arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2303.11368astro-ph.GAastro-ph.CO

贯穿宇宙时间的晕星系-超大质量黑洞连接的贝叶斯方法

A Bayesian approach to the halo galaxy - supermassive black hole connection through cosmic time

Christopher Boettner, Maxime Trebitsch, Pratika Dayal

AI总结:

使用经验星系演化模型研究暗物质晕、星系与超大质量黑洞的共同演化,通过贝叶斯方法校准重子过程规则,重现了关键观测结果并预测了JWST和Euclid巡天的预期源数量上限。

摘要:

我们使用从 $z=0$ 到 $10$ 的经验星系演化模型研究暗物质晕、星系和超大质量黑洞的共同演化。我们证明,通过将暗物质结构演化与重子过程的简单经验规则联系起来,我们能够忠实地重现星系及其超大质量黑洞之间关系的关键观测结果。通过假设星系和超大质量黑洞属性与其宿主晕质量之间存在物理驱动的直接关系,我们构建了星系恒星质量函数、星系 UV 亮度函数、活动黑洞质量函数和类星体热光度函数的表达式。我们使用完全贝叶斯方法校准重子规则,以重现观测到的种群统计结果。然后,获得的参数化被用于研究星系和黑洞属性之间的关系,以及它们随红移的演化。从模型中获得的星系恒星质量--UV 亮度关系、黑洞质量--恒星质量关系、黑洞质量--AGN 亮度关系,以及这些量的红移演化在定性上与观测结果一致。基于这些结果,我们给出了计划中的 JWST 和 \ extit{Euclid} 巡天在 $z=5$ 到 $z=15$ 期间预期源数量的上限,从而表明经验模型能够以快速、简单和灵活的方式提供定性和定量预测,补充了计算成本更高的方法。

英文摘要:

We study the co-evolution of dark matter halos, galaxies and supermassive black holes using an empirical galaxy evolution model from $z=0$ -- $10$. We demonstrate that by connecting dark matter structure evolution with simple empirical prescriptions for baryonic processes, we are able to faithfully reproduce key observations in the relation between galaxies and their supermassive black holes. By assuming a physically-motivated, direct relationship between the galaxy and supermassive black hole properties to the mass of their host halo, we construct expressions for the galaxy stellar mass function, galaxy UV luminosity function, active black hole mass function and quasar bolometric luminosity function. We calibrate the baryonic prescriptions using a fully Bayesian approach in order to reproduce observed population statistics. The obtained parametrizations are then used to study the relation between galaxy and black hole properties, as well as their evolution with redshift. The galaxy stellar mass -- UV luminosity relation, black hole mass -- stellar mass relation, black hole mass -- AGN luminosity relation, and redshift evolution of these quantities obtained from the model are qualitatively consistent with observations. Based on these results, we present upper limits on the expected number of sources for $z=5$ up to $z=15$ for scheduled JWST and \textit{Euclid} surveys, thus showcasing that empirical models can offer qualitative as well as quantitative prediction in a fast, easy and flexible manner that complements more computationally expensive approaches.

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。

↑