Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
SLUG IV: a novel forward-modelling method to derive the demographics of star clusters
Stockholm University, Faculty of Science, Department of Astronomy. Stockholm University, Faculty of Science, The Oskar Klein Centre for Cosmo Particle Physics (OKC). Centre of Excellence for Astronomy in Three Dimensions (ASTRO-3D), Australia.
Number of Authors: 42019 (English)In: Monthly notices of the Royal Astronomical Society, ISSN 0035-8711, E-ISSN 1365-2966, Vol. 482, no 3, p. 3550-3566Article in journal (Refereed) Published
Abstract [en]

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 (e.g. fields that have been imaged with different sets of filters or to different depths), marginalizes over uncertain extinctions, and returns the full posterior distributions of the parameters describing star cluster demographics. We demonstrate the method using mock star cluster catalogues 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.

Place, publisher, year, edition, pages
2019. Vol. 482, no 3, p. 3550-3566
Keywords [en]
methods, data analysis, methods: statistical, techniques: photometric, galaxies: star clusters: general
National Category
Astronomy, Astrophysics and Cosmology
Identifiers
URN: urn:nbn:se:su:diva-168473DOI: 10.1093/mnras/sty2896ISI: 000462312600049PubMedID: 30662096OAI: oai:DiVA.org:su-168473DiVA, id: diva2:1313121
Available from: 2019-05-02 Created: 2019-05-02 Last updated: 2019-05-02Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Krumholz, Mark R.Adamo, AngelaFumagalli, Michele
By organisation
Department of AstronomyThe Oskar Klein Centre for Cosmo Particle Physics (OKC)
In the same journal
Monthly notices of the Royal Astronomical Society
Astronomy, Astrophysics and Cosmology

Search outside of DiVA

GoogleGoogle Scholar

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf