A New Diagnostic Method for Assessment of Stellar Stratification in Star Clusters
Dimitrios A. Gouliermis, Richard de Grijs, Yu Xin

TL;DR
This paper introduces a novel, model-independent method using the mean-square radius to detect stellar stratification in star clusters, validated through simulations and Hubble data, offering a reliable diagnostic tool.
Contribution
It presents the first application of a dynamically stable radius for assessing stellar stratification, independent of models or theoretical predictions.
Findings
Method effectively detects stellar stratification in simulated clusters.
Results are robust against data variations if contamination and incompleteness are managed.
Applicable to real observational data with reliable results.
Abstract
We propose a new method for the characterization of stellar stratification in stellar systems. The method uses the mean-square radius (also called the Spitzer radius) of the system as a diagnostic tool. An estimate of the observable counterpart of this radius for stars of different magnitude ranges is used as the effective radius of each stellar species in a star cluster. We explore the dependence of these radii on magnitude as a possible indication of stellar stratification. This method is the first of its kind to use a dynamically stable radius, and though seemingly trivial it has never been applied before. We test the proposed method using model star clusters, which are constructed to be segregated on the basis of a Monte Carlo technique, and on Hubble Space Telescope observations of mass-segregated star clusters in order to explore the limitations of the method in relation to actual…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
