A possible late-time transition of $M_B$ inferred via neural networks

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Hauptverfasser: Mukherjee, Purba, Dialektopoulos, Konstantinos F., Said, Jackson Levi, Mifsud, Jurgen
Format: Preprint
Veröffentlicht: 2024
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author Mukherjee, Purba
Dialektopoulos, Konstantinos F.
Said, Jackson Levi
Mifsud, Jurgen
author_facet Mukherjee, Purba
Dialektopoulos, Konstantinos F.
Said, Jackson Levi
Mifsud, Jurgen
contents 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 possible transition redshift at the $z\approx 1$ region.
format Preprint
id arxiv_https___arxiv_org_abs_2402_10502
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A possible late-time transition of $M_B$ inferred via neural networks
Mukherjee, Purba
Dialektopoulos, Konstantinos F.
Said, Jackson Levi
Mifsud, Jurgen
Cosmology and Nongalactic Astrophysics
Machine Learning
General Relativity and Quantum Cosmology
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 possible transition redshift at the $z\approx 1$ region.
title A possible late-time transition of $M_B$ inferred via neural networks
topic Cosmology and Nongalactic Astrophysics
Machine Learning
General Relativity and Quantum Cosmology
url https://arxiv.org/abs/2402.10502