No description available.

Variable emission from Sgr A*, the luminous counterpart to the super-massive black hole at the center of our Galaxy, arises from the innermost portions of the accretion flow. Better characterization of the variability is important for constraining models of the low-luminosity accretion mode powering Sgr A*, and could further our ability to use variable emission as a probe of the strong gravitational potential in the vicinity of the 4 x 10(6) M-circle dot black hole. We use the Herschel Spectral and Photometric Imaging Receiver (SPIRE) to monitor Sgr. A* at wavelengths that are difficult or impossible to observe from the ground. We find highly significant variations at 0.25, 0.35, and 0.5 mm, with temporal structure that is highly correlated across these wavelengths. While the variations correspond to < 1% changes in the total intensity in the Herschel beam containing Sgr. A*, comparison to independent, simultaneous observations at 0.85 mm strongly supports the reality of the variations. The lowest point in the light curves, similar to 0.5 Jy below the time-averaged flux density, places a lower bound on the emission of Sgr. A* at 0.25 mm, the first such constraint on the THz portion of the spectral energy distribution. The variability on few hour timescales in the SPIRE light curves is similar to that seen in historical 1.3 mm data, where the longest time series is available, but the distribution of variations in the sub-mm do not show a tail of large-amplitude variations seen at 1.3 mm. Simultaneous X-ray photometry from XMM-Newton shows no significant variation within our observing period, which may explain the lack of very large submillimeter variations in our data if X-ray and submillimeter flares are correlated.

Closure phases along different baseline triangles carry a large amount of information regarding the structures of the images of black holes in interferometric observations with the Event Horizon Telescope. We use long time span, high cadence, GRMHD+radiative transfer models of Sgr A* to investigate the expected variability of closure phases in such observations. We find that, in general, closure phases along small baseline triangles show little variability, except in the cases when one of the triangle vertices crosses one of the small regions of low visibility amplitude. The closure phase variability increases with the size of the baseline triangle, as larger baselines probe the small-scale structures of the images, which are highly variable. On average, the funnel-dominated MAD models show less closure phase variability than the disk-dominated SANE models, even in the large baseline triangles, because the images from the latter are more sensitive to the turbulence in the accretion flow. Our results suggest that image reconstruction techniques need to explicitly take into account the closure phase variability, especially if the quality and quantity of data allow for a detailed characterization of the nature of variability. This also implies that, if image reconstruction techniques that rely on the assumption of a static image are utilized, regions of the u-v space that show a high level of variability will need to be identified and excised.

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius. A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore the robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.

The Apache Point Observatory Galactic Evolution Experiment (APOGEE) has built the largest moderately high-resolution (R approximate to 22,500) spectroscopic map of the stars across the Milky Way, and including dust-obscured areas. The APOGEE Stellar Parameter and Chemical Abundances Pipeline (ASPCAP) is the software developed for the automated analysis of these spectra. ASPCAP determines atmospheric parameters and chemical abundances from observed spectra by comparing observed spectra to libraries of theoretical spectra, using. 2 minimization in a multidimensional parameter space. The package consists of a FORTRAN90 code that does the actual minimization and a wrapper IDL code for book-keeping and data handling. This paper explains in detail the ASPCAP components and functionality, and presents results from a number of tests designed to check its performance. ASPCAP provides stellar effective temperatures, surface gravities, and metallicities precise to 2%, 0.1 dex, and 0.05 dex, respectively, for most APOGEE stars, which are predominantly giants. It also provides abundances for up to 15 chemical elements with various levels of precision, typically under 0.1 dex. The final data release (DR12) of the Sloan Digital Sky Survey III contains an APOGEE database of more than 150,000 stars. ASPCAP development continues in the SDSS-IV APOGEE-2 survey.