Bayesian matching for X-ray and infrared sources in the MYStIX project

Identifying the infrared counterparts of X-ray sources in Galactic plane fields such as those of the MYStIX project presents particular difficulties due to the high density of infrared sources. This high stellar density makes it inevitable that a large fraction of X-ray positions will have a faint field star close to them, which standard matching techniques may incorrectly take to be the counterpart. Instead we use the infrared data to create a model of both the field star and counterpart magnitude distributions, which we then combine with a Bayesian technique to yield a probability that any star is the counterpart of an X-ray source. In our more crowded fields, between 10% and 20% of counterparts that would be identified on the grounds of being the closest star to an X-ray position within a 99% confidence error circle are instead identified by the Bayesian technique as field stars. These stars are preferentially concentrated at faint magnitudes. Equally importantly the technique also gives a probability that the true counterpart to the X-ray source falls beneath the magnitude limit of the infrared catalog. In deriving our method, we place it in the context of other procedures for matching astronomical catalogs. © 2013. The American Astronomical Society. All rights reserved.The MYStIX project is supported at Penn State by NASA grant NNX09AC74G, NSF grant AST-0908038, and the Chandra ACIS Team contract SV4-74018 (G. Garmire & L. Townsley, Principal Investigators), issued by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS8-03060. This research made use of data products from the Chandra Data Archive and the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory (California Institute of Technology) under a contract with NASA

Big Data and the Internet of Things

Advances in sensing and computing capabilities are making it possible to embed increasing computing power in small devices. This has enabled the sensing devices not just to passively capture data at very high resolution but also to take sophisticated actions in response. Combined with advances in communication, this is resulting in an ecosystem of highly interconnected devices referred to as the Internet of Things - IoT. In conjunction, the advances in machine learning have allowed building models on this ever increasing amounts of data. Consequently, devices all the way from heavy assets such as aircraft engines to wearables such as health monitors can all now not only generate massive amounts of data but can draw back on aggregate analytics to "improve" their performance over time. Big data analytics has been identified as a key enabler for the IoT. In this chapter, we discuss various avenues of the IoT where big data analytics either is already making a significant impact or is on the cusp of doing so. We also discuss social implications and areas of concern.Comment: 33 pages. draft of upcoming book chapter in Japkowicz and Stefanowski (eds.) Big Data Analysis: New algorithms for a new society, Springer Series on Studies in Big Data, to appea

The MYStIX wide-field near-infrared data: Optimal photometry in crowded fields

We present JHK infrared data from the UK InfraRed Telescope (UKIRT) for a subset of the regions of the Massive Young Star-Forming Complex Study in Infrared and X-ray (MYStIX) survey. Some of the data were obtained specifically for the MYStIX project, and some as part of the UKIRT Infrared Deep Sky Survey's Galactic Plane Survey. In most of these fields, crowding is a significant issue for aperture photometry, and so we have re-extracted the photometry from the processed images using an optimal extraction technique, and we describe how we adapt the optimal technique to mitigate the effects of crowding. © 2013. The American Astronomical Society. All rights reserved.The MYStIX project is supported at Penn State by NASA grant NNX09AC74G, NSF grant AST-0908038, and the Chandra ACIS Team contract SV4-74018 (G. Garmire & L. Townsley, Principal Investigators), issued by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS8-03060. This research made use of data products from the Chandra Data Archive

On the role of magnetic reconnection in jet/accretion disk systems

The most accepted model for jet production is based on the magneto-centrifugal acceleration out off an accretion disk that surrounds the central source (Blandford & Payne, 1982). This scenario, however, does not explain, e.g., the quasi-periodic ejection phenomena often observed in different astrophysical jet classes. de Gouveia Dal Pino & Lazarian (2005) (hereafter GDPL) have proposed that the large scale superluminal ejections observed in microquasars during radio flare events could be produced by violent magnetic reconnection (MR) episodes. Here, we extend this model to other accretion disk systems, namely: active galactic nuclei (AGNs) and young stellar objects (YSOs), and also discuss its role on jet heating and particle acceleration.Comment: To be published in the IAU Highlights of Astronomy, Volume 15, XXVII IAU General Assembly, August 2009, Ian F. Corbett et al., eds., 201

Intracluster age gradients in numerous young stellar clusters

This is the final version of the article.Available from Oxford University Press via the DOI in this record.The pace and pattern of star formation leading to rich young stellar clusters is quite uncertain. In this context, we analyse the spatial distribution of ages within 19 young (median t ≲ 3 Myr on the Siess et al. time-scale), morphologically simple, isolated, and relatively rich stellar clusters. Our analysis is based on young stellar object (YSO) samples from the Massive Young Star-Forming Complex Study in Infrared and X-ray and Star Formation in Nearby Clouds surveys, and a new estimator of pre-main sequence (PMS) stellar ages, AgeJX, derived from X-ray and near-infrared photometric data. Median cluster ages are computed within four annular subregions of the clusters. We confirm and extend the earlier result of Getman et al. (2014): 80 per cent of the clusters show age trends where stars in cluster cores are younger than in outer regions. Our cluster stacking analyses establish the existence of an age gradient to high statistical significance in several ways. Time-scales vary with the choice of PMS evolutionary model; the inferred median age gradient across the studied clusters ranges from 0.75 to 1.5 Myr pc−1. The empirical finding reported in the present study – late or continuing formation of stars in the cores of star clusters with older stars dispersed in the outer regions – has a strong foundation with other observational studies and with the astrophysical models like the global hierarchical collapse model of Vázquez-Semadeni et al.The MYStIX project is now supported by the Chandra archive grant AR7-18002X. The SFiNCs project is supported at Penn State by NASA grant NNX15AF42G, Chandra GO grant SAO AR5-16001X, Chandra GO grant GO2-13012X, Chandra GO grant GO3-14004X, Chandra GO grant GO4-15013X, and the Chandra ACIS Team contract SV474018 (G. Garmire & L. Townsley, Principal Investigators), issued by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS8-03060. The Guaranteed Time Observations (GTO) data used here were selected by the ACIS Instrument Principal Investigator, Gordon P. Garmire, of the Huntingdon Institute for X-ray Astronomy, LLC, which is under contract to the Smithsonian Astrophysical Observatory; Contract SV2-82024. This research has made use of NASA's Astrophysics Data System Bibliographic Services and SAOImage DS9 software developed by Smithsonian Astrophysical Observatory

Star Formation in Nearby Clouds (SFiNCs): X-Ray and Infrared Source Catalogs and Membership

This is the final version of the article. Available from American Astronomical Society via the DOI in this record.The Star Formation in Nearby Clouds (SFiNCs) project is aimed at providing a detailed study of the young stellar populations and of star cluster formation in the nearby 22 star-forming regions (SFRs) for comparison with our earlier MYStIX survey of richer, more distant clusters. As a foundation for the SFiNCs science studies, here, homogeneous data analyses of the Chandra X-ray and Spitzer mid-infrared archival SFiNCs data are described, and the resulting catalogs of over 15,300 X-ray and over 1,630,000 mid-infrared point sources are presented. On the basis of their X-ray/infrared properties and spatial distributions, nearly 8500 point sources have been identified as probable young stellar members of the SFiNCs regions. Compared to the existing X-ray/mid-infrared publications, the SFiNCs member list increases the census of YSO members by 6%-200% for individual SFRs and by 40% for the merged sample of all 22 SFiNCs SFRs.The SFiNCs project is supported at Penn State by NASA grant NNX15AF42G, Chandra GO grant SAO AR5-16001X, Chandra GO grant GO2-13012X, Chandra GO grant GO3-14004X, Chandra GO grant GO4-15013X, Spitzer GO program 90179, and the Chandra-ACIS Team contract SV474018 (G. Garmire & L. Townsley, Principal Investigators), issued by the Chandra X-Ray Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS8-03060. he Guaranteed Time Observations (GTO) included here were selected by the ACIS Instrument Principal Investigator, Gordon P. Garmire, of the Huntingdon Institute for X-Ray Astronomy, LLC, which is under contract to the Smithsonian Astrophysical Observatory; Contract SV2-82024. This research made use of data products from the Chandra Data Archive and the Spitzer Space Telescope, which is operated by the Jet Propulsion Laboratory (California Institute of Technology) under a contract with NASA. This research used data products from the Two Micron All Sky Survey, which is a joint project of the University of Massachusetts and the Infrared Processing and Analysis Center/California Institute of Technology, funded by the National Aeronautics and Space Administration and the National Science Foundation. This research has also made use of NASA's Astrophysics Data System Bibliographic Services and SAOImage DS9 software developed by Smithsonian Astrophysical Observatory, and the SIMBAD database (operated at CDS, Strasbourg, France)

Circumstellar disc lifetimes in numerous galactic young stellar clusters

This is the final version of the article. Available from Oxford University Press via the DOI in this record.Photometric detections of dust circumstellar discs around pre-main sequence (PMS) stars, coupled with estimates of stellar ages, provide constraints on the time available for planet formation. Most previous studies on disc longevity, starting with Haisch, Lada & Lada, use star samples from PMS clusters but do not consider data sets with homogeneous photometric sensitivities and/or ages placed on a uniform time-scale. Here we conduct the largest study to date of the longevity of inner dust discs using X-ray and 1–8 µm infrared photometry from the MYStIX and SFiNCs projects for 69 young clusters in 32 nearby star-forming regions with ages t ≤ 5 Myr. Cluster ages are derived by combining the empirical AgeJX method with PMS evolutionary models, which treat dynamo-generated magnetic fields in different ways. Leveraging X-ray data to identify disc-free objects, we impose similar stellar mass sensitivity limits for disc-bearing and disc-free young stellar objects while extending the analysis to stellar masses as low as M ∼ 0.1 M⊙. We find that the disc longevity estimates are strongly affected by the choice of PMS evolutionary model. Assuming a disc fraction of 100 per cent at zero age, the inferred disc half-life changes significantly, from t1/2 ∼ 1.3–2 Myr to t1/2 ∼ 3.5 Myr when switching from non-magnetic to magnetic PMS models. In addition, we find no statistically significant evidence that disc fraction varies with stellar mass within the first few Myr of life for stars with masses <2 M⊙, but our samples may not be complete for more massive stars. The effects of initial disc fraction and star-forming environment are also explored.We thank the referee for his/her very helpful comments. We thank K. Luhman, E. Mamajek, M. Pecaut, G. Somers, and R. Jeffries for stimulating discussions. The MYStIX project is now supported by the Chandra archive grant AR7-18002X. The SFiNCs project is supported at Penn State by NASA grant NNX15AF42G, Chandra GO grant SAO AR5-16001X, Chandra GO grant GO2-13012X, Chandra GO grant GO3-14004X, Chandra GO grant GO4-15013X, and the Chandra ACIS Team contract SV474018 (G. Garmire and L. Townsley, Principal Investigators), issued by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS8-03060. The Guaranteed Time Observations (GTO) data used here were selected by the ACIS Instrument Principal Investigator, Gordon P. Garmire, of the Huntingdon Institute for X-ray Astronomy, LLC, which is under contract to the Smithsonian Astrophysical Observatory; Contract SV2-82024. This research has made use of NASA’s Astrophysics Data System Bibliographic Services and SAOImage DS9 software developed by Smithsonian Astrophysical Observatory

Young star clusters in nearby molecular clouds

This is the final version of the article. Available from Oxford University Press via the DOI in this record.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.The MYStIX project is now supported by the Chandra archive grant AR7-18002X. The SFiNCs project is supported at Penn State by NASA grant NNX15AF42G, Chandra GO grant SAO AR5- 16001X, Chandra GO grant GO2-13012X, Chandra GO grant GO3-14004X, Chandra GO grant GO4-15013X, and the Chandra ACIS Team contract SV474018 (G. Garmire and L. Townsley, Principal Investigators), issued by the Chandra X-ray Center, which is operated by the Smithsonian Astrophysical Observatory for and on behalf of NASA under contract NAS8-03060

New distance measures for classifying X-ray astronomy data into stellar classes

The classification of the X-ray sources into classes (such as extragalactic sources, background stars, ...) is an essential task in astronomy. Typically, one of the classes corresponds to extragalactic radiation, whose photon emission behaviour is well characterized by a homogeneous Poisson process. We propose to use normalized versions of the Wasserstein and Zolotarev distances to quantify the deviation of the distribution of photon interarrival times from the exponential class. Our main motivation is the analysis of a massive dataset from X-ray astronomy obtained by the Chandra Orion Ultradeep Project (COUP). This project yielded a large catalog of 1616 X-ray cosmic sources in the Orion Nebula region, with their series of photon arrival times and associated energies. We consider the plug-in estimators of these metrics, determine their asymptotic distributions, and illustrate their finite-sample performance with a Monte Carlo study. We estimate these metrics for each COUP source from three different classes. We conclude that our proposal provides a striking amount of information on the nature of the photon emitting sources. Further, these variables have the ability to identify X-ray sources wrongly catalogued before. As an appealing conclusion, we show that some sources, previously classified as extragalactic emissions, have a much higher probability of being young stars in Orion Nebula.Comment: 29 page

Age Gradients in the Stellar Populations of Massive Star Forming Regions Based on a New Stellar Chronometer

Accepted for publication in ApJ; 89 pages, 23 figures, 2 Tables; High quality version is at http://astro.psu.edu/mystixAuthor's accepted version of article published at http://dx.doi.org/10.1088/0004-637X/787/2/108A major impediment to understanding star formation in massive star forming regions (MSFRs) is the absence of a reliable stellar chronometer to unravel their complex star formation histories. We present a new estimation of stellar ages using a new method that employs near-infrared (NIR) and X-ray photometry, AgeJX. Stellar masses are derived from X-ray luminosities using the Lx - Mass relation from the Taurus cloud. J-band luminosities are compared to mass-dependent pre-main-sequence evolutionary models to estimate ages. AgeJX is sensitive to a wide range of evolutionary stages, from disk-bearing stars embedded in a cloud to widely dispersed older pre-main sequence stars. The MYStIX (Massive Young Star-Forming Complex Study in Infrared and X-ray) project characterizes 20 OB-dominated MSFRs using X-ray, mid-infrared, and NIR catalogs. The AgeJX method has been applied to 5525 out of 31,784 MYStIX Probable Complex Members. We provide a homogeneous set of median ages for over a hundred subclusters in 15 MSFRs; median subcluster ages range between 0.5 Myr and 5 Myr. The important science result is the discovery of age gradients across MYStIX regions. The wide MSFR age distribution appears as spatially segregated structures with different ages. The AgeJX ages are youngest in obscured locations in molecular clouds, intermediate in revealed stellar clusters, and oldest in distributed populations. The NIR color index J-H, a surrogate measure of extinction, can serve as an approximate age predictor for young embedded clusters