Mass composition anisotropy with the Telescope Array Surface Detector data

Mass composition anisotropy is predicted by a number of theories describing sources of ultrahigh-energy cosmic rays. Event-by-event determination of a type of a primary cosmic-ray particle is impossible due to large shower-to-shower fluctuations, and the mass composition usually is obtained by averaging over some composition-sensitive observable determined independently for each extensive air shower (EAS) over a large number of events. In the present study we propose to employ the observable xi used in the TA mass composition analysis for the mass composition anisotropy analysis. The xi variable is determined with the use of Boosted Decision Trees (BDT) technique trained with the Monte-Carlo sets, and the xi value is assigned for each event, where xi = -1 corresponds to an event initiated by the primary iron nuclei and xi = 1 corresponds to a proton event. Use of xi distributions obtained for the Monte-Carlo sets allows us to separate proton and iron candidate events from a data set with some given accuracy and study its distributions over the observed part of the sky. Results for the TA SD 11-year data set mass composition anisotropy will be presented.