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arXiv 2407.19481astro-ph.COastro-ph.IMcs.LG
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利用高斯过程回归法研究再电离期间天体物理参数

What can we learn about Reionization astrophysical parameters using Gaussian Process Regression?

Centre for Theoretical Physics, Jamia Millia Islamia(理论物理中心,Jamia Millia Islamia大学);Physics and Applied Mathematics Unit, Indian Statistical Institute(印度统计研究所物理与应用数学单元);Institute of Physics, Bhubaneswar(物理研究所,Bhubaneswar)

Purba Mukherjee, Antara Dey, Supratik Pal

AI总结:

本文利用高斯过程回归方法研究再电离期间天体物理参数,通过MCMC分析和联合参数估计提高推断可靠性。

摘要:

再电离是宇宙进化历史中最不为人知的过程之一,主要是因为同时发生的过程众多,目前我们对其了解甚少。本文利用高斯过程回归(GPR)方法来学习再电离历史并推断天体物理参数。我们使用HFF和早期JWST数据重建了紫外辐射亮度密度函数。从重建的再电离历史中,计算了该时期全球微分亮度温度波动。我们利用SARAS仪器规格对全球21厘米信号进行了MCMC分析,结合Lyman-α电离分数数据、Planck光学深度测量和紫外辐射亮度数据。我们的分析表明,GPR比传统方法以一种模型无关的方式帮助推断天体物理参数。此外,我们利用重建的再电离历史分析了21厘米功率谱,并展示了未来21厘米任务SKA与Planck和Lyman-α森林数据结合,通过联合MCMC分析对再电离天体物理参数的限制进行改进。结果使基于GPR的重建技术成为稳健的学习过程,由此得到的天体物理参数推断结果非常可靠,可用于未来分析。

英文摘要:

Reionization is one of the least understood processes in the evolution history of the Universe, mostly because of the numerous astrophysical processes occurring simultaneously about which we do not have a very clear idea so far. In this article, we use the Gaussian Process Regression (GPR) method to learn the reionization history and infer the astrophysical parameters. We reconstruct the UV luminosity density function using the HFF and early JWST data. From the reconstructed history of reionization, the global differential brightness temperature fluctuation during this epoch has been computed. We perform MCMC analysis of the global 21-cm signal using the instrumental specifications of SARAS, in combination with Lyman-$α$ ionization fraction data, Planck optical depth measurements and UV luminosity data. Our analysis reveals that GPR can help infer the astrophysical parameters in a model-agnostic way than conventional methods. Additionally, we analyze the 21-cm power spectrum using the reconstructed history of reionization and demonstrate how the future 21-cm mission SKA, in combination with Planck and Lyman-$α$ forest data, improves the bounds on the reionization astrophysical parameters by doing a joint MCMC analysis for the astrophysical parameters plus 6 cosmological parameters for $Λ$CDM model. The results make the GPR-based reconstruction technique a robust learning process and the inferences on the astrophysical parameters obtained therefrom are quite reliable that can be used for future analysis.

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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