SLUG IV: A Novel Forward-Modelling Method to Derive the Demographics of Star Clusters

Krumholz, M.R.; Adamo, A.; Fumagalli, M.; Calzetti, D.

doi:10.1093/mnras/sty2896

SLUG IV: A Novel Forward-Modelling Method to Derive the Demographics of Star Clusters

Krumholz, M.R.; Adamo, A.; Fumagalli, M.; Calzetti, D.

Authors

M.R. Krumholz

A. Adamo

Professor Michele Fumagalli michele.fumagalli@durham.ac.uk
Academic Visitor

D. Calzetti

Abstract

We describe a novel method for determining the demographics of a population of star clusters, for example distributions of cluster mass and age, from unresolved photometry. This method has a number of desirable properties: it fully exploits all the information available in a data set without any binning, correctly accounts for both measurement error and sample incompleteness, naturally handles heterogenous data (for example fields that have been imaged with different sets of filters or to different depths), marginalises over uncertain extinctions, and returns the full posterior distributions of the parameters describing star cluster demographics. We demonstrate the method using mock star cluster catalogs and show that our method is robust and accurate, and that it can recover the demographics of star cluster populations significantly better than traditional fitting methods. For realistic sample sizes, our method is sufficiently powerful that its accuracy is ultimately limited by the accuracy of the underlying physical models for stellar evolution and interstellar dust, rather than by statistical uncertainties. Our method is implemented as part of the Stochastically Lighting Up Galaxies (slug) stellar populations code, and is freely available.

Citation

Krumholz, M., Adamo, A., Fumagalli, M., & Calzetti, D. (2019). SLUG IV: A Novel Forward-Modelling Method to Derive the Demographics of Star Clusters. Monthly Notices of the Royal Astronomical Society, 482(3), 3550-3566. https://doi.org/10.1093/mnras/sty2896

Journal Article Type	Article
Acceptance Date	Oct 23, 2018
Online Publication Date	Oct 27, 2018
Publication Date	Jan 21, 2019
Deposit Date	Nov 21, 2018
Publicly Available Date	Nov 21, 2018
Journal	Monthly Notices of the Royal Astronomical Society
Print ISSN	0035-8711
Electronic ISSN	1365-2966
Publisher	Royal Astronomical Society
Peer Reviewed	Peer Reviewed
Volume	482
Issue	3
Pages	3550-3566
DOI	https://doi.org/10.1093/mnras/sty2896

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This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society © 2018 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.