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Global survey of star clusters in the Milky Way VIII. Cluster formation and evolution (2503.14480v2)

Published 18 Mar 2025 in astro-ph.GA

Abstract: We consider tidal masses and ages of Milky Way open clusters, as well as a simple model of their distribution. Our aim is to investigate the space of model parameters and the correspondence between modelled and observed two-dimensional cluster age-mass distributions. The model for cluster evolution is comprised of a two-section cluster initial mass function, constant cluster formation rate, and a mass loss function. This mass loss function represents a supervirial phase after gas expulsion, mass loss due to stellar evolution, and gradual dissolution driven by internal dynamics and the Galactic tidal field. We construct different estimators of model fitness based on $\chi2$-statistics, the Kullback-Leibler divergence (KLD) and a maximum-likelihood approach. Using these estimators and Markov Chain Monte Carlo sampling, we obtain best-fit values and posterior distributions for a selection of model parameters. The KLD returns a superior model compared to the other statistics. The cluster initial mass function is well constrained and we find a clear signature of an enhanced cluster mass loss in the first 50 Myr. In the KLD best model, clusters lose 72% of their initial mass in the violent relaxation phase, after which cluster mass loss slows down, allowing for a relatively low rate of cluster formation of $0.088\mathrm{M_\odot kpc{-2} Gyr{-1}}$. The observed upper limit of cluster ages at approx. 5 Gyr is reflected in the model by a shallow lifetime-mass relation for clusters with initial masses above $1000\mathrm{M_\odot}$. The application of the model to an independent cluster sample based on Gaia DR3 data yields similar results except for a systematic shift in age. The observed cluster age-mass distribution is compatible with a constant cluster formation rate. The enhanced number of young massive clusters observed requires an early violent relaxation phase of strong mass loss.

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