Non-linear corrections to the cosmological matter power spectrum and scale-dependent galaxy bias: implications for parameter estimation

Non-linear corrections to the cosmological matter power spectrum and scale-dependent galaxy bias: implications for parameter estimation
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DOI:
10.1088/1475-7516/2008/07/017
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发表时间:
2008-04
影响因子:
6.4
通讯作者:
J. Hamann;S. Hannestad;A. Melchiorri;Y. Wong
J. Hamann;S. Hannestad;A. Melchiorri;Y. Wong
中科院分区:
物理与天体物理2区
文献类型:
--
作者:
J. Hamann;S. Hannestad;A. Melchiorri;Y. Wong

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我们探索和比较两个非线性校正和尺度依赖的偏置模型的性能,从星系功率谱数据中提取宇宙学信息,特别是在超ΛCDM(CDM:冷暗物质)宇宙学的背景下。第一个模型是著名的Q模型,首次应用于分析二度场星系红移巡天数据。第二,P模型,灵感来自晕轮模型,其中非线性演化和尺度相关的偏置封装在一个单一的非泊松散粒噪声项。我们发现,虽然这两个模型在标准ΛCDM宇宙学和大质量中微子扩展中为一系列星系聚类数据提供足够的校正方面表现同样出色,但Q模型可以在包含次主导自由流动暗物质的宇宙学中给出非物理结果,其温度取决于粒子质量,例如,残余的热轴子,除非一个合适的前施加在校正参数。最后一种情况也暴露了分析边缘化的危险,这种技术有时用于边缘化讨厌的参数。相比之下,P模型没有受到不期望的影响,并且由于其物理透明性,也是推荐的非线性校正模型。
We explore and compare the performances of two non-linear correction and scale-dependent biasing models for the extraction of cosmological information from galaxy power spectrum data, especially in the context of beyond-ΛCDM (CDM: cold dark matter) cosmologies. The first model is the well known Q model, first applied in the analysis of Two-degree Field Galaxy Redshift Survey data. The second, the P model, is inspired by the halo model, in which non-linear evolution and scale-dependent biasing are encapsulated in a single non-Poisson shot noise term. We find that while the two models perform equally well in providing adequate correction for a range of galaxy clustering data in standard ΛCDM cosmology and in extensions with massive neutrinos, the Q model can give unphysical results in cosmologies containing a subdominant free-streaming dark matter whose temperature depends on the particle mass, e.g., relic thermal axions, unless a suitable prior is imposed on the correction parameter. This last case also exposes the danger of analytic marginalization, a technique sometimes used in the marginalization of nuisance parameters. In contrast, the P model suffers no undesirable effects, and is the recommended non-linear correction model also because of its physical transparency.