论文标题

红移空间流速度对Lyman-$α$ forest Baryon声学量表的影响

Redshift-space streaming velocity effects on the Lyman-$α$ forest baryon acoustic oscillation scale

论文作者

Givans, Jahmour J., Hirata, Christopher M.

论文摘要

Baryon声学振荡(BAO)量表是测量宇宙学距离的标准统治者,因此已成为宇宙扩张历史的主要探针。但是,任何改变标尺长度的物理作用都会导致我们确定距离和膨胀率的偏见。这些物理效应之一是流速度,即早期宇宙中巴元和暗物质之间的相对速度,由于它们在重组时声波中的共同起源,因此将其耦合到BAO量表。在这项工作中,我们调查了流速度对Lyman-$α$森林自动功率频谱的BAO特征的影响,这是最近被委托的DESI光谱仪使用的主要示踪剂之一。为此,我们为Lyman- $α$通量密度的对比度开发了一种新的扰动模型,该模型对于某些字段而言是二阶的,并且适用于任何红移空间结构的示踪剂,因为它仅基于对称性考虑因素。我们发现有8个偏置系数到二阶。我们发现流速度诱导的BAO量表为0.081--0.149%(横向)和0.053---0.058%(径向方向)(径向方向)的变化,具体取决于使用的偏置系数的模型。与Desi Lyman- $α$ BAO错误预算相比,这些比但不容易忽略,该预算在整体规模上为0.46%。这些结果对我们选择的偏差参数的敏感性强调了未来工作以测量模拟中高阶偏置系数的需求,尤其是对于DESI以外的将来的实验。

The baryon acoustic oscillation (BAO) scale acts as a standard ruler for measuring cosmological distances and has therefore emerged as a leading probe of cosmic expansion history. However, any physical effect that alters the length of the ruler can lead to a bias in our determination of distance and expansion rate. One of these physical effects is the streaming velocity, the relative velocity between baryons and dark matter in the early Universe, which couples to the BAO scale due to their common origin in acoustic waves at recombination. In this work, we investigate the impact of streaming velocity on the BAO feature of the Lyman-$α$ forest auto-power spectrum, one of the main tracers being used by the recently commissioned DESI spectrograph. To do this, we develop a new perturbative model for Lyman-$α$ flux density contrast which is complete to second order for a certain set of fields, and applicable to any redshift-space tracer of structure since it is based only on symmetry considerations. We find that there are 8 biasing coefficients through second order. We find streaming velocity-induced shifts in the BAO scale of 0.081--0.149% (transverse direction) and 0.053--0.058% (radial direction), depending on the model for the biasing coefficients used. These are smaller than, but not negligible compared to, the DESI Lyman-$α$ BAO error budget, which is 0.46% on the overall scale. The sensitivity of these results to our choice of bias parameters underscores the need for future work to measure the higher-order biasing coefficients from simulations, especially for future experiments beyond DESI.

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