Time filter

Source Type

Tucson, AZ, United States

Dindar S.,University of Florida | Ford E.B.,University of Florida | Juric M.,LSST Corporation | Juric M.,University of Arizona | And 5 more authors.
New Astronomy | Year: 2013

We present Swarm-NG, a C++ library for the efficient direct integration of many n-body systems using a Graphics Processing Unit (GPU), such as NVIDIA's Tesla T10 and M2070 GPUs. While previous studies have demonstrated the benefit of GPUs for n-body simulations with thousands to millions of bodies, Swarm-NG focuses on many few-body systems, e.g., thousands of systems with 3...15 bodies each, as is typical for the study of planetary systems. Swarm-NG parallelizes the simulation, including both the numerical integration of the equations of motion and the evaluation of forces using NVIDIA's "Compute Unified Device Architecture" (CUDA) on the GPU. Swarm-NG includes optimized implementations of 4th order time-symmetrized Hermite integration and mixed variable symplectic integration, as well as several sample codes for other algorithms to illustrate how non-CUDA-savvy users may themselves introduce customized integrators into the Swarm-NG framework. To optimize performance, we analyze the effect of GPU-specific parameters on performance under double precision. For an ensemble of 131072 planetary systems, each containing three bodies, the NVIDIA Tesla M2070 GPU outperforms a 6-core Intel Xeon X5675 CPU by a factor of ∼2.75. Thus, we conclude that modern GPUs offer an attractive alternative to a cluster of CPUs for the integration of an ensemble of many few-body systems. Applications of Swarm-NG include studying the late stages of planet formation, testing the stability of planetary systems and evaluating the goodness-of-fit between many planetary system models and observations of extrasolar planet host stars (e.g., radial velocity, astrometry, transit timing). While Swarm-NG focuses on the parallel integration of many planetary systems, the underlying integrators could be applied to a wide variety of problems that require repeatedly integrating a set of ordinary differential equations many times using different initial conditions and/or parameter values. © 2013 Published by Elsevier B.V.

Axelrod T.,Steward Observatory | Kantor J.,LSST Corporation | Lupton R.H.,Princeton University | Pierfederici F.,US Space Telescope Science Institute
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2010

The LSST Data Management System is built on an open source software framework that has middleware and application layers. The middleware layer provides capabilities to construct, configure, and manage pipelines on clusters of processing nodes, and to manage the data the pipelines consume and produce. It is not in any way specific to astronomical applications. The complementary application layer provides the building blocks for constructing pipelines that process astronomical data, both in image and catalog forms. The application layer does not directly depend upon the LSST middleware, and can readily be used with other middleware implementations. Both layers have object oriented designs that make the creation of more specialized capabilities relatively easy through class inheritance. This paper outlines the structure of the LSST application framework and explores its usefulness for constructing pipelines outside of the LSST context, two examples of which are discussed. The classes that the framework provides are related within a domain model that is applicable to any astronomical pipeline that processes imaging data. Specifically modeled are mosaic imaging sensors; the images from these sensors and the transformations that result as they are processed from raw sensor readouts to final calibrated science products; and the wide variety of catalogs that are produced by detecting and measuring astronomical objects in a stream of such images. The classes are implemented in C++ with Python bindings provided so that pipelines can be constructed in any desired mixture of C++ and Python. © 2010 SPIE.

Loebman S.R.,University of Washington | Ivezic Z.,University of Washington | Quinn T.R.,University of Washington | Governato F.,University of Washington | And 3 more authors.
Astrophysical Journal Letters | Year: 2012

We search for evidence of dark matter in the Milky Way by utilizing the stellar number density distribution and kinematics measured by the Sloan Digital Sky Survey (SDSS) to heliocentric distances exceeding 10kpc. We employ the cylindrically symmetric form of Jeans equations and focus on the morphology of the resulting acceleration maps, rather than the normalization of the total mass as done in previous, mostly local, studies. Jeans equations are first applied to a mock catalog based on a cosmologically derived N-body+SPH simulation, and the known acceleration (gradient of gravitational potential) is successfully recovered. The same simulation is also used to quantify the impact of dark matter on the total acceleration. We use Galfast, a code designed to quantitatively reproduce SDSS measurements and selection effects, to generate a synthetic stellar catalog. We apply Jeans equations to this catalog and produce two-dimensional maps of stellar acceleration. These maps reveal that in a Newtonian framework, the implied gravitational potential cannot be explained by visible matter alone. The acceleration experienced by stars at galactocentric distances of 20kpc is three times larger than what can be explained by purely visible matter. The application of an analytic method for estimating the dark matter halo axis ratio to SDSS data implies an oblate halo with q DM = 0.47 ± 0.14 within the same distance range. These techniques can be used to map the dark matter halo to much larger distances from the Galactic center using upcoming deep optical surveys, such as LSST. © 2012. The American Astronomical Society. All rights reserved.

Schlafly E.F.,Max Planck Institute for Astronomy | Green G.,Harvard - Smithsonian Center for Astrophysics | Finkbeiner D.P.,Harvard - Smithsonian Center for Astrophysics | Finkbeiner D.P.,Harvard University | And 18 more authors.
Astrophysical Journal | Year: 2014

We present a map of the dust reddening to 4.5 kpc derived from Pan-STARRS1 stellar photometry. The map covers almost the entire sky north of declination -30° at a resolution of 7′-14′, and is based on the estimated distances and reddenings to more than 500 million stars. The technique is designed to map dust in the Galactic plane, where many other techniques are stymied by the presence of multiple dust clouds at different distances along each line of sight. This reddening-based dust map agrees closely with the Schlegel et al. (SFD) far-infrared emission-based dust map away from the Galactic plane, and the most prominent differences between the two maps stem from known limitations of SFD in the plane. We also compare the map with Planck, finding likewise good agreement in general at high latitudes. The use of optical data from Pan-STARRS1 yields reddening uncertainty as low as 25 mmag E(B-V). © 2014. The American Astronomical Society. All rights reserved.

Green G.M.,Harvard - Smithsonian Center for Astrophysics | Schlafly E.F.,Max Planck Institute for Astronomy | Finkbeiner D.P.,Harvard - Smithsonian Center for Astrophysics | Juric M.,LSST Corporation | And 12 more authors.
Astrophysical Journal | Year: 2014

We present a method to infer reddenings and distances to stars based only on their broad-band photometry, and show how this method can be used to produce a three-dimensional (3D) dust map of the Galaxy. Our method samples from the full probability density function of distance, reddening, and stellar type for individual stars, as well as the full uncertainty in reddening as a function of distance in the 3D dust map. We incorporate prior knowledge of the distribution of stars in the Galaxy and the detection limits of the survey. For stars in the Pan-STARRS 1 (PS1) 3π survey, we demonstrate that our reddening estimates are unbiased and accurate to ∼0.13 mag in E(B-V) for the typical star. Based on comparisons with mock catalogs, we expect distances for main-sequence stars to be constrained to within ∼20%-60%, although this range can vary, depending on the reddening of the star, the precise stellar type, and its position on the sky. A later paper will present a 3D map of dust over the three quarters of the sky surveyed by PS1. Both the individual stellar inferences and the 3D dust map will enable a wealth of Galactic science in the plane. The method we present is not limited to the passbands of the PS1 survey but may be extended to incorporate photometry from other surveys, such as the Two Micron All Sky Survey, the Sloan Digital Sky Survey (where available), and in the future, LSST and Gaia. © 2014. The American Astronomical Society. All rights reserved.

Discover hidden collaborations