All Weather Calibration of Wide Field Optical and NIR Surveys

The science goals for ground-based large-area surveys, such as the Dark Energy Survey, Pan-STARRS, and the Large Synoptic Survey Telescope, require calibration of broadband photometry that is stable in time and uniform over the sky to precisions of a per cent or better. This performance will need to be achieved with data taken over the course of many years, and often in less than ideal conditions. This paper describes a strategy to achieve precise internal calibration of imaging survey data taken in less than photometric conditions, and reports results of an observational study of the techniques needed to implement this strategy. We find that images of celestial fields used in this case study with stellar densities of order one per arcmin-squared and taken through cloudless skies can be calibrated with relative precision of 0.5 per cent (reproducibility). We report measurements of spatial structure functions of cloud absorption observed over a range of atmospheric conditions, and find it possible to achieve photometric measurements that are reproducible to 1 per cent in images that were taken through cloud layers that transmit as little as 25 per cent of the incident optical flux (1.5 magnitudes of extinction). We find, however, that photometric precision below 1 per cent is impeded by the thinnest detectable cloud layers. We comment on implications of these results for the observing strategies of future surveys.Comment: Accepted for publication in The Astronomical Journal (AJ

Inclusive pion - proton scattering

The reactions {pi}+ p {yields} {pi}+ {hor_ellipsis} and {pi}+ p {yields} K+ {hor_ellipsis} will be studied over a wide range of the Feynman variables X, Q and S in order to test the conjectured scaling law for hadron collisions and study the form of the yield distributions. Particular attention will be paid to the vicinity of X = 0. The experiment will be carried out with a simple one-magnet spectrometer which takes full advantage of the kinematics and has wide acceptance and the capability of high precision

Parametrization and Classification of 20 Billion LSST Objects: Lessons from SDSS

The Large Synoptic Survey Telescope (LSST) will be a large, wide-field ground-based system designed to obtain, starting in 2015, multiple images of the sky that is visible from Cerro Pachon in Northern Chile. About 90% of the observing time will be devoted to a deep-wide-fast survey mode which will observe a 20,000 deg{sup 2} region about 1000 times during the anticipated 10 years of operations (distributed over six bands, ugrizy). Each 30-second long visit will deliver 5{sigma} depth for point sources of r {approx} 24.5 on average. The co-added map will be about 3 magnitudes deeper, and will include 10 billion galaxies and a similar number of stars. We discuss various measurements that will be automatically performed for these 20 billion sources, and how they can be used for classification and determination of source physical and other properties. We provide a few classification examples based on SDSS data, such as color classification of stars, color-spatial proximity search for wide-angle binary stars, orbital-color classification of asteroid families, and the recognition of main Galaxy components based on the distribution of stars in the position-metallicity-kinematics space. Guided by these examples, we anticipate that two grand classification challenges for LSST will be (1) rapid and robust classification of sources detected in difference images, and (2) simultaneous treatment of diverse astrometric and photometric time series measurements for an unprecedentedly large number of objects