ 6
The University of Nottingham（诺丁汉大学）；University of Edinburgh（爱丁堡大学）；Kavli Institute for Cosmology（卡弗里宇宙学研究所）；Tata Institute of Fundamental Research（塔塔基础研究所）；Leibniz-Institut für Astrophysik Potsdam（波茨坦阿斯特拉物理研究所）
Non-negative matrix factorization for self-calibration of photometric redshift scatter in weak lensing surveys
光z误差是系统学中降低弱透镜宇宙学推论准确性的主要原因之一。Zhang et al.（2010）提出了一种结合星系-星系相关性和星系-剪切相关性的自校准方法。Fisher矩阵分析表明，仅使用光度数据就可以确定0.01-1%水平的photo-z离群值比率，而不依赖于任何先验知识。在本文中，我们开发了一种新的算法来实现这种方法，通过解决自校准过程中出现的约束非线性优化问题。该算法基于不动点迭代和非负矩阵分解技术，能够高效、鲁棒地重建真z面元和光z面元之间的散射概率。该算法已经过广泛的测试，将其应用到模拟第四阶段弱透镜项目的模拟数据。我们发现，该算法提供了一个成功的恢复的散射率在0.01- 1%的水平，和真正的平均红移的photo-z仓在0.001的水平，这可能会满足要求，在未来的透镜调查。
J-PAS & FLAMINGO: Cosmic voids and void galaxies in the gravitational landscape of photometric surveys
University of Tartu（塔尔图大学）；University of Groningen（格罗宁根大学）；University of Turku（图尔库大学）；Leiden University（莱顿大学）；Universidade de São Paulo（圣保罗大学）；Instituto de Astronomia, Geofísica e Ciências Atmosféricas da USP（圣保罗大学天文、地球物理与大气科学研究所）；Centro de Estudios de Física del Cosmos de Aragón (CEFCA)（阿拉贡宇宙物理研究中心）
Challenges of standard halo models in constraining galaxy properties from CIB anisotropies
Institutes of Computer Science and Astrophysics, Foundation for Research and Technology Hellas (FORTH)（计算机科学与天体物理研究所，希腊研究与技术基金会）；Aix Marseille Univ, CNRS, CNES, LAM（艾克斯马赛大学）；Université de Strasbourg, CNRS, Observatoire astronomique de Strasbourg, UMR 7550（斯特拉斯堡大学）；Kavli Institute for Particle Astrophysics and Cosmology, Stanford University（斯坦福大学卡弗里粒子天体物理学与宇宙学研究所）；SLAC National Accelerator Laboratory（SLAC国家加速器实验室）
Denoising clustering covariance matrices with Rotational Invariant Estimators
INAF - Osservatorio Astronomico di Brera（意大利国家天体物理研究所布拉拉天文台）；Dipartimento di Fisica, Università degli Studi di Genova（热那亚大学物理系）；INFN - Sezione di Genova（意大利国家核物理研究所热那亚分部）；Dipartimento di Fisica e Astronomia Augusto Righi, Università di Bologna（博洛尼大学奥古斯托·里基物理与天文学系）
An Evaluation of 10 Lensing Models of the Frontier Fields Cluster MACSJ0416.1-2403
星系团可以充当引力透镜，放大背后的宇宙，让我们看到早期宇宙的深处。哈勃太空望远镜前沿领域计划（Lotz et al. 2017）使用哈勃拍摄的六个星系团来发现和研究z ~ 5-10的星系。七个独立的团队开发了透镜模型，并根据当时最好的可用数据的位置和红移限制，为每个星系团推导出放大率。在这项工作中，我们评估了2015年公布的MACSJ0416.1-2403的十个模型，并将其与2016年测量的新光谱红移进行了对比（Caminha et al. 2017）。我们开发了一种独立的比较方法，使用源平面均方根作为透镜模型性能的度量。我们的分析量化了模型预测未知多个图像的能力。我们研究了多重成像系统的源平面散射，并探讨了散射对背景源的位置和红移的依赖性。我们提出的分析评估的具体情况下的MACSJ0416.1-2403模型的不同算法的性能。
