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Thuan T.X.,University of Virginia | Bauer F.E.,University of Santiago de Chile | Bauer F.E.,Millennium Institute of Astrophysics | Bauer F.E.,Space Science Institute | Izotov Y.I.,Ukrainian Academy of Sciences
Monthly Notices of the Royal Astronomical Society | Year: 2014

We present XMM-Newton and Chandra observations of two low-metallicity cometary blue compact dwarf (BCD) galaxies, Mrk 59 and Mrk 71. The first BCD, Mrk 59, contains two ultraluminous X-ray sources (ULXs), IXO 72 and IXO 73, both associated with bright massivestars and HII complexes, as well as one fainter extended source associated with a massive HII complex at the head of the cometary structure. The low metallicity of Mrk 59 appears to be responsible for the presence of the two ULXs. IXO 72 has varied little over thelast 10 yr, while IXO 73 has demonstrated a variability factor of ~4 over the same period. The second BCD, Mrk 71, contains two faint X-ray point sources and two faint extendedsources. One point source is likely a background AGN, while the other appears to be coincident with a very luminous star and a compact HII region at the 'head' of the cometary structure. The two faint extended sources are also associated with massive HII complexes. Although both BCDs have the same metallicity, the three sources in Mrk 71 have X-ray luminosities ~1-2 orders of magnitude fainter than those in Mrk 59. The age of the starburst may play a role. © 2014 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.

Pejcha O.,Princeton University | Prieto J.L.,Diego Portales University | Prieto J.L.,Millennium Institute of Astrophysics
Astrophysical Journal | Year: 2015

Hydrogen-rich Type II-Plateau supernovae (SNe) exhibit correlations between the plateau luminosity Lpl, the nickel mass MNi, the explosion energy Eexp, and the ejecta mass Mej. Using our global, self-consistent, multi-band model of nearby well-observed SNe, we find that the covariances of these quantities are strong and that the confidence ellipsoids are oriented in the direction of the correlations, which reduces their significance. By proper treatment of the covariance matrix of the model, we discover a significant intrinsic width to the correlations between Lpl, Eexp and MNi, where the uncertainties due to the distance and the extinction dominate. For fixed Eexp, the spread in MNi is about 0.25 dex, which we attribute to the differences in the progenitor internal structure. We argue that the effects of incomplete γ-ray trapping are not important in our sample. Similarly, the physics of the Type II-Plateau SN light curves leads to inherently degenerate estimates of Eexp and Mej, which makes their observed correlation weak. Ignoring the covariances of SN parameters or the intrinsic width of the correlations causes significant biases in the slopes of the fitted relations. Our results imply that Type II-Plateau SN explosions are not described by a single physical parameter or a simple one-dimensional trajectory through the parameter space, but instead reflect the diversity of the core and surface properties of their progenitors. We discuss the implications for the physics of the explosion mechanism and possible future observational constraints. © 2015. The American Astronomical Society. All rights reserved.

Pejcha O.,Princeton University | Prieto J.L.,Diego Portales University | Prieto J.L.,Millennium Institute of Astrophysics
Astrophysical Journal | Year: 2015

We present a new self-consistent and versatile method that derives photospheric radius and temperature variations of Type II-Plateau supernovae based on their expansion velocities and photometric measurements. We apply the method to a sample of 26 well-observed, nearby supernovae with published light curves and velocities. We simultaneously fit ∼230 velocity and ∼6800 mag measurements distributed over 21 photometric passbands spanning wavelengths from 0.19 to 2.2 μm. The light-curve differences among the Type II-Plateau supernovae are well modeled by assuming different rates of photospheric radius expansion, which we explain as different density profiles of the ejecta, and we argue that steeper density profiles result in flatter plateaus, if everything else remains unchanged. The steep luminosity decline of Type II-Linear supernovae is due to fast evolution of the photospheric temperature, which we verify with a successful fit of SN 1980K. Eliminating the need for theoretical supernova atmosphere models, we obtain self-consistent relative distances, reddenings, and nickel masses fully accounting for all internal model uncertainties and covariances.We use our global fit to estimate the time evolution of any missing band tailored specifically for each supernova, and we construct spectral energy distributions and bolometric light curves. We produce bolometric corrections for all filter combinations in our sample. We compare our model to the theoretical dilution factors and find good agreement for the B and V filters. Our results differ from the theory when the I, J, H, or K bands are included. We investigate the reddening law toward our supernovae and find reasonable agreement with standard script RV ∼ 3.1 reddening law in UBVRI bands. Results for other bands are inconclusive. We make our fitting code publicly available. © 2015. The American Astronomical Society. All rights reserved.

Harrison C.M.,Durham University | Thomson A.P.,Durham University | Alexander D.M.,Durham University | Bauer F.E.,University of Santiago de Chile | And 6 more authors.
Astrophysical Journal | Year: 2015

We present multi-frequency (1-8 GHz) Very Large Array data, combined with VIsible MultiObject Spectrograph integral field unit data and Hubble Space Telescope imaging, of a z = 0.085 radio-quiet type 2 quasar (with L 1.4 GHz 5 × 1023 W Hz-1 and L AGN 2 × 1045 erg s-1). Due to the morphology of its emission-line region, the target (J1430+1339) has been referred to as the "Teacup" active galactic nucleus (AGN) in the literature. We identify "bubbles" of radio emission that are extended 10-12 kpc to both the east and west of the nucleus. The edge of the brighter eastern bubble is co-spatial with an arc of luminous ionized gas. We also show that the "Teacup" AGN hosts a compact radio structure, located 0.8 kpc from the core position, at the base of the eastern bubble. This radio structure is co-spatial with an ionized outflow with an observed velocity of v = -740 km s-1. This is likely to correspond to a jet, or possibly a quasar wind, interacting with the interstellar medium at this position. The large-scale radio bubbles appear to be inflated by the central AGN, which indicates that the AGN can also interact with the gas on ≳ 10 kpc scales. Our study highlights that even when a quasar is formally "radio-quiet" the radio emission can be extremely effective for observing the effects of AGN feedback. © 2015. The American Astronomical Society. All rights reserved..

Huijse P.,Millennium Institute of Astrophysics | Estevez P.A.,University of Chile | Protopapas P.,Harvard University | Principe J.C.,University of Florida | Zegers P.,University of Los Andes, Chile
IEEE Computational Intelligence Magazine | Year: 2014

Time-domain astronomy (TDA) is facing a paradigm shift caused by the exponential growth of the sample size, data complexity and data generation rates of new astronomical sky surveys. For example, the Large Synoptic Survey Telescope (LSST), which will begin operations in northern Chile in 2022, will generate a nearly 150 Petabyte imaging dataset of the southern hemisphere sky. The LSST will stream data at rates of 2 Terabytes per hour, effectively capturing an unprecedented movie of the sky. The LSST is expected not only to improve our understanding of time-varying astrophysical objects, but also to reveal a plethora of yet unknown faint and fast-varying phenomena. To cope with a change of paradigm to data-driven astronomy, the fields of astroinformatics and astrostatistics have been created recently. The new data-oriented paradigms for astronomy combine statistics, data mining, knowledge discovery, machine learning and computational intelligence, in order to provide the automated and robust methods needed for the rapid detection and classification of known astrophysical objects as well as the unsupervised characterization of novel phenomena. In this article we present an overview of machine learning and computational intelligence applications to TDA. Future big data challenges and new lines of research in TDA, focusing on the LSST, are identified and discussed from the viewpoint of computational intelligence/machine learning. Interdisciplinary collaboration will be required to cope with the challenges posed by the deluge of astronomical data coming from the LSST. © 2014 IEEE.

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