Speaker
Mr
Ujjwal Kumar Upadhyay
(Indian Institute of Science, Raman Research Institute)
Description
While fitting a non-linear model to data, it is common to consider errors only in the dependent variable 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 $\Lambda$CDM fit to the data. We are investigating the implications of this method on cosmological tension in the value of Hubble constant $H_0$ with presently available data and with simulated data of larger volume and better quality expected to be available in the future.
ujjwalu@iisc.ac.in | |
Affiliation | Indian Institution of Science |
Author
Mr
Ujjwal Kumar Upadhyay
(Indian Institute of Science, Raman Research Institute)
Co-author
Dr
Tarun Deep Saini
(Indian Institute of Science)