On the degeneracy between tension and its Gaussian process forecasting
arXiv:2203.03574 · doi:10.3390/universe8080394
Abstract
In this paper we reconstruct the growth and evolution of the cosmic structure of the Universe using Markov Chain Monte Carlo algorithms for Gaussian processes [1]. We estimate the difference between the reconstructions that are calculated through a maximization of the kernel hyperparameters and those that are obtained with a complete exploration of the parameter space. We find that the difference between these two approaches is of the order of . Furthermore, we compare our results with those obtained by Planck Collaboration 2018 assuming a CDM model and we do not find a statistically significant difference in the redshift range were the reconstructions of have been made.
7 pages, 2 figures. Accepted in Universe
References in corpus (12)
- A Comprehensive Measurement of the Local Value of the Hubble Constant with 1 km/s/Mpc Uncertainty from the Hubble Space Telescope and the SH0ES Team
- Dark Energy Survey Year 3 Results: Cosmological Constraints from Galaxy Clustering and Weak Lensing
- Dark Energy Survey Year 3 Results: Cosmology from Cosmic Shear and Robustness to Data Calibration
- Dark Energy Survey Year 3 Results: Cosmology from Cosmic Shear and Robustness to Modeling Uncertainty
- Arbitrating the discrepancy with growth rate measurements from Redshift-Space Distortions
- KiDS+VIKING-450 and DES-Y1 combined: Mitigating baryon feedback uncertainty with COSEBIs
- Neural Network Reconstruction of Late-Time Cosmology and Null Tests
- Reconstructing teleparallel gravity with cosmic structure growth and expansion rate data
- Optimising growth of structure constraints on modified gravity
- Model-independent constraints on and from the link between geometry and growth
- Multi-tasking the growth of cosmological structures
- Improving data-driven model-independent reconstructions and updated constraints on dark energy models from Horndeski cosmology