The predictive model for identifying the parameters of the feather vector of Milky Way galaxy strands through applying the theory of covariance functions

Abstract

We have analysed an opportunity to form a predictive model for identifying the parameters of the Milky Way galaxy strands feather vector upon applying the theory of covariance functions. The strands of spiral galaxies are connected by narrower gas strips (referred to as feathers). We used the data on the gas strips connecting the first strands of the Milky Way galaxy to perform the calculations. A square cut-out of a photograph of the said strip in a jpg format was transformed into a textual form using the developed software. The Doppler method and the theory of covariance functions were applied to analyse the measurement data arrays. The trends of the feather intensity vector were evaluated by applying the least squares method. The said procedure helped partially eliminate the random errors of the performed measurements as well. Upon changing the intensity of the feather vector parameters on a time scale, the estimates of the autocovariance and cross-covariance of parameters of the vector were calculated while varying the quantisation interval on a time scale. The average values of the parameter z in the Doppler formula were calculated with the formula using the expressions of the cross-covariance functions of the algebraic addition of the relevant vectors and a single vector. The software used for the calculations was developed in the MATLAB packages.