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Information × Registration Number 0223U004569, 0122U200209 , R & D reports Title Observational indicators of active processes in galaxies in different environments popup.stage_title Head Vavylova Iryna B., Доктор фізико-математичних наук Registration Date 20-11-2023 Organization Main Astronomical Observatory of the National Academy of Sciences of Ukraine popup.description2 For galaxies with active nuclei (AGN), 1) an estimate of the rates of matter accretion to supermassive black holes was made in comparison with the same estimates for AGN at higher redshifts for SDSS survey galaxies; 2) models of the energy distribution of isolated galaxies with active nuclei have been developed, which have the same observational feature of excess radiation in the soft X-band; 3) the feedback hypothesis (cyclicity of the process of gas heating to keV temperatures and its cooling to molecular temperatures) was confirmed for elliptical galaxies and central galaxies of galaxy clusters according to data from the X-observatory Chandra.For galaxies with active and degenerate star formation 1) the parametric dependence "stellar mass – metallicity – star formation rate" was obtained taking into account the age of the stellar population of ∼200,000 galaxies with active star formation in the Local Universe (z<0.25) from the SDSS survey; 2) estimates of the influence of the frequency of supernova events on star formation processes using the example of galaxy NGC6946 were confirmed and obtained; 3) for the first time, new features of the radiation fluxes of isolated galaxies with faint nuclear activity in the radio and X-spectral bands were obtained, depending on the type of galaxy activity determined from the optical band data; 4) refined estimates of the ratio of mass to luminosity of isolated galaxies of early and late type based on updated data for their non-significant dwarf satellites in different spectral ranges, five new dwarf galaxies in the M101 galaxy group were discovered. Based on the results of the project, new methods were created and methods already developed by the authors were improved; in particular, the morphological features of 140,000 faint galaxies at z<0.1 were obtained for the first time using machine learning methods (CNN) and the corresponding catalog of these data was published. Product Description popup.authors Babyk Yurii V. Vavylova Iryna B. Vasylenko Anatoliy A. Vasylenko Maksym Yurijovych Dobrycheva Daria V. Karachentseva Valentina Yu. Kompaniiets Olena V Piliuhin Leonid S. Pulatova Nadiia H. Sergijenko Olga M. Torbaniuk Olena O. popup.nrat_date 2023-11-20 Close