| Abstract [eng] |
In this study we present algorithm for modelling 3D star clusters and their images. Grid of models which in parameter space covers M31 clusters observed in PHAT survey was generated. In total, 50000 artificial 3D star clusters were generated, their images were simulated in 3 photometric passbands, projecting into 2D from 13 different directions. Aperture photometry was performed on these simulated cluster images, curves of growth were measured. Based on these measurements, we investigated influence of star distribution stochastic effects onto cluster photometric and structural parameters. Aim of the study – investigate stochasticity of star cluster structural and photometric parameters. Main tasks: Create algorithm and computer programs for modelling 3D star clusters and their images resembling real clusters of M31 observed in PHAT survey. Determine the effects of bright stars and their spatial distribution stochasticity on accuracy of cluster structural and photometric parameters. Main conclusions: In case of young (10–100 Myr) and low mass (10^2-10^4 M_⊙) clusters spread of colour indices can reach up to several magnitudes due to stochastic effects of bright stars. This can lead to inaccurately determined cluster physical parameters. Due to effects of observation angle, low mass clusters can exhibit spread of color indices up to several tenths of magnitude, which exceed statistical uncertainties of photometric measurements. Due to bright star spatial distribution stochasticity, young low mass clusters show large uncertainties of structural parameters. In the context of PHAT survey, spread of r_h can reach up to >3.5 pc. In the case of some 10^2-10^3 M_⊙ clusters, their radial surface brightness profile can be dominated by few or even one bright star. The same cluster observed from different angles can exhibit drastically different radial surface brightness profile, and in the case of youngest clusters, their sizes when observing from different directions can differ up to even 1.8 pc. |
