论文标题

通过非线性可区分远期建模的宇宙的关节速度和密度重建

Joint velocity and density reconstruction of the Universe with nonlinear differentiable forward modeling

论文作者

Bayer, Adrian E., Modi, Chirag, Ferraro, Simone

论文摘要

从延迟观察中重建宇宙的初始条件具有最佳提取宇宙学信息的潜力。由于参数空间的高维度,因此需要一个可区分的前向模型,并且最近的进步使得可以使用基于星系(或晕圈)位置的非线性模型进行重建。除位置外,未来的调查还将通过运动学Sunyaev-Zel'Dovich效应(KSZ),IA型超新星和基本平面或Tully-Fisher关系来测量星系的特殊速度。在这里,我们开发了包括光晕速度(晕圈位置)的形式主义,以增强初始条件的重建。我们表明,与仅使用光环密度场相比,使用速度信息可以显着提高重建精度。我们研究这种改进是射击噪声,速度测量噪声以及与视线线的角度的函数。我们还展示了如何使用光晕速度数据来改善最终非线性物质密度和速度场的重建。我们已经将管道构建到可区分的粒子网式封装中,为执行场级宇宙学的推断铺平了道路,并使用关节速度和密度重建。鉴于在不久的将来测量特殊速度的能力增加了,这一点尤其有用。

Reconstructing the initial conditions of the Universe from late-time observations has the potential to optimally extract cosmological information. Due to the high dimensionality of the parameter space, a differentiable forward model is needed for convergence, and recent advances have made it possible to perform reconstruction with nonlinear models based on galaxy (or halo) positions. In addition to positions, future surveys will provide measurements of galaxies' peculiar velocities through the kinematic Sunyaev-Zel'dovich effect (kSZ), type Ia supernovae, and the fundamental plane or Tully-Fisher relations. Here we develop the formalism for including halo velocities, in addition to halo positions, to enhance the reconstruction of the initial conditions. We show that using velocity information can significantly improve the reconstruction accuracy compared to using only the halo density field. We study this improvement as a function of shot noise, velocity measurement noise, and angle to the line of sight. We also show how halo velocity data can be used to improve the reconstruction of the final nonlinear matter overdensity and velocity fields. We have built our pipeline into the differentiable Particle-Mesh FlowPM package, paving the way to perform field-level cosmological inference with joint velocity and density reconstruction. This is especially useful given the increased ability to measure peculiar velocities in the near future.

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