RT journal article
T1 Miec: A Bayesian hierarchical model for the analysis of nearby young open clusters
A1 Olivares, J.
A1 Bouy, H.
A1 Sarro, L.M.
A1 Moraux, E.
A1 Berihuete Macías, Ángel
A1 Galli, P. A. B.
A1 Miret-Roig, N.
A2 Estadística e Investigación Operativa
K1 proper motions
K1 methods: statistical
K1 open clusters and associations: general
K1 open clusters and associations: individual: M45
AB 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 itsss 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 A(v)similar to 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%).
PB EDP SCIENCES S A
SN 0004-6361
YR 2021
FD 2021-06
LK http://hdl.handle.net/10498/25325
UL http://hdl.handle.net/10498/25325
LA eng
DS Repositorio Institucional de la Universidad de Cádiz
RD 11-nov-2026