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arXiv 2102.06902astro-ph.CO
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检验单圈星系偏差:功率谱和双谱的联合分析

Testing one-loop galaxy bias: joint analysis of power spectrum and bispectrum

Alexander Eggemeier, Román Scoccimarro, Robert E. Smith, Martin Crocce, Andrea Pezzotta, Ariel G. Sánchez

摘要:

我们提出了一个联合似然分析的实空间功率谱和双谱测量从各种晕和星系模拟目录。这项工作的一个新颖的方面是列入非线性三角形配置的双谱,使之成为可能的一个完整的下一个领先的顺序(“一圈”)描述星系的偏见,因为已经是常见的做法的功率谱。基于拟合优度和参数后验的无偏性,我们完成了一个严格的验证,该模型相比,领先的顺序(“树级”)双谱。使用对应于$6\,(\mathrm{Gpc}/h)^3$的有效调查体积的测量不确定性,我们确定单循环校正大致将尺度的适用范围加倍,从$\sim 0.17\,h/\mathrm{Mpc}$(树级)到$\sim 0.3\,h/\mathrm{Mpc}$。这转化为在固定宇宙学的线性偏置参数的约束上的$1.5 - 2$ x改进,以及波动幅度上的不确定性的$1.5 - 2.4$ x收缩$A_s$,这清楚地证明了从非线性尺度提取信息的益处,尽管必须在大量偏置参数上边缘化。此外,我们的精确测量的星系偏置参数高达四阶允许彻底的比较,共同进化的关系,显示出良好的协议所产生的所有贡献的非局部引力作用。在似然分析中使用这些关系不会损害模型的有效性,并且对于在$A_s$上获得所引用的改进至关重要。我们还分析了高阶导数和尺度依赖随机项的影响,发现对于我们的示踪剂的子集,前者可以提高树级模型的性能,与单循环模型相比,$A_s$上的约束仅略有下降。

英文摘要:

We present a joint likelihood analysis of the real-space power spectrum and bispectrum measured from a variety of halo and galaxy mock catalogs. A novel aspect of this work is the inclusion of nonlinear triangle configurations for the bispectrum, made possible by a complete next-to-leading order ("one-loop") description of galaxy bias, as is already common practice for the power spectrum. Based on the goodness-of-fit and the unbiasedness of the parameter posteriors, we accomplish a stringent validation of this model compared to the leading order ("tree-level") bispectrum. Using measurement uncertainties that correspond to an effective survey volume of $6\,(\mathrm{Gpc}/h)^3$, we determine that the one-loop corrections roughly double the applicable range of scales, from $\sim 0.17\,h/\mathrm{Mpc}$ (tree-level) to $\sim 0.3\,h/\mathrm{Mpc}$. This converts into a $1.5 - 2$x improvement on constraints of the linear bias parameter at fixed cosmology, and a $1.5 - 2.4$x shrinkage of uncertainties on the amplitude of fluctuations $A_s$, which clearly demonstrates the benefit of extracting information from nonlinear scales despite having to marginalize over a larger number of bias parameters. Besides, our precise measurements of galaxy bias parameters up to fourth order allow for thorough comparisons to coevolution relations, showing excellent agreement for all contributions generated by the nonlocal action of gravity. Using these relations in the likelihood analysis does not compromise the model validity and is crucial for obtaining the quoted improvements on $A_s$. We also analyzed the impact of higher-derivative and scale-dependent stochastic terms, finding that for a subset of our tracers the former can boost the performance of the tree-level model with constraints on $A_s$ that are only slightly degraded compared to the one-loop model.

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