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arXiv 2602.14533astro-ph.CO
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Zel'dovich 近似下的 BAO 特征涂抹:用于模型无关的宇宙学推断

Zel'dovich smearing approximation of the BAO feature for model-agnostic cosmological inference

Inter-University Centre for Astronomy & Astrophysics(星际大学天文学与天体物理中心);Center for Particle Cosmology, University of Pennsylvania(宾夕法尼亚大学粒子宇宙学中心);The Abdus Salam International Center for Theoretical Physics(阿卜杜斯·萨拉姆国际理论物理中心)

Aseem Paranjape, Ravi K. Sheth

AI总结:

本文提出基于Zel'dovich近似的模型无关框架,描述红移空间重子声学振荡(BAO)特征的非线性涂抹和偏差尺度依赖,通过无模板方法从星系巡天中获取无偏宇宙学约束。

摘要:

红移空间中重子声学振荡(BAO)特征的模型无关描述需要多个要素。物理上,必须描述宇宙学整体流的影响,这些流随时间逐渐且各向异性地涂抹特征。还必须模拟示踪偏差的尺度依赖性以及短尺度和长尺度之间的模式耦合。所有这些都可以仅使用Zel'dovich近似来纳入,无需参考任何特定的宇宙学模型。在技术方面,需要一个稳健、完整且与宇宙学无关的基来描述线性理论中实空间BAO特征的形状,然后可以将其传播到红移空间中非线性演化、测量到的特征。在这项工作中,我们描述了这些要素——我们在最近的工作中系统地构建了这些要素——如何在一个能够描述最先进星系巡天的BAO尺度成对测量的准确框架中结合在一起。使用模拟观测和$N$体模拟,我们展示了我们的无模板框架有可能为具有现实非线性水平的样本产生无偏且精确的宇宙学约束。这项工作代表了朝着构建一个用于从BAO特征进行模型无关宇宙学推断的数据就绪分析框架的最后步骤之一。

英文摘要:

A model-agnostic description of the baryon acoustic oscillation (BAO) feature in redshift space requires a number of ingredients. Physically, one must describe the impact of cosmological bulk flows which progressively and anisotropically smear out the feature over time. One must also model the effects of the scale dependence of tracer bias and the mode coupling between short and long scales. All of these can be incorporated using the Zel'dovich approximation alone, without reference to any particular cosmological model. On the technical front, one needs a robust, complete and cosmology-independent basis to describe the shape of the real space BAO feature in linear theory, which can then be propagated to the nonlinearly evolved, measured feature in redshift space. In this work, we describe how these ingredients -- which we have systematically constructed in recent work -- come together in an accurate framework capable of describing the BAO-scale pairwise measurements of state-of-the-art galaxy surveys. Using mock observations and $N$-body simulations, we show that our template-free framework can potentially produce unbiased and precise cosmological constraints for samples with realistic levels of nonlinearity. This work represents one of the final steps towards constructing a data-ready analysis framework for model-agnostic cosmological inference from the BAO feature.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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