Show simple item record

dc.contributor.authorBarentsen, G.
dc.contributor.authorDrew, J.E.
dc.contributor.authorVink, J.S.
dc.contributor.authorSale, S.E.
dc.date.accessioned2013-06-05T07:00:54Z
dc.date.available2013-06-05T07:00:54Z
dc.date.issued2013-01-01
dc.identifier.citationBarentsen , G , Drew , J E , Vink , J S & Sale , S E 2013 , ' Bayesian inference of T Tauri star properties using multi-wavelength survey photometry ' , Monthly Notices of the Royal Astronomical Society , vol. 429 , no. 3 , pp. 1981-2000 . https://doi.org/10.1093/mnras/sts462
dc.identifier.issn0035-8711
dc.identifier.otherPURE: 1743932
dc.identifier.otherPURE UUID: 0c6e342f-7a76-4a7c-af10-4c2779fc26ab
dc.identifier.otherScopus: 84874025444
dc.identifier.urihttp://hdl.handle.net/2299/10696
dc.description.abstractThere are many pertinent open issues in the area of star and planet formation. Large statistical samples of young stars across star-forming regions are needed to trigger a breakthrough in our understanding, but most optical studies are based on a wide variety of spectrographs and analysis methods, which introduces large biases. Here we show how graphical Bayesian networks can be employed to construct a hierarchical probabilistic model which allows pre-main-sequence ages, masses, accretion rates and extinctions to be estimated using two widely available photometric survey data bases (Isaac Newton Telescope Photometric Ha Survey r/Ha/i and Two Micron All Sky Survey J-band magnitudes). Because our approach does not rely on spectroscopy, it can easily be applied to homogeneously study the large number of clusters for which Gaia will yield membership lists. We explain how the analysis is carried out using the Markov chain Monte Carlo method and provide PYTHON source code. We then demonstrate its use on 587 known low-mass members of the star-forming region NGC 2264 (Cone Nebula), arriving at a median age of 3.0 Myr, an accretion fraction of 20±2 per cent and a median accretion rate of 10 Myr. The Bayesian analysis formulated in this work delivers results which are in agreement with spectroscopic studies already in the literature, but achieves this with great efficiency by depending only on photometry. It is a significant step forward from previous photometric studies because the probabilistic approach ensures that nuisance parameters, such as extinction and distance, are fully included in the analysis with a clear picture on any degeneraciesen
dc.format.extent20
dc.language.isoeng
dc.relation.ispartofMonthly Notices of the Royal Astronomical Society
dc.titleBayesian inference of T Tauri star properties using multi-wavelength survey photometryen
dc.contributor.institutionSchool of Physics, Astronomy and Mathematics
dc.contributor.institutionScience & Technology Research Institute
dc.contributor.institutionCentre for Astrophysics Research
dc.description.statusPeer reviewed
rioxxterms.versionSMUR
rioxxterms.versionofrecordhttps://doi.org/10.1093/mnras/sts462
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record