Open-cluster density profiles derived using a kernel estimator
Anton F. Seleznev

TL;DR
This paper introduces a kernel estimator method to derive open-cluster density profiles, assesses their structural features, and compares results with models and previous studies, revealing extended clusters and mass segregation.
Contribution
It presents a novel kernel estimator approach for deriving open-cluster density profiles and evaluates their structural parameters using observational data and models.
Findings
Open-cluster radii are largely insensitive to kernel half-width.
Evidence of stellar mass segregation and non-stationarity in clusters.
Extended corona around NGC 6939 confirmed.
Abstract
Surface and spatial radial density profiles in open clusters are derived using a kernel estimator method. Formulae are obtained for the contribution of every star into the spatial density profile. The evaluation of spatial density profiles is tested against open-cluster models from N-body experiments with N = 500. Surface density profiles are derived for seven open clusters (NGC 1502, 1960, 2287, 2516, 2682, 6819 and 6939) using Two-Micron All-Sky Survey data and for different limiting magnitudes. The selection of an optimal kernel half-width is discussed. It is shown that open-cluster radius estimates hardly depend on the kernel half-width. Hints of stellar mass segregation and structural features indicating cluster non-stationarity in the regular force field are found. A comparison with other investigations shows that the data on open-cluster sizes are often underestimated. The…
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