Abstract
Context. Star clusters, composed of stars born from the same molecular cloud, serve as invaluable natural laboratories for understanding the fundamental processes governing stellar formation and evolution. Aims. This study aims to investigate correlations between the Mean Interdistance (D i), Mean Closest Interdistance (D c) and Median Weighted Central Interdistance (D cc) with the age of star clusters, examining their evolutionary trends and assessing the robustness of these quantities as possible age indicators. Methods. We selected a sample of open clusters in the solar region and with a representative number of members (e.g. well populated and without outliers). The interdistances are derived from the spatial distribution of member stars within a cluster. Their evolution over time allows us to use them as age indicators for star clusters. Results. Our investigation reveals a high-significant correlation between the interdistances and cluster age. Considering the full sample of clusters between 7 and 9 kpc, the relationship is very broad. This is due to uncertainties in parallax, which increase with increasing distance. In particular, we must limit the sample to a maximum distance from the Sun of about 200 pc to avoid artificial effects on cluster shape and on the spatial distribution of their stars along the line of sight. Conclusions. By conservatively restraining the distance to a maximum of ~200 pc, we have established a relationship between the interdistances and the age of the clusters. In our sample, the relationship is mainly driven by the internal expansion of the clusters and is marginally affected by external perturbative effects. Such relation might enhance our comprehension of cluster dynamics and might be used to derive cluster dynamical ages.
| Original language | English |
|---|---|
| Article number | A268 |
| Number of pages | 16 |
| Journal | Astronomy & Astrophysics |
| Volume | 689 |
| Early online date | 20 Sept 2024 |
| DOIs | |
| Publication status | Published - Sept 2024 |
Funding
This work made use of Astropy (Astropy Collaboration 2018), Scikit-learn Machine Learning (Pedregosa et al. 2011), Scipy (Virtanen et al. 2020), Seaborn (Waskom 2021), TopCat (Taylor 2005), Statsmodels (Seabold & Perktold 2010), Pandas (The pandas development team 2020) and Matplotlib (Hunter 2007). CVV and LM thank the EU programme Erasmus+ Staff Mobility for their support. CVV, LM, SR, LS thank INAF for the support (MiniGrant Checs, Large Grant EPOCH). LM and SR acknowledge financial support under the National Recovery and Resilience Plan (NRRP), Mission 4, Component 2, Investment 1.1, Call for tender No. 104 published on 2.2.2022 by the Italian Ministry of University and Research (MUR), funded by the European Union \u2013 NextGenerationEU\u2013 Project \u2018Cosmic POT\u2019 Grant Assignment Decree No. 2022X4TM3H by the Italian Ministry of Ministry of University and Research (MUR). CVV and GT acknowledge funding from the Research Council of Lithuania (LMTLT, grant No. P-MIP-23-24). This work benefited from fruitful discussions during the Workshop \u2018Form star cluster to field population\u2019 held in Firenze (Italy), November 2023. We thank the anonymous referee for useful comments that enriched the paper considerably. This work made use of Astropy (Astropy Collaboration 2018), Scikit-learn Machine Learning (Pedregosa et al. 2011), Scipy (Virtanen et al. 2020), Seaborn (Waskom 2021), TopCat (Taylor 2005), Statsmodels (Seabold & Perktold 2010), Pandas (The pandas development team 2020) and Matplotlib (Hunter 2007). CVV and LM thank the EU programme Erasmus+ Staff Mobility for their support. CVV, LM, SR, LS thank INAF for the support (MiniGrant Checs, Large Grant EPOCH). LM and SR acknowledge financial support under the National Recovery and Resilience Plan (NRRP), Mission 4, Component 2, Investment 1.1, Call for tender No. 104 published on 2.2.2022 by the Italian Ministry of University and Research (MUR), funded by the European Union - NextGenerationEU- Project 'Cosmic POT' Grant Assignment Decree No. 2022X4TM3H by the Italian Ministry of Ministry of University and Research (MUR). CVV and GT acknowledge funding from the Research Council of Lithuania (LMTLT, grant No. P-MIP-23-24). This work benefited from fruitful discussions during the Workshop 'Form star cluster to field population' held in Firenze (Italy), November 2023. We thank the anonymous referee for useful comments that enriched the paper considerably.
Austrian Fields of Science 2012
- 103004 Astrophysics
- 103003 Astronomy
Keywords
- Astrophysics - Astrophysics of Galaxies
- Galaxy: disk
- Galaxy: kinematics and dynamics
- Open clusters and associations: general
- Galaxy: abundances
- Galaxy: evolution
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