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- W2937830625 abstract "The aim of this work is to investigate the characteristics of the young stellar population in the spiral galaxy NGC 247. In particular, we focused our attention in its hierarchical clustering distributions and the properties of the smallest groups. We used multiband Hubble Space Telescope (HST) data from three fields covering more than half of NGC 247 to select the young population. Then, through the path linkage criterion (PLC), we found compact young star groups, and estimated their fundamental parameters, such as their stellar densities, sizes, amount of members and luminosity function (LF) slopes. We also performed a fractal analysis to determinate the clustering properties of this population. We build a stellar density map and the corresponding dendrograms corresponding to the galactic young population to detect large structures and draw their main characteristics. We detected 339 young star groups, for which we computed a mean radius of $sim$ 60 pc and a maximum in the size distribution between 30 and 70 pc. We also obtained LF slopes with a bimodal distribution showing peaks at $sim$ 0.1 and $sim$ 0.2. We identified several candidates to HII regions which follow an excellent spatial correlation with the young groups found by the PLC. We observed that the young population are hierarchically organized, where the smaller and denser structures are within larger and less dense ones. We noticed that all these groups presented a fractal subclustering, following the hierarchical distribution observed in the corresponding stellar density map. For the large young structures observed in this map, we obtained a fractal dimension of $sim$ 1.6-1.8 using the perimeter-area relation and the cumulative size distribution. These values are consistent with a scenario of hierarchical star formation." @default.
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- W2937830625 date "2019-04-22" @default.
- W2937830625 modified "2023-10-06" @default.
- W2937830625 title "The young stellar population in NGC 247 Main properties and hierarchical clustering" @default.
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