1,328 research outputs found
Gaia Data Release 1. Cross-match with external catalogues - Algorithm and results
Although the Gaia catalogue on its own will be a very powerful tool, it is
the combination of this highly accurate archive with other archives that will
truly open up amazing possibilities for astronomical research. The advanced
interoperation of archives is based on cross-matching, leaving the user with
the feeling of working with one single data archive. The data retrieval should
work not only across data archives, but also across wavelength domains. The
first step for seamless data access is the computation of the cross-match
between Gaia and external surveys. The matching of astronomical catalogues is a
complex and challenging problem both scientifically and technologically
(especially when matching large surveys like Gaia). We describe the cross-match
algorithm used to pre-compute the match of Gaia Data Release 1 (DR1) with a
selected list of large publicly available optical and IR surveys. The overall
principles of the adopted cross-match algorithm are outlined. Details are given
on the developed algorithm, including the methods used to account for position
errors, proper motions, and environment; to define the neighbours; and to
define the figure of merit used to select the most probable counterpart.
Statistics on the results are also given. The results of the cross-match are
part of the official Gaia DR1 catalogue.Comment: 18 pages, 8 figures. Accepted for publication by A&
Elastic DVS Management in Processors with Discrete Voltage/Frequency Modes
Applying classical dynamic voltage scaling (DVS) techniques to real-time systems running on processors with discrete voltage/frequency modes causes a waste of computational resources. In fact, whenever the ideal speed level computed by the DVS algorithm is not available in the system, to guarantee the feasibility of the task set, the processor speed must be set to the nearest level greater than the optimal one, thus underutilizing the system. Whenever the task set allows a certain degree of flexibility in specifying timing constraints, rate adaptation techniques can be adopted to balance performance (which is a function of task rates) versus energy consumption (which is a function of the processor speed).
In this paper, we propose a new method that combines discrete DVS management with elastic scheduling to fully exploit the available computational resources. Depending on the application
requirements, the algorithm can be set to improve performance or reduce energy consumption, so enhancing the flexibility of the system. A reclaiming mechanism is also used to take advantage
of early completions. To make the proposed approach usable in real-world applications, the task model is enhanced to consider some of the real CPU characteristics, such as discrete voltage/frequency levels, switching overhead, task execution times nonlinear with the frequency, and tasks with different power consumption. Implementation issues and experimental results for the proposed algorithm are also discussed
Cloud chemistry at the Puy de Dôme: variability and relationships with environmental factors
The chemical composition of cloud water was investigated during the winter-spring months of 2001 and 2002 at the Puy de Dôme station (1465 m above sea level, 45°46′22′′ N, 2°57′43′′ E) in an effort to characterize clouds in the continental free troposphere. Cloud droplets were sampled with single-stage cloud collectors (cut-off diameter approximately 7 µm) and analyzed for inorganic and organic ions, as well as total dissolved organic carbon. Results show a very large variability in chemical composition and total solute concentration of cloud droplets, ranging from a few mg l<sup>-1</sup> to more than 150 mg l<sup>-1</sup>. Samplings can be classified in three different categories with respect to their total ionic content and relative chemical composition: background continental (BG, total solute content lower than 18 mg l<sup>-1</sup>), anthropogenic continental (ANT, total solute content from 18 to 50 mg l<sup>-1</sup>), and special events (SpE, total solute content higher than 50 mg l<sup>-1</sup>). The relative chemical composition shows an increase in anthropogenic-derived species (NO<sub>3</sub><sup>-</sup>, SO<sub>4</sub><sup>2-</sup> and NH<sub>4</sub><sup>+</sup>) from BG to SpE, and a decrease in dissolved organic compounds (ionic and non-ionic) that are associated with the anthropogenic character of air masses. <P style='line-height: 20px;'> We observed a high contribution of solute in cloud water derived from the dissolution of gas phase species in all cloud events. This was evident from large solute fractions of nitrate, ammonium and mono-carboxylic acids in cloud water, relative to their abundance in the aerosol phase. The comparison between droplet and aerosol composition clearly shows the limited ability of organic aerosols to act as cloud condensation nuclei. The strong contribution of gas-phase species limits the establishment of direct relationships between cloud water solute concentration and LWC that are expected from nucleation scavenging
The double RGB in M 2: C, N, Sr and Ba abundances
The globular cluster M 2 has a photometrically detected double red giant
branch (RGB) sequence. We investigate here the chemical differences between the
two RGBs in order to gain insight in the star formation history of this
cluster. The low-resolution spectra, covering the blue spectral range, were
collected with the MODS spectrograph on the LBT, and analyzed via spectrum
synthesis technique. The high quality of the spectra allows us to measure C, N,
Ba, and Sr abundances relative to iron for 15 RGB stars distributed along the
two sequences. We add to the MODS sample C and N measurements for 35 additional
stars belonging to the blue RGB sequence, presented in Lardo et al. (2012). We
find a clear separation between the two groups of stars in s-process elements
as well as C and N content. Both groups display a C-N anti-correlation and the
red RGB stars are on average richer in C and N with respect to the blue RGB.
Our results reinforce the suggestion that M2 belongs to the family of globular
clusters with complex star formation history, together with Omega Cen, NGC
1851, and M 22.Comment: 11 pages, 8 figures. Accepted for publication in MNRA
Gaia Data Release 2. Cross-match with external catalogues - Algorithms and results
Context. Although the Gaia catalogue on its own is a very powerful tool, it
is the combination of this high-accuracy archive with other archives that will
truly open up amazing possibilities for astronomical research. The advanced
interoperation of archives is based on cross-matching, leaving the user with
the feeling of working with one single data archive. The data retrieval should
work not only across data archives but also across wavelength domains. The
first step for a seamless access to the data is the computation of the
cross-match between Gaia and external surveys.
Aims. We describe the adopted algorithms and results of the pre-computed
cross-match of the Gaia Data Release 2 (DR2) catalogue with dense surveys
(Pan-STARRS1 DR1, 2MASS, SDSS DR9, GSC 2.3, URAT-1, allWISE, PPMXL, and APASS
DR9) and sparse catalogues (Hipparcos2, Tycho-2, and RAVE 5).
Methods. A new algorithm is developed specifically for sparse catalogues.
Improvements and changes with respect to the algorithm adopted for DR1 are
described in detail.
Results. The outputs of the cross-match are part of the official Gaia DR2
catalogue. The global analysis of the cross-match results is also presented.Comment: accepted for publication in A&A Gaia DR2 special issu
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