http://arxiv.org/abs/2209.00549
In this work, a computer optimization model has been developed that allows one to load the initial observation data of supernovae 1a into a table and, simply, by searching for the best fit between observations and theory, obtain the values of the parameters of cosmological models. Naturally, the initial data are redshifts z and apparent magnitudes m at the maximum brightness of supernovae. For better fit between theory and observation, Pearson’s Chi2 (Chi-squared) goodness-of-fit test was used. The results are obtained for the LCDM model and, for comparison, the model with a zero cosmological constant. In order to improve the fit between observed data and theory, the optimization is carried out assuming that the absolute magnitude of supernovae is not constant, but evolves with time. It is assumed that the dependence of the absolute magnitude on the redshift is linear: M=M(z=0)+ez, where e is the evolution coefficient of the absolute magnitude of type 1a supernovae.
A. Mahtessian, G. Karapetian, M. Hovhannisyan, et. al.
Fri, 2 Sep 22
1/62
Comments: 17 pages, 8 figures, 12 tables
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