CIGaRS I: Combined simulation-based inference from SNae Ia and host photometry
Konstantin Karchev and Roberto Trotta and Raul Jimenez
使用Ia型超新星(SNae Ia)作为宇宙学探测器需要经验校正,这与它们的宿主环境相关。 我们提出了一个统一的贝叶斯分层模型,旨在从纯粹的光度观测中推断出SN Ia亮度对祖源特性(金属性年龄)的内在依赖性,延迟时间分布(DTD)作为年龄函数的速率,以及宇宙学,以及所有宿主的红移。 该模型结合了基于物理的恒星形成和从Prospector-beta的化学进化,星系和SN光的尘埃灭绝以及观测选择效应。 我们通过模拟表明,对金属性和年龄的内在依赖性具有不同的观测特征,金属性模仿了SN Ia量级在≈10^10 M_⊙的宿主恒星质量中众所周知的步骤。 然后,我们展示了基于神经模拟的从模拟观测16000 SNae Ia及其主机到红移0.9的所有模型参数的推断。 我们基于物理的联合方法提供强大而精确的光度红移(<0.01中位散射)和改进的宇宙学约束,解锁光度数据的全部能力,并为LSST时代的端到端模拟分析管道铺平道路。
Using type Ia supernovae (SNae Ia) as cosmological probes requires empirical corrections, which correlate with their host environment. We present a unified Bayesian hierarchical model designed to infer, from purely photometric observations, the intrinsic dependence of SN Ia brightness on progenitor properties (metallicity age), the delay-time distribution (DTD) that governs their rate as a function of age, and cosmology, as well as the redshifts of all hosts. The model incorporates physics-based...