用于MICE Grand Challenge光锥模拟的全天空集成Sachs-Wolfe地图
Full sky Integrated Sachs-Wolfe maps for the MICE Grand Challenge lightcone simulation
摘要：
我们提出了完整的天空地图的综合萨克斯-沃尔夫效应（ISW）的MICE大挑战光锥模拟高达红移1.4。该地图是在线性政权使用球面贝塞尔变换。我们比较和对比这个过程对文献中发现的分析近似。通过计算ISW的线性政权，我们删除了大量的计算和存储资源所需的非线性Rees-Sciama效应。由于线性ISW在低红移$z\leq1$，在大的角度尺度，并在物质支配后，是$\sim 10^{2}\times$更大的$ΔT/T$，这有一个可以忽略不计的影响所产生的地图，只有成为相关的尺度，占主导地位的宇宙微波背景（CMB）各向异性。MICE模拟产品已广泛用于涉及当前和未来星系调查的研究。这些地图的可用性将允许MICE用于未来的星系和CMB互相关研究，ISW重建研究，以及星系调查（如暗能量调查，暗能量光谱仪器，欧几里得和鲁宾遗产时空调查）探测的ISW空隙堆积研究。本研究中开发的管道作为公共Python包pyGenISW提供。这可以用于未来的研究，从现有和未来的模拟套件探测大量的宇宙学参数和模型来构建ISW。
英文摘要：
We present full-sky maps of the Integrated Sachs-Wolfe effect (ISW) for the MICE Grand Challenge lightcone simulation up to redshift 1.4. The maps are constructed in the linear regime using spherical Bessel transforms. We compare and contrast this procedure against analytical approximations found in the literature. By computing the ISW in the linear regime, we remove the substantial computing and storage resources required to calculate the non-linear Rees-Sciama effect. Since the linear ISW at low redshift $z\leq1$, at large angular scales, and after matter domination is $\sim 10^{2}\times$ larger in $ΔT/T$, this has a negligible impact on the maps produced and only becomes relevant on scales which are dominated by cosmic microwave background (CMB) anisotropies. The MICE simulation products have been extensively used for studies involving current and future galaxy surveys. The availability of these maps will allow MICE to be used for future galaxy and CMB cross-correlation studies, ISW reconstruction studies, and ISW void-stacking studies probed by galaxy surveys such as Dark Energy Survey, Dark Energy Spectroscopic Instrument, Euclid, and Rubin Legacy Survey of Space and Time. The pipeline developed in this study is provided as a public Python package pyGenISW. This could be used in the future studies for constructing the ISW from existing and future simulation suites probing vast sets of cosmological parameters and models.
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。
