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&

Galaxies in group and field environments: a comparison of optical-NIR luminosities and colors

We compare properties of galaxies in loose groups with those in field environment by analyzing the Nearby Optical Galaxy (NOG) catalog of galaxy systems. We consider as group galaxies, objects belonging to systems with at least five members identified by means of the "friends of friends method", and, as field galaxies, all galaxies with no companions. We analyze both a magnitude--limited sample of 959 and 2035 galaxies (groups vs. field galaxies, respectively, B<14 mag, and 2000<cz<6000 km/s) and a volume-limited sample (M_B <-19.01 mag, 2000<cz<4000 km/s 369 group and 548 field galaxies). For all these galaxies, blue corrected magnitudes and morphological types are available. The cross-correlation of NOG with the 2MASS second release allow us to assign K magnitudes and obtain B-K colors for about half of the galaxies in our samples. We analyze luminosity and color segregation-effects in relation with the morphological segregation. For both B and K bands, we find that group galaxies are, on average, more luminous than field galaxies and this effect is not entirely a consequence of the morphological segregation. After taking into account the morphological segregation, the luminosity difference between group and field galaxies is about 10%. When considering only very early-type galaxies (T<-2) the difference is larger than 30%. We also find that group galaxies are redder than field galaxies, Delta(B-K) about 0.4 mag. However, after taking into account the morphological segregation, we find a smaller B-K difference, poorly significant (only at the c.l. of about 80%).Comment: 11 pages, 10 eps figures, A&A in pres

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

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

SFI++ II: A New I-band Tully-Fisher Catalog, Derivation of Peculiar Velocities and Dataset Properties

We present the SFI++ dataset, a homogeneously derived catalog of photometric and rotational properties and the Tully-Fisher distances and peculiar velocities derived from them. We make use of digital optical images, optical long-slit spectra, and global HI line profiles to extract parameters of relevance to disk scaling relations, incorporating several previously published datasets as well as a new photometric sample of some 2000 objects. According to the completeness of available redshift samples over the sky area, we exploit both a modified percolation algorithm and the Voronoi-Delaunay method to assign individual galaxies to groups as well as clusters, thereby reducing scatter introduced by local orbital motions. We also provide corrections to the peculiar velocities for both homogeneous and inhomogeneous Malmquist bias, making use of the 2MASS Redshift Survey density field to approximate large scale structure. We summarize the sample selection criteria, corrections made to raw observational parameters, the grouping techniques, and our procedure for deriving peculiar velocities. The final SFI++ peculiar velocity catalog of 4861 field and cluster galaxies is large enough to permit the study not just of the global statistics of large scale flows but also of the {\it details} of the local velocity field.Comment: 14 pages, 6 figures, 4 external online tables, accepted for publication in ApJ

Studying the evolution of AGB stars in the Gaia epoch

We present asymptotic giant branch (AGB) models of solar metallicity, to allow the interpretation of observations of Galactic AGB stars, whose distances should be soon available after the first release of the Gaia catalogue. We find an abrupt change in the AGB physical and chemical properties, occurring at the threshold mass to ignite hot bottom burning,i.e. $3.5M_{\odot}$. Stars with mass below $3.5 M_{\odot}$ reach the C-star stage and eject into the interstellar medium gas enriched in carbon , nitrogen and $^{17}O$. The higher mass counterparts evolve at large luminosities, between $3\times 10^4 L_{\odot}$ and $10^5 L_{\odot}$. The mass expelled from the massive AGB stars shows the imprinting of proton-capture nucleosynthesis, with considerable production of nitrogen and sodium and destruction of $^{12}C$ and $^{18}O$. The comparison with the most recent results from other research groups are discussed, to evaluate the robustness of the present findings. Finally, we compare the models with recent observations of galactic AGB stars, outlining the possibility offered by Gaia to shed new light on the evolution properties of this class of objects.Comment: 21 pages, 11 figure, 3 tables, accepted for publication in MNRAS (2016 July 11

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

A Novel Rayleigh Dynamical Model for Remote Sensing Data Interpretation

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This article introduces the Rayleigh autoregressive moving average (RARMA) model, which is useful to interpret multiple different sets of remotely sensed data, from wind measurements to multitemporal synthetic aperture radar (SAR) sequences. The RARMA model is indeed suitable for continuous, asymmetric, and nonnegative signals observed over time. It describes the mean of Rayleigh-distributed discrete-time signals by a dynamic structure including autoregressive (AR) and moving average (MA) terms, a set of regressors, and a link function. After presenting the conditional likelihood inference for the model parameters and the detection theory, in this article, a Monte Carlo simulation is performed to evaluate the finite signal length performance of the conditional likelihood inferences. Finally, the new model is applied first to sequences of wind speed measurements, and then to a multitemporal SAR image stack for land-use classification purposes. The results in these two test cases illustrate the usefulness of this novel dynamic model for remote sensing data interpretation