Statistical techniques for the detection and analysis of solar explosive events

Solar explosive events are commonly explained as small scale magnetic reconnection events, although unambiguous confirmation of this scenario remains elusive due to the lack of spatial resolution and of the statistical analysis of large enough samples of this type of events. In this work, we propose a sound statistical treatment of data cubes consisting of a temporal sequence of long slit spectra of the solar atmosphere. The analysis comprises all the stages from the explosive event detection to its characterization and the subsequent sample study. We have designed two complementary approaches based on the combination of standard statistical techniques (Robust Principal Component Analysis in one approach and wavelet decomposition and Independent Component Analysis in the second) in order to obtain least biased samples. These techniques are implemented in the spirit of letting the data speak for themselves. The analysis is carried out for two spectral lines: the C IV line at 1548.2 angstroms and the Ne VIII line at 770.4 angstroms. We find significant differences between the characteristics of the line profiles emitted in the proximities of two active regions, and in the quiet Sun, most visible in the relative importance of a separate population of red shifted profiles. We also find a higher frequency of explosive events near the active regions, and in the C IV line. The distribution of the explosive events characteristics is interpreted in the light of recent numerical simulations. Finally, we point out several regions of the parameter space where the reconnection model has to be refined in order to explain the observations.Comment: Accepted for publication in Astronomy and Astrophysics (in Section 9. The Sun) on 18/01/2011. 17 pages, 22 Figure

Properties of ultra-cool dwarfs with Gaia. An assessment of the accuracy for the temperature determination

We aimed to assess the accuracy of the Gaia teff and logg estimates as derived with current models and observations. We assessed the validity of several inference techniques for deriving the physical parameters of ultra-cool dwarf stars. We used synthetic spectra derived from ultra-cool dwarf models to construct (train) the regression models. We derived the intrinsic uncertainties of the best inference models and assessed their validity by comparing the estimated parameters with the values derived in the bibliography for a sample of ultra-cool dwarf stars observed from the ground. We estimated the total number of ultra-cool dwarfs per spectral subtype, and obtained values that can be summarised (in orders of magnitude) as 400000 objects in the M5-L0 range, 600 objects between L0 and L5, 30 objects between L5 and T0, and 10 objects between T0 and T8. A bright ultra-cool dwarf (with teff=2500 K and \logg=3.5 will be detected by Gaia out to approximately 220 pc, while for teff=1500 K (spectral type L5) and the same surface gravity, this maximum distance reduces to 10-20 pc. The RMSE of the prediction deduced from ground-based spectra of ultra-cool dwarfs simulated at the Gaia spectral range and resolution, and for a Gaia magnitude G=20 is 213 K and 266 K for the models based on k-nearest neighbours and Gaussian process regression, respectively. These are total errors in the sense that they include the internal and external errors, with the latter caused by the inability of the synthetic spectral models (used for the construction of the regression models) to exactly reproduce the observed spectra, and by the large uncertainties in the current calibrations of spectral types and effective temperatures.Comment: 18 pages, 17 figures, accepted by Astronomy & Astrophysic

Long-term variations in global sea level extremes

Decadal to multidecadal variations in sea level extremes unrelated to mean sea level changes have been investigated using long tide gauge records distributed worldwide. A state space approach has been applied that provides robust solutions and uncertainties of the time evolving characteristics of extremes, allowing for data gaps and uneven sampling, both common features of historical sea level time series. Two different models have been formulated for the intensity and for the occurrence of extreme sea level events and have been applied independently to each tide gauge record. Our results reveal two key findings: first, the intensity and the frequency of occurrence of extreme sea levels unrelated to mean sea level vary coherently on decadal scales in most of the sites examined (63 out of 77) and, second, extreme sea level changes are regionally consistent, thus pointing toward a common large-scale forcing. This variability of extremes associated with climate drivers should be considered in the framework of climate change studies

Long-term variations in global sea level extremes

Decadal to multidecadal variations in sea level extremes unrelated to mean sea level changes have been investigated using long tide gauge records distributed worldwide. A state space approach has been applied that provides robust solutions and uncertainties of the time evolving characteristics of extremes, allowing for data gaps and uneven sampling, both common features of historical sea level time series. Two different models have been formulated for the intensity and for the occurrence of extreme sea level events and have been applied independently to each tide gauge record. Our results reveal two key findings: first, the intensity and the frequency of occurrence of extreme sea levels unrelated to mean sea level vary coherently on decadal scales in most of the sites examined (63 out of 77) and, second, extreme sea level changes are regionally consistent, thus pointing toward a common large-scale forcing. This variability of extremes associated with climate drivers should be considered in the framework of climate change studies.M. Marcos acknowledges a “Ramon y Cajal” contract funded by the Spanish Ministry of Economy. This work was supported by the research project CLIMPACT (CGL2014-54246-C2-1-R) funded by the Spanish Ministry of EconomyPeer Reviewe

Cluster membership probabilities from proper motions and multiwavelength photometric catalogues: I. Method and application to the Pleiades cluster

We present a new technique designed to take full advantage of the high dimensionality (photometric, astrometric, temporal) of the DANCe survey to derive self-consistent and robust membership probabilities of the Pleiades cluster. We aim at developing a methodology to infer membership probabilities to the Pleiades cluster from the DANCe multidimensional astro-photometric data set in a consistent way throughout the entire derivation. The determination of the membership probabilities has to be applicable to censored data and must incorporate the measurement uncertainties into the inference procedure. We use Bayes' theorem and a curvilinear forward model for the likelihood of the measurements of cluster members in the colour-magnitude space, to infer posterior membership probabilities. The distribution of the cluster members proper motions and the distribution of contaminants in the full multidimensional astro-photometric space is modelled with a mixture-of-Gaussians likelihood. We analyse several representation spaces composed of the proper motions plus a subset of the available magnitudes and colour indices. We select two prominent representation spaces composed of variables selected using feature relevance determination techniques based in Random Forests, and analyse the resulting samples of high probability candidates. We consistently find lists of high probability (p > 0.9975) candidates with $\approx$ 1000 sources, 4 to 5 times more than obtained in the most recent astro-photometric studies of the cluster. The methodology presented here is ready for application in data sets that include more dimensions, such as radial and/or rotational velocities, spectral indices and variability.Comment: 14 pages, 4 figures, accepted by A&

The Seven Sisters DANCe III: Projected spatial distribution

Methods. We compute Bayesian evidences and Bayes Factors for a set of variations of the classical radial models by King (1962), Elson et al. (1987) and Lauer et al. (1995). The variations incorporate different degrees of model freedom and complexity, amongst which we include biaxial (elliptical) symmetry, and luminosity segregation. As a by-product of the model comparison, we obtain posterior distributions and maximum a posteriori estimates for each set of model parameters. Results. We find that the model comparison results depend on the spatial extent of the region used for the analysis. For a circle of 11.5 parsecs around the cluster centre (the most homogeneous and complete region), we find no compelling reason to abandon Kings model, although the Generalised King model, introduced in this work, has slightly better fitting properties. Furthermore, we find strong evidence against radially symmetric models when compared to the elliptic extensions. Finally, we find that including mass segregation in the form of luminosity segregation in the J band, is strongly supported in all our models. Conclusions. We have put the question of the projected spatial distribution of the Pleiades cluster on a solid probabilistic framework, and inferred its properties using the most exhaustive and least contaminated list of Pleiades candidate members available to date. Our results suggest however that this sample may still lack about 20% of the expected number of cluster members. Therefore, this study should be revised when the completeness and homogeneity of the data can be extended beyond the 11.5 parsecs limit. Such study will allow a more precise determination of the Pleiades spatial distribution, its tidal radius, ellipticity, number of objects and total mass.Comment: 39 pages, 31 figure

The Seven Sisters DANCe. I. Empirical isochrones, Luminosity and Mass Functions of the Pleiades cluster

The DANCe survey provides photometric and astrometric (position and proper motion) measurements for approximately 2 millions unique sources in a region encompassing $\approx$80deg$^{2}$ centered around the Pleiades cluster. We aim at deriving a complete census of the Pleiades, and measure the mass and luminosity function of the cluster. Using the probabilistic selection method described in Sarro+2014, we identify high probability members in the DANCe ($i\ge$14mag) and Tycho-2 ($V\lesssim$12mag) catalogues, and study the properties of the cluster over the corresponding luminosity range. We find a total of 2109 high probability members, of which 812 are new, making it the most extensive and complete census of the cluster to date. The luminosity and mass functions of the cluster are computed from the most massive members down to $\approx$0.025M$_{\odot}$. The size, sensitivity and quality of the sample result in the most precise luminosity and mass functions observed to date for a cluster. Our census supersedes previous studies of the Pleiades cluster populations, both in terms of sensitivity and accuracy.Comment: Language Edition Done. Final version to be published in A&A. Tables will be published at CDS. Meanwhile, they can be requested to H. Bouy (hbouy -at- cab . inta - csic . es

Corona-Australis DANCe I. Revisiting the census of stars with Gaia-DR2 data

Context. Corona-Australis is one of the nearest regions to the Sun with recent and ongoing star formation, but the current picture of its stellar (and substellar) content is not complete yet. Aims. We take advantage of the second data release of the Gaia space mission to revisit the stellar census and search for additional members of the young stellar association in Corona-Australis. Methods. We applied a probabilistic method to infer membership probabilities based on a multidimensional astrometric and photometric data set over a field of 128 deg(2) around the dark clouds of the region. Results. We identify 313 high-probability candidate members to the Corona-Australis association, 262 of which had never been reported as members before. Our sample of members covers the magnitude range between G greater than or similar to 5 mag and G less than or similar to 20 mag, and it reveals the existence of two kinematically and spatially distinct subgroups. There is a distributed "off-cloud" population of stars located in the north of the dark clouds that is twice as numerous as the historically known "on-cloud" population that is concentrated around the densest cores. By comparing the location of the stars in the HR-diagram with evolutionary models, we show that these two populations are younger than 10 Myr. Based on their infrared excess emission, we identify 28 Class II and 215 Class III stars among the sources with available infrared photometry, and we conclude that the frequency of Class II stars (i.e. "disc-bearing" stars) in the on-cloud region is twice as large as compared to the off-cloud population. The distance derived for the Corona-Australis region based on this updated census is d = 149.4(-0.4)(+0.4) pc, which exceeds previous estimates by about 20 pc. Conclusions. In this paper we provide the most complete census of stars in Corona-Australis available to date that can be confirmed with Gaia data. Furthermore, we report on the discovery of an extended and more evolved population of young stars beyond the region of the dark clouds, which was extensively surveyed in the past