3,667 research outputs found

    Assessing the Milky Way Satellites Associated with the Sagittarius Dwarf Spheroidal Galaxy

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    Numerical models of the tidal disruption of the Sagittarius (Sgr) dwarf galaxy have recently been developed that for the first time simultaneously satisfy most observational constraints on the angular position, distance, and radial velocity trends of both leading and trailing tidal streams emanating from the dwarf. We use these dynamical models in combination with extant 3-D position and velocity data for Galactic globular clusters and dSph galaxies to identify those Milky Way satellites that are likely to have originally formed in Sgr and been stripped from it during its extended interaction with the Milky Way. We conclude that the globular clusters Arp 2, M 54, NGC 5634, Terzan 8, and Whiting 1 are likely associated with the Sgr dwarf, and that Berkeley 29, NGC 5053, Pal 12, and Terzan 7 may be as well. The initial Sgr system therefore may have contained 5-9 globular clusters, corresponding to a specific frequency S_N = 5 - 9 for an initial Sgr luminosity M_V = -15.0. Our result is consistent with the 8\pm2 Sgr globular clusters expected from statistical modeling of the Galactic globular cluster distribution and the corresponding false-association rate due to chance alignments with the Sgr streams. These clusters are consistent with previous reconstructions of the Sgr age-metallicity relation, and show no evidence for a second-parameter effect shaping their horizontal branch morphologies. We find no statistically significant evidence to suggest that any of the recently discovered population of ultra-faint dwarf galaxies are conclusively associated with the Sgr tidal streams. (Abridged).Comment: 25 pages, 12 figures. Accepted for publication in ApJ. Version with full-resolution figures is available at http://www.astro.ucla.edu/~drlaw/Papers/Sgr_clusters.pd

    Physical Properties of a Pilot Sample of Spectroscopic Close Pair Galaxies at z ~ 2

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    We use Hubble Space Telescope Wide-Field Camera 3 (HST/WFC3) rest-frame optical imaging to select a pilot sample of star-forming galaxies in the redshift range z = 2.00-2.65 whose multi-component morphologies are consistent with expectations for major mergers. We follow up this sample of major merger candidates with Keck/NIRSPEC longslit spectroscopy obtained in excellent seeing conditions (FWHM ~ 0.5 arcsec) to obtain Halpha-based redshifts of each of the morphological components in order to distinguish spectroscopic pairs from false pairs created by projection along the line of sight. Of six pair candidates observed, companions (estimated mass ratios 5:1 and 7:1) are detected for two galaxies down to a 3sigma limiting emission-line flux of ~ 10^{-17} erg/s/cm2. This detection rate is consistent with a ~ 50% false pair fraction at such angular separations (1-2 arcsec), and with recent claims that the star-formation rate (SFR) can differ by an order of magnitude between the components in such mergers. The two spectroscopic pairs identified have total SFR, SFR surface densities, and stellar masses consistent on average with the overall z ~ 2 star forming galaxy population.Comment: 11 pages, 5 figures. Accepted for publication in Ap

    The inner structure and kinematics of the Sagittarius dwarf galaxy as a product of tidal stirring

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    The tidal stirring model envisions the formation of dwarf spheroidal (dSph) galaxies in the Local Group via the tidal interaction of disky dwarf systems with a larger host galaxy like the Milky Way. These progenitor disks are embedded in extended dark halos and during the evolution both components suffer strong mass loss. In addition, the disks undergo the morphological transformation into spheroids and the transition from ordered to random motion of their stars. Using collisionless N-body simulations we construct a model for the nearby and highly elongated Sagittarius (Sgr) dSph galaxy within the framework of the tidal stirring scenario. Constrained by the present known orbit of the dwarf, the model suggests that in order to produce the majority of tidal debris observed as the Sgr stream, but not yet transform the core of the dwarf into a spherical shape, Sgr must have just passed the second pericenter of its current orbit around the Milky Way. In the model, the stellar component of Sgr is still very elongated after the second pericenter and morphologically intermediate between the strong bar formed at the first pericenter and the almost spherical shape existing after the third pericenter. This is thus the first model of the evolution of the Sgr dwarf that accounts for its observed very elliptical shape. At the present time there is very little intrinsic rotation left and the velocity gradient detected along the major axis is almost entirely of tidal origin. We model the recently measured velocity dispersion profile for Sgr assuming that mass traces light and estimate its current total mass within 5 kpc to be 5.2 x 10^8 M_sun. To have this mass at present, the model requires that the initial virial mass of Sgr must have been as high as 1.6 x 10^10 M_sun, comparable to that of the Large Magellanic Cloud, which may serve as a suitable analog for the pre-interaction, Sgr progenitor.Comment: 14 pages, 14 figures, minor changes to match the version published in Ap

    Cluster, Classify, Regress: A General Method For Learning Discountinous Functions

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    This paper presents a method for solving the supervised learning problem in which the output is highly nonlinear and discontinuous. It is proposed to solve this problem in three stages: (i) cluster the pairs of input-output data points, resulting in a label for each point; (ii) classify the data, where the corresponding label is the output; and finally (iii) perform one separate regression for each class, where the training data corresponds to the subset of the original input-output pairs which have that label according to the classifier. It has not yet been proposed to combine these 3 fundamental building blocks of machine learning in this simple and powerful fashion. This can be viewed as a form of deep learning, where any of the intermediate layers can itself be deep. The utility and robustness of the methodology is illustrated on some toy problems, including one example problem arising from simulation of plasma fusion in a tokamak.Comment: 12 files,6 figure
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