标题： 晚期时间转换的$M_B$通过神经网络推断 显示英文标题

标题： Late-time transition of $M_B$ inferred via neural networks

摘要： 宇宙学参数中的紧张关系加剧促使重新审视标准宇宙学的基本方面。 哈勃常数的紧张也可以看作是局部和早期宇宙对Ia型超新星绝对星等$M_B$的约束之间的紧张。 在本工作中，我们以模型无关的方式重新考虑该参数变化的可能性。 我们使用神经网络无偏地约束绝对星等的值，并评估从Pantheon+数据集中的红移变化对$M_B$的影响和统计显著性，同时对神经网络架构进行深入分析。 我们发现在一个$z\approx 1$区域存在一个过渡红移的迹象。 显示英文摘要

摘要： The strengthening of tensions in the cosmological parameters has led to a reconsideration of fundamental aspects of standard cosmology. The tension in the Hubble constant can also be viewed as a tension between local and early Universe constraints on the absolute magnitude $M_B$ of Type Ia supernova. In this work, we reconsider the possibility of a variation of this parameter in a model-independent way. We employ neural networks to agnostically constrain the value of the absolute magnitude as well as assess the impact and statistical significance of a variation in $M_B$ with redshift from the Pantheon+ compilation, together with a thorough analysis of the neural network architecture. We find an indication for a transition redshift at the $z\approx 1$ region.