| Name: | Ujjwal Kumar Upadhyay |
| Affiliation: | Indian Institute of Science |
| Conference ID : | ASI2024_551 |
| Title : | Non-linear regression with errors on both axes and its implications on Hubble tension |
| Authors : | Ujjwal Kumar Upadhyay 1,2 Tarun Deep Saini 1 |
| Authors Affiliation: | 1 Indian Institute of Science, Bangalore- 560012, India
2 Raman Research Institute, Bangalore-560080, India |
| Mode of Presentation: | Poster |
| Abstract Category : | Galaxies and Cosmology |
| Abstract : | While fitting a non-linear model to data, it is common to consider errors only in the dependent vari-
able, and treat other variables as perfectly measured. A more flexible model fitting considering errors
in independent variables is expected to better estimate the parameters of the model from the same
data. We employ a Bayesian method to consider redshift errors in the Pantheon sample of Type-Ia
supernovae, and find that it improves the ΛCDM fit to the data. We are investigating the implications
of this method on cosmological tension in the value of Hubble constant H0 with presently available
data and with simulated data of larger volume and better quality expected to be available in the future. |
