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Reconstructing the Universe: Testing the Mutual Consistency of the Pantheon and SDSS/eBOSS BAO Data Sets with Gaussian Processes

Keeley et al. (2021)

Ryan E. Keeley #1 Lead Arman Shafieloo #2 Corresponding Hanwool Koo #5 Co-author
THE ASTRONOMICAL JOURNAL IF 5.84 A 등급 International collaboration
HPC(High-Performance Clusters)

Abstract

We test the mutual consistency between the baryon acoustic oscillation measurements from the eBOSS SDSS final release and the Pantheon supernova compilation in a model-independent fashion using Gaussian process regression. We also test their joint consistency with the ΛCDM model in a model-independent fashion. We also use Gaussian process regression to reconstruct the expansion history that is preferred by these two data sets. While this methodology finds no significant preference for model flexibility beyond ΛCDM, we are able to generate a number of reconstructed expansion histories that fit the data better than the best-fit ΛCDM model. These example expansion histories may point the way toward modifications to ΛCDM. We also constrain the parameters Ωk and H0rd both with ΛCDM and with Gaussian process regression. We find that H0rd = 10,030 ± 130 km s-1 and Ωk = 0.05 ± 0.10 for ΛCDM and that H0rd = 10,040 ± 140 km s-1 and Ωk = 0.02 ± 0.20 for the Gaussian process case.

AI Classification

Maturity Tier

Tier 1 — Classical ML

AI Role

parameter-estimation

supporting

Techniques

gaussian-process

Tasks

regression/parameter-estimation

Subfield

cosmology

tabular-catalog

Flags

Develops AI method
· Classification confidence: 90%