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Young Star Clusters in Nearby Molecular Clouds MNRAS 477, 298–324 (2018) doi:10.1093/mnras/sty473 Advance Access publication 2018 February 22 Young star clusters in nearby molecular clouds K. V. Getman,1‹ M. A. Kuhn,2,3 E. D. Feigelson,1 P. S. Broos,1 M. R. Bate4 andG.P.Garmire5 1Department of Astronomy and Astrophysics, Pennsylvania State University, 525 Davey Laboratory, University Park, PA 16802, USA 2Instituto de Fisica y Astronomia, Universidad de Valparaiso, Gran Bretana 1111, Playa Ancha, Valparaiso, Chile 3Millennium Institute of Astrophysics, Av. Vicuna Mackenna 4860, 782-0436 Macul, Santiago, Chile 4Department of Physics and Astronomy, University of Exeter, Stocker Road, Exeter, Devon EX4 4QL, UK 5Huntingdon Institute for X-ray Astronomy, LLC, 10677 Franks Road, Huntingdon, PA 16652, USA Accepted 2018 February 19. Received 2018 February 13; in original form 2017 December 31 ABSTRACT The SFiNCs (Star Formation in Nearby Clouds) project is an X-ray/infrared study of the young stellar populations in 22 star-forming regions with distances 1 kpc designed to extend our earlier MYStIX (Massive Young Star-Forming Complex Study in Infrared and X-ray) survey of more distant clusters. Our central goal is to give empirical constraints on cluster formation mechanisms. Using parametric mixture models applied homogeneously to the catalogue of SFiNCs young stars, we identify 52 SFiNCs clusters and 19 unclustered stellar structures. The procedure gives cluster properties including location, population, morphology, association with molecular clouds, absorption, age (AgeJX), and infrared spectral energy distribution (SED) slope. Absorption, SED slope, and AgeJX are age indicators. SFiNCs clusters are examined individually, and collectively with MYStIX clusters, to give the following results. (1) SFiNCs is dominated by smaller, younger, and more heavily obscured clusters than MYStIX. (2) SFiNCs cloud-associated clusters have the high ellipticities aligned with their host molecular filaments indicating morphology inherited from their parental clouds. (3) The effect of cluster expansion is evident from the radius–age, radius–absorption, and radius–SED correlations. Core radii increase dramatically from ∼0.08 to ∼0.9 pc over the age range 1–3.5 Myr. Inferred gas removal time-scales are longer than 1 Myr. (4) Rich, spatially distributed stellar populations are present in SFiNCs clouds representing early generations of star formation. An appendix compares the performance of the mixture models and non-parametric minimum spanning tree to identify clusters. This work is a foundation for future SFiNCs/MYStIX studies including disc longevity, age gradients, and dynamical modelling. Key words: stars: early-type – stars: formation – stars: pre-main-sequence – open clusters and associations: general – infrared: stars – X-rays: stars. But the formation mechanisms of rich clusters are still under 1 INTRODUCTION study. Dozens of sophisticated numerical (radiation)-(magneto)- Most stars in the Galaxy were formed in compact bound stellar clus- hydrodynamic simulations of the collapse and fragmentation of tur- ters (Lada & Lada 2003) or distributed, unbound stellar associations bulent molecular clouds followed by cluster formation have been (Kruijssen 2012). Short-lived radioisotopic daughter nuclei in the published (Krumholz et al. 2014; Dale 2015). The inclusion of Solar system meteorites indicate that our Sun formed in a modest- stellar feedback is generally found to better reproduce important sized cluster on the edge of a massive OB-dominated molecular characteristics of star formation such as the stellar initial mass cloud complex (Gounelle & Meynet 2012;Pfalzneretal.2015). function (IMF; Bate 2009;Offneretal.2009; Krumholz, Dekel & It is well accepted that most clusters quickly expand and disperse McKee 2012), gas depletion time, and star formation efficiency upon the removal of the residual molecular gas via stellar feedback (SFE; Krumholz et al. 2014;Vazquez-Semadeni,´ Gonzalez-´ so only a small fraction survive as bound open clusters (Tutukov Samaniego & Col´ın 2017). 1978; Krumholz et al. 2014). Constraints can be imposed on the simulations through quantita- tive comparison with the detailed properties of large cluster sam- ples. For instance, realistic simulations of stellar clusters in the E-mail: [email protected] solar neighbourhood, such as Bate (2009, 2012), are anticipated C 2018 The Author(s) Downloaded from https://academic.oup.com/mnras/article-abstract/477/1/298/4898079Published by Oxford University Press on behalf of the Royal Astronomical Society by University of Exeter user on 16 May 2018 Young star clusters 299 to obey the empirical cluster mass–size relationship seen in in- Briefly, this analysis investigates the distribution of a set of frared (IR) cluster catalogues (Carpenter 2000;Lada&Lada2003), points X ={x1,...,xN } giving the (RA,Dec.) coordinates of X-ray/IR catalogues (Kuhn et al. 2014, 2015b; Kuhn, Getman & each YSO. Each point belongs to one of k clusters,ortoan Feigelson 2015a), and compilations of massive stellar clusters unclustered component of scattered stars characterized by com- (Portegies Zwart, McMillan & Gieles 2010; Pfalzner & Kaczmarek plete spatial randomness. Each cluster is described by the prob- 2013;Pfalzneretal.2016). ability density function g(x; θ j ), where θ j is the set of pa- Our effort called MYStIX, Massive Young Star-Forming Com- rameters for the component. Mixture models of point processes plex Study in Infrared and X-ray, produces a large and homoge- commonly use a normal (Gaussian) function (McLachlan & neous data set valuable for the analysis of clustered star formation Peel 2000; Fraley & Raftery 2002; Kuhn & Feigelson 2017). (Feigelson et al. 2013; Feigelson 2018, http://astro.psu.edu/mystix). But, following Kuhn et al. (2014), we choose g to be a two- MYStIX identified >30 000 young discless (X-ray selected) and dimensional isothermal ellipsoid defined in their equation (4). disc-bearing (IR excess selected) stars in 20 massive star-forming This is the radial profile of a dynamically relaxed, isothermal, self- regions (SFRs) at distances from 0.4 to 3.6 kpc. Using quantitative gravitating system where the stellar surface density has a roughly flat statistical methods, Kuhn et al. (2014) identify over 140 MYS- core and power-law halo. The effectiveness of the isothermal ellip- tIX clusters with diverse morphologies, from simple ellipsoids to soidal model is shown in Section 4.2 below for SFiNCs and by Kuhn elongated, clumpy substructures. Getman et al. (2014a) and Get- et al. (2014, 2017) for other young clusters. The relative contribution { } man, Feigelson & Kuhn (2014b) develop a new X-ray/IR age stel- of each cluster is given by mixing coefficients a1,...,ak ,where lar chronometer and discover spatio-age gradients across MYStIX 0 ≤ a ≤ 1and k a = 1. The distribution of the full sample j j=1 j SFRs and within individual clusters. Kuhn et al. (2015a,b)derive k+1 θ f (x) is then the sum of the k cluster components, j=1 aj g(x; j ), various cluster properties, discover wide ranges of the cluster sur- and a constant representing the unclustered component. face stellar density distributions, and provide empirical signs of The mixture model is fitted to the (RA,Dec.) point distribution for dynamical evolution and cluster expansion/merger. each SFiNCs field from Getman et al. (2017) by maximum likeli- More recently, the Star Formation in Nearby Clouds (SFiNCs) hood estimation. Each cluster has six parameters, θ = {x0, y0, Rc, , project (Getman et al. 2017) extends the MYStIX effort to an archive φ, c}: coordinates of cluster centre (x0, y0), isothermal core radius study of 22 generally nearer and smaller SFRs where the stellar Rc defined as the harmonic mean of the semimajor and semiminor clusters are often dominated by a single massive star – typically axes, ellipticity , position angle φ, and central stellar surface den- a late-O or early-B – rather than by numerous O stars as in the sity c. The full model, including the unclustered surface density, MYStIX fields. Utilizing the MYStIX-based X-ray and IR data has 6k + 1 parameters. The density in our chosen model never analysis methods, Getman et al. produce a catalogue of nearly 8500 vanishes at large distances from the cluster centre. However, the discless and disc-bearing young stars in SFiNCs fields. One of our absence of a parameter for the outer truncation radius in our model objectives is to perform analyses similar to those of MYStIX in order does not strongly affect the results, because the spatial distribution to examine whether the behaviours of clustered star formation are of the MYStIX and SFiNCs stars is examined over a finite field of similar – or different – in smaller (SFiNCs) and giant (MYStIX) view. The core radius parameter can be better constrained than the molecular clouds. truncation radius (e.g. Kroupa, Aarseth & Hurley 2001), and our In the current paper, the MYStIX-based parametric method for previous work shows that inclusion of a truncation radius parameter identifying clusters using finite mixture models (Kuhn et al. 2014) is not necessary to get a good fit (e.g. Kuhn et al. 2010). is applied to the young stellar SFiNCs sample. 52 SFiNCs clus- To reduce unnecessary computation on the entire parameter ters and 19 unclustered stellar structures are identified across the space, an initial superset of possible cluster components is obtained 22 SFiNCs SFRs. Various basic SFiNCs stellar structure proper- by visual examination of the YSO adaptively smoothed surface
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