The SkyMapper Southern Sky Survey is carrying out a search for the most metal-poor stars in the Galaxy. It identifies candidates by way of its unique filter set which allows for estimation of stellar atmospheric parameters. The set includes a narrow filter centered on the Ca II K 3933 Å line, enabling a robust estimate of stellar metallicity. Promising candidates are then confirmed with spectroscopy. We present the analysis of Magellan Inamori Kyocera Echelle high-resolution spectroscopy of 122 metal-poor stars found by SkyMapper in the first two years of commissioning observations. Forty-one stars have These results demonstrate the ability to identify extremely metal-poor stars from SkyMapper photometry, pointing to increased sample sizes and a better characterization of the metal-poor tail of the halo metallicity distribution function in the future.

We report the discovery of one extremely metal-poor (EMP; [Fe/H]< −3) and one ultra metal-poor (UMP; [Fe/H]< −4) star selected from the SDSS/SEGUE survey. These stars were identified as EMP candidates based on their medium-resolution (R ∼ 2, 000) spectra, and were followed-up with high-resolution (R ∼ 35, 000) spectroscopy with the Magellan-Clay Telescope. Their derived chemical abundances exhibit good agreement with those of stars with similar metallicities. We also provide new insights on the formation of the UMP stars, based on comparison with a new set of theoretical models of supernovae nucleosynthesis. The models were matched with 20 UMP stars found in the literature, together with one of the program stars (SDSS J1204+1201), with [Fe/H] = −4.34. From fitting their abundances, we find that the supernovae progenitors, for stars where carbon and nitrogen are measured, had masses ranging from 20.5 M ⊙ to 28 M ⊙ , and explosion energies from 0.3 to 0.9×10 51 erg. These results are highly sensitive to the carbon and nitrogen abundance determinations, which is one of the main drivers for future high-resolution follow-up of UMP candidates. In addition, we are able to reproduce the different CNO abundance patterns found in UMP stars with a single progenitor type, by varying its mass and explosion energy.1 Based on observations gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile

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We report on the serendipitous observations of Solar System objects imaged during the High cadence Transient Survey (HiTS) 2014 observation campaign. Data from this high cadence, wide field survey was originally analyzed for finding variable static sources using Machine Learning to select the mostlikely candidates. In this work we search for moving transients consistent with Solar System objects and derive their orbital parameters. We use a simple, custom detection algorithm to link trajectories and assume Keplerian motion to derive the asteroid's orbital parameters. We use known asteroids from the Minor Planet Center (MPC) database to assess the detection efficiency of the survey and our search algorithm. Trajectories have an average of nine detections spread over 2 days, and our fit yields typical errors of σ a ∼ 0.07 AU, σ e ∼ 0.07 and σ i ∼ 0. • 5 deg in semi-major axis, eccentricity, and inclination respectively for known asteroids in our sample. We extract 7,700 orbits from our trajectories, identifying 19 near Earth objects, 6,687 asteroids, 14 Centaurs, and 15 trans-Neptunian objects. This highlights the complementarity of supernova wide field surveys for Solar System research and the significance of machine learning to clean data of false detections. It is a good example of the data-driven science that LSST will deliver.