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Register a new userMiec: A Bayesian hierarchical model for the analysis of nearby young open clusters
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Context. The analysis of luminosity and mass distributions of young stellar clusters is essential to understanding the star-formation process. However, the gas and dust left over by this process extinct the light of the newborn stars and can severely bias both the census of cluster members and its luminosity distribution. Aims. We aim to develop a Bayesian methodology to infer, with minimal biases due to photometric extinction, the candidate members and magnitude distributions of embedded young stellar clusters. Methods. We improve a previously published methodology and extend its application to embedded stellar clusters. We validate the method using synthetically extincted data sets of the Pleiades cluster with varying degrees of extinction. Results. Our methodology can recover members from data sets extincted up to Av ~ 6 mag with accuracies, true positive, and contamination rates that are better than 99%, 80%, and 9%, respectively. Missing values hamper our methodology by introducing contaminants and artifacts into the magnitude distributions. Nonetheless, these artifacts vanish through the use of informative priors in the distribution of the proper motions. Conclusions. The methodology presented here recovers, with minimal biases, the members and distributions of embedded stellar clusters from data sets with a high percentage of sources with missing values (>96%).
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Hierarchical mergers are one of the distinctive signatures of binary black hole (BBH) formation through dynamical evolution. Here, we present a fast semi-analytic approach to simulate hierarchical mergers in nuclear star clusters (NSCs), globular clusters (GCs) and young star clusters (YSCs). Hierarchical mergers are more common in NSCs than they are in both GCs and YSCs, because of the different escape velocity. The mass distribution of hierarchical BBHs strongly depends on the properties of first-generation BBHs, such as their progenitors metallicity. In our fiducial model, we form black holes (BHs) with masses up to $sim{}10^3$ M$_odot$ in NSCs and up to $sim{}10^2$ M$_odot$ in both GCs and YSCs. When escape velocities in excess of 100 km~s$^{-1}$ are considered, BHs with mass $>10^3$ M$_odot$ are allowed to form in NSCs. Hierarchical mergers lead to the formation of BHs in the pair instability mass gap and intermediate-mass BHs, but only in metal-poor environments. The local BBH merger rate in our models ranges from $sim{}10$ to $sim{} 60$ Gpc$^{-3}$ yr$^{-1}$; hierarchical BBHs in NSCs account for $sim{}10^{-2}- 0.2$ Gpc$^{-3}$ yr$^{-1}$, with a strong upper limit of $sim{}10$ Gpc$^{-3}$ yr$^{-1}$. When comparing our models with the second gravitational-wave transient catalog, we find that multiple formation channels are favored to reproduce the observed BBH population.
Star clusters appear to be the ideal environment for the assembly of neutron star-neutron star (NS-NS) and black hole-neutron star (BH-NS) binaries. These binaries are among the most interesting astrophysical objects, being potential sources of gravitational waves (GWs) and gamma-ray bursts. We use for the first time high-precision N-body simulations of young massive and open clusters to study the origin and dynamical evolution of NSs, within clusters with different initial masses, metallicities, primordial binary fractions, and prescriptions for the compact object natal kicks at birth. We find that the radial profile of NSs is shaped by the BH content of the cluster, which partially quenches the NS segregation due to the BH-burning process. This leaves most of the NSs out of the densest cluster regions, where NS-NS and BH-NS binaries could potentially form. Due to a large velocity kick that they receive at birth, most of the NSs escape the host clusters, with the bulk of their retained population made up of NSs of $sim 1.3$ M$_odot$ coming from the electron-capture supernova process. The details of the primordial binary fraction and pairing can smear out this trend. Finally, we find that a subset of our models produce NS-NS mergers, leading to a rate of $sim 0.01$--$0.1$ Gpc$^{-3}$ yr$^{-1}$ in the local Universe, and compute an upper limit of $sim 3times 10^{-2}$--$3times 10^{-3}$ Gpc$^{-3}$ yr$^{-1}$ for the BH-NS merger rate. Our estimates are several orders of magnitude smaller than the current empirical merger rate from LIGO/Virgo, in agreement with the recent rate estimates for old globular clusters.
Understanding the formation and evolution of our Galaxy requires accurate distances, ages and chemistry for large populations of field stars. Here we present several updates to our spectro-photometric distance code, that can now also be used to estimate ages, masses, and extinctions for individual stars. Given a set of measured spectro-photometric parameters, we calculate the posterior probability distribution over a given grid of stellar evolutionary models, using flexible Galactic stellar-population priors. The code (called {tt StarHorse}) can acommodate different observational datasets, prior options, partially missing data, and the inclusion of parallax information into the estimated probabilities. We validate the code using a variety of simulated stars as well as real stars with parameters determined from asteroseismology, eclipsing binaries, and isochrone fits to star clusters. Our main goal in this validation process is to test the applicability of the code to field stars with known {it Gaia}-like parallaxes. The typical internal precision (obtained from realistic simulations of an APOGEE+Gaia-like sample) are $simeq 8%$ in distance, $simeq 20%$ in age,$simeq 6 %$ in mass, and $simeq 0.04$ mag in $A_V$. The median external precision (derived from comparisons with earlier work for real stars) varies with the sample used, but lies in the range of $simeq [0,2]%$ for distances, $simeq [12,31]%$ for ages, $simeq [4,12]%$ for masses, and $simeq 0.07$ mag for $A_V$. We provide StarHorse distances and extinctions for the APOGEE DR14, RAVE DR5, GES DR3 and GALAH DR1 catalogues.
We developed a code that estimates distances to stars using measured spectroscopic and photometric quantities. We employ a Bayesian approach to build the probability distribution function over stellar evolutionary models given these data, delivering estimates of model parameters for each star individually. The code was first tested on simulations, successfully recovering input distances to mock stars with <1% bias.The method-intrinsic random distance uncertainties for typical spectroscopic survey measurements amount to around 10% for dwarf stars and 20% for giants, and are most sensitive to the quality of $log g$ measurements. The code was validated by comparing our distance estimates to parallax measurements from the Hipparcos mission for nearby stars (< 300 pc), to asteroseismic distances of CoRoT red giant stars, and to known distances of well-studied open and globular clusters. The external comparisons confirm that our distances are subject to very small systematic biases with respect to the fundamental Hipparcos scale (+0.4 % for dwarfs, and +1.6% for giants). The typical random distance scatter is 18% for dwarfs, and 26% for giants. For the CoRoT-APOGEE sample, the typical random distance scatter is ~15%, both for the nearby and farther data. Our distances are systematically larger than the CoRoT ones by about +9%, which can mostly be attributed to the different choice of priors. The comparison to known distances of star clusters from SEGUE and APOGEE has led to significant systematic differences for many cluster stars, but with opposite signs, and with substantial scatter. Finally, we tested our distances against those previously determined for a high-quality sample of giant stars from the RAVE survey, again finding a small systematic trend of +5% and an rms scatter of 30%.
A cluster finding method was developed and applied in four Local Group Galaxies (SMC, M31, M33 and NGC 6822). The aim is to study the young stellar population of these galaxies by identifying stellar structures in small and large scales. Also our aim is to assess the potential of using the observations of ESAs space mission Gaia for the study of nearby galaxies resolved in stars. The detection method used is a Hierarchical technique based on a modified friends of friends algorithm. The identified clusters are classified in five distinct categories according to their size. The data for our study were used from two ground based surveys, the Local Group Galaxy Survey and the Maggelanic Clouds Spectroscopic Survey. Relatively young main sequence stars were selected from the stellar catalogs and were used by the detection algorithm. Multiple young stellar structures were identified in all galaxies with size varying from very small scales of a few pc up to scales larger than 1 kpc. The same cluster finding method was used in six spiral galaxies observed with the Hubble Space Telescope in a previous study. The average size in each category of the identified structures in the Local Group galaxies presents values consistent with the identified structures in the relatively distant spiral galaxies. Most of the structures consist of stars within the observational limits of Gaias instruments. It is expected that Gaias observations will contribute significantly on the study of the young stellar population of nearby galaxies.
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