Joint analyses of the large-scale distribution of galaxies, and their motions under the gravitational influence of this density field, allow powerful tests of the cosmological model, including measurement of the growth rate of cosmic structure. In this paper we perform a statistical comparison between two important classes of method for performing these tests. In the first method, which we refer to as the "power-spectrum method", we measure the 2-point power spectra between the velocity and density tracers, and jointly fit these statistics using theoretical models. In the second method, which we refer to as the "reconstruction-and-scaling method", we use the density tracers to reconstruct a model velocity field through space, which we compare with the measured galaxy velocities on a point-by-point basis. By generating an ensemble of numerical simulations in a simplified test scenario, we show that the error in the growth rate inferred by the reconstruction-and-scaling method may be under-estimated, unless the full covariances of the underlying and reconstructed velocity fields are included in the analysis. In this case the inferred growth rate errors agree with both the power-spectrum method and a Fisher matrix forecast. We provide a roadmap for evaluating these covariances, considering reconstruction performed using both a Fourier basis within a cuboid, and a Spherical Fourier-Bessel basis within a curved-sky observational volume.
Reconstructing dark matter distribution with peculiar velocities: Bayesian forward modelling with corrections for inhomogeneous Malmquist bias
我们提出了一个前向建模的速度场重建算法，只使用特殊的速度数据进行质量密度场的重建。我们的方法始终占的非齐次Malmquist偏差使用沿视线的分析积分。通过模拟测试我们的方法，我们表明，我们的方法给出了一个无偏重建的速度场。我们发现，不考虑不均匀的Malmquist偏差可能会导致显着的偏差，在向前建模重建。我们将我们的方法应用到一个由SFI++和2 MTF Tully-Fisher星表以及A2超新星汇编组成的特殊速度数据集上，从而获得了一个新的局部宇宙速度重建。我们的速度重建具有与理论预期一致的宇宙学功率谱。此外，我们通过后验分布的样本获得重建的不确定性的完整描述。我们验证我们的速度重建的本地宇宙进行比较，使用2 M ++星系目录的独立重建，获得良好的协议之间的两个重建。使用贝叶斯模型的比较，我们发现，我们的速度模型的性能优于自适应核平滑速度相同的特殊速度数据。然而，我们的速度模型不执行以及从2 M ++星系目录的速度重建，由于稀疏和噪声的性质，独特的速度示踪剂样本。这里提出的方法提供了一种方法，包括特殊的速度数据的初始条件重建框架。
The Velocity Field Olympics: Assessing velocity field reconstructions with direct distance tracers
University of Oxford（牛津大学）；Flatiron Institute（平顿研究所）；University of Portsmouth（朴茨茅斯大学）；CNRS & Sorbonne Université, Institut d’Astrophysique de Paris (IAP)（法国国家科学研究中心与索邦大学，巴黎天体物理研究所）；University of Waterloo（滑铁卢大学）；Perimeter Institute for Theoretical Physics（理论物理珀尔默特研究所）；Université Claude Bernard Lyon 1（里昂第一大学克洛德·贝尔纳大学）
Estimation and mitigation of foregrounds in projected kSZ velocity reconstruction
University of Cambridge（剑桥大学）；Kavli Institute for Cosmology Cambridge（卡弗里宇宙学剑桥研究所）；Berkeley Center for Cosmological Physics, Department of Physics, University of California, Berkeley（加州大学伯克利分校物理系宇宙学物理中心）；Lawrence Berkeley National Laboratory（劳伦斯伯克利国家实验室）；Institute of Astronomy, University of Cambridge（剑桥大学天文研究所）
Measuring cosmic bulk flow with kinetic Sunyaev-Zel'dovich velocity reconstruction
Perimeter Institute for Theoretical Physics（Perimeter理论物理研究所）；Department of Physics and Astronomy, York University（约克大学物理与天文学系）；Department of Physics and Astronomy, University of Waterloo（滑铁卢大学物理与天文学系）；Waterloo Centre for Astrophysics, University of Waterloo（滑铁卢大学滑铁卢天体物理中心）
Interpreting the stacked kinetic SZ effect I: velocity reconstruction and non-linear velocity effects
Institute of Astronomy, University of Cambridge（剑桥大学天文学研究所）；Kavli Institute for Cosmology Cambridge（卡弗里宇宙学剑桥研究所）；Donostia International Physics Center（圣塞巴斯蒂安国际物理中心）；IKERBASQUE, Basque Foundation for Science（伊克拉巴斯基，巴斯克科学基金会）；Leiden Observatory, Leiden University（莱顿大学莱顿天文台）
