Polarization measurements analysis II. Best estimators of polarization fraction and angle

With the forthcoming release of high precision polarization measurements, such as from the Planck satellite, it becomes critical to evaluate the performance of estimators for the polarization fraction and angle. These two physical quantities suffer from a well-known bias in the presence of measurement noise, as has been described in part I of this series. In this paper, part II of the series, we explore the extent to which various estimators may correct the bias. Traditional frequentist estimators of the polarization fraction are compared with two recent estimators: one inspired by a Bayesian analysis and a second following an asymptotic method. We investigate the sensitivity of these estimators to the asymmetry of the covariance matrix which may vary over large datasets. We present for the first time a comparison among polarization angle estimators, and evaluate the statistical bias on the angle that appears when the covariance matrix exhibits effective ellipticity. We also address the question of the accuracy of the polarization fraction and angle uncertainty estimators. The methods linked to the credible intervals and to the variance estimates are tested against the robust confidence interval method. From this pool of estimators, we build recipes adapted to different use-cases: build a mask, compute large maps, and deal with low S/N data. More generally, we show that the traditional estimators suffer from discontinuous distributions at low S/N, while the asymptotic and Bayesian methods do not. Attention is given to the shape of the output distribution of the estimators, and is compared with a Gaussian. In this regard, the new asymptotic method presents the best performance, while the Bayesian output distribution is shown to be strongly asymmetric with a sharp cut at low S/N.Finally, we present an optimization of the estimator derived from the Bayesian analysis using adapted priors

Dust properties inside molecular clouds from coreshine modeling and observations

Context. Using observations to deduce dust properties, grain size distribution, and physical conditions in molecular clouds is a highly degenerate problem. Aims. The coreshine phenomenon, a scattering process at 3.6 and 4.5 $\mu$m that dominates absorption, has revealed its ability to explore the densest parts of clouds. We want to use this effect to constrain the dust parameters. The goal is to investigate to what extent grain growth (at constant dust mass) inside molecular clouds is able to explain the coreshine observations. We aim to find dust models that can explain a sample of Spitzer coreshine data. We also look at the consistency with near-infrared data we obtained for a few clouds. Methods. We selected four regions with a very high occurrence of coreshine cases: Taurus-Perseus, Cepheus, Chameleon and L183/L134. We built a grid of dust models and investigated the key parameters to reproduce the general trend of surface bright- nesses and intensity ratios of both coreshine and near-infrared observations with the help of a 3D Monte-Carlo radiative transfer code. The grid parameters allow to investigate the effect of coagulation upon spherical grains up to 5 $\mu$m in size derived from the DustEm diffuse interstellar medium grains. Fluffiness (porosity or fractal degree), ices, and a handful of classical grain size distributions were also tested. We used the near- and mostly mid-infrared intensity ratios as strong discriminants between dust models. Results. The determination of the background field intensity at each wavelength is a key issue. In particular, an especially strong background field explains why we do not see coreshine in the Galactic plane at 3.6 and 4.5 $\mu$m. For starless cores, where detected, the observed 4.5 $\mu$m / 3.6 $\mu$m coreshine intensity ratio is always lower than $\sim$0.5 which is also what we find in the models for the Taurus-Perseus and L183 directions. Embedded sources can lead to higher fluxes (up to four times greater than the strongest starless core fluxes) and higher coreshine ratios (from 0.5 to 1.1 in our selected sample). Normal interstellar radiation field conditions are sufficient to find suitable grain models at all wavelengths for starless cores. The standard interstellar grains are not able to reproduce observations and, due to the multi-wavelength approach, only a few grain types meet the criteria set by the data. Porosity does not affect the flux ratios while the fractal dimension helps to explain coreshine ratios but does not seem able to reproduce near-infrared observations without a mix of other grain types. Conclusions. Combined near- and mid-infrared wavelengths confirm the potential to reveal the nature and size distribution of dust grains. Careful assessment of the environmental parameters (interstellar and background fields, embedded or nearby reddened sources) is required to validate this new diagnostic

Paramètres locaux pour une méthode de contours actifs

L'introduction des contours actifs (snakes) comme nouvelle méthode d'extraction des contours dans le domaine du traitement d'images a constitué une avancée majeure en ce qui concerne les méthodes de segmentation. Malheureusement, la modélisation de la fonctionnelle d'énergie qui doit être associée à chaque image est délicate. En effet, elle dépend de nombreux paramètres qui sont souvent fixés empiriquement par le concepteur du système. Nous proposons ici une méthode originale qui permet de résoudre, dans la plupart des cas, le problème de la détermination de ces paramètres. La méthode est présentée dans le cadre de l'algorithme "greedy". Nous considérons ici que les coefficients de la fonctionnelle d'énergie ne sont pas globaux, ni indépendants des points considérés mais qu'ils sont locaux. Nous les recherchons donc en chaque point en effectuant le meilleur choix dans un ensemble de paramètres qui est crée par des tirages aléatoires. L'application sur un ensemble d'images variées, dont des radiographies, montre la convergence de la méthode proposée

The Good, the Bad, and the Ugly: Statistical quality assessment of SZ detections

International audienceWe examine three approaches to the problem of source classification in catalogues. Our goal is to determine the confidence withwhich the elements in these catalogues can be distinguished in populations on the basis of their spectral energy distribution (SED).Our analysis is based on the projection of the measurements onto a comprehensive SED model of the main signals in the consideredrange of frequencies. We first consider likelihood analysis, which is halfway between supervised and unsupervised methods. Next, weinvestigate an unsupervised clustering technique. Finally, we consider a supervised classifier based on artificial neural networks. Weillustrate the approach and results using catalogues from various surveys, such as X-rays (MCXC), optical (SDSS), and millimetric(Planck Sunyaev-Zeldovich (SZ)). We show that the results from the statistical classifications of the three methods are in very goodagreement with each other, although the supervised neural network-based classification shows better performance allowing the bestseparation into populations of reliable and unreliable sources in catalogues. The latest method was applied to the SZ sources detectedby the Planck satellite. It led to a classification assessing and thereby agreeing with the reliability assessment published in the PlanckSZ catalogue. Our method could easily be applied to catalogues from future large surveys such as SRG/eROSITA and Euclid

Interaction between galectin-3 and cystinosin uncovers a pathogenic role of inflammation in kidney involvement of cystinosis.

Inflammation is involved in the pathogenesis of many disorders. However, the underlying mechanisms are often unknown. Here, we test whether cystinosin, the protein involved in cystinosis, is a critical regulator of galectin-3, a member of the β-galactosidase binding protein family, during inflammation. Cystinosis is a lysosomal storage disorder and, despite ubiquitous expression of cystinosin, the kidney is the primary organ impacted by the disease. Cystinosin was found to enhance lysosomal localization and degradation of galectin-3. In Ctns-/- mice, a mouse model of cystinosis, galectin-3 is overexpressed in the kidney. The absence of galectin-3 in cystinotic mice ameliorates pathologic renal function and structure and decreases macrophage/monocyte infiltration in the kidney of the Ctns-/-Gal3-/- mice compared to Ctns-/- mice. These data strongly suggest that galectin-3 mediates inflammation involved in kidney disease progression in cystinosis. Furthermore, galectin-3 was found to interact with the pro-inflammatory cytokine Monocyte Chemoattractant Protein-1, which stimulates the recruitment of monocytes/macrophages, and proved to be significantly increased in the serum of Ctns-/- mice and also patients with cystinosis. Thus, our findings highlight a new role for cystinosin and galectin-3 interaction in inflammation and provide an additional mechanistic explanation for the kidney disease of cystinosis. This may lead to the identification of new drug targets to delay cystinosis progression

Matching dust emission structures and magnetic field in high-latitude cloud L1642 : comparing Herschel and Planck maps

The nearby cloud L1642 is one of only two known very high latitude (b| > 30 deg) clouds actively forming stars. It is a rare example of star formation in isolated conditions, and can reveal important details of star formation in general, e.g. of the effect of magnetic fields. We compareHerschel dust emission structures and magnetic field orientation revealed byPlanck polarization maps in L1642. The high-resolution (similar to 20 arcsec)Herschel data reveal a complex structure including a dense, compressed central clump, and low-density striations. ThePlanck polarization data (at 10 arcmin resolution) reveal an ordered magnetic field pervading the cloud and aligned with the surrounding striations. There is a complex interplay between the cloud structure and large-scale magnetic field. This suggests that the magnetic field is closely linked to the formation and evolution of the cloud. CO rotational emission confirms that the striations are connected with the main clumps and likely to contain material either falling into or flowing out of the clumps. There is a clear transition from aligned to perpendicular structures approximately at a column density ofN(H) = 1.6 x 10(21) cm(-2). Comparing theHerschel maps with thePlanck polarization maps shows the close connection between the magnetic field and cloud structure even in the finest details of the cloud.Peer reviewe

The good, the bad, and the ugly: Statistical quality assessment of SZ detections

We examine three approaches to the problem of source classification in catalogues. Our goal is to determine the confidence with which the elements in these catalogues can be distinguished in populations on the basis of their spectral energy distribution (SED). Our analysis is based on the projection of the measurements onto a comprehensive SED model of the main signals in the considered range of frequencies. We first consider likelihood analysis, which is halfway between supervised and unsupervised methods. Next, we investigate an unsupervised clustering technique. Finally, we consider a supervised classifier based on artificial neural networks. We illustrate the approach and results using catalogues from various surveys, such as X-rays (MCXC), optical (SDSS), and millimetric (Planck Sunyaev-Zeldovich (SZ)). We show that the results from the statistical classifications of the three methods are in very good agreement with each other, although the supervised neural network-based classification shows better performance allowing the best separation into populations of reliable and unreliable sources in catalogues. The latest method was applied to the SZ sources detected by the Planck satellite. It led to a classification assessing and thereby agreeing with the reliability assessment published in the Planck SZ catalogue. Our method could easily be applied to catalogues from future large surveys such as SRG/eROSITA and Euclid.We acknowledge the support of the French Agence Nationale de la Recherche under grant ANR-11-BD56-015. The development of Planck has been supported by: ESA; CNES and CNRS/INSU-IN2P3-INP (France); ASI, CNR, and INAF (Italy); NASA and DoE (USA); STFC and UKSA (UK); CSIC, MICINN and JA (Spain); Tekes, AoF and CSC (Finland); DLR and MPG (Germany); CSA (Canada); DTU Space (Denmark); SER/SSO (Switzerland); RCN (Norway); SFI (Ireland); FCT/MCTES (Portugal); and PRACE (EU).Peer Reviewe

Comprehensive analysis of a symbiotic candidate V503 Her

V503 Her was previously proposed as an eclipsing symbiotic candidate based on photometric behavior and spectroscopic appearance indicating the composite optical spectrum. To investigate its nature, we analyzed long-term photometric observations covering one hundred years of its photometric history and new low-resolution optical spectroscopic data, supplemented with the multifrequency measurements collected from several surveys and satellites. Based on the analysis presented in this paper, we claim that V503 Her is not an eclipsing binary star. The optical and infrared wavelengths are dominated by a K-type bright giant with an effective temperature of 4 500 K, luminosity of 1 900 L$_\odot$, and sub-solar metallicity on the asymptotic giant branch showing semiregular complex multi-periodic pulsation behavior. V503 Her does not show the characteristics of strongly interacting symbiotic variables, but some pieces of evidence suggest that it could still be one of the 'hidden' accreting-only symbiotic systems. However, the currently available data do not allow us to fully confirm or constrain the parameters of a possible companion.Comment: 16 pages, 10 figures, 4 tables; accepted in the Astronomical Journa

Mapping the column density and dust temperature structure of IRDCs with Herschel

Infrared dark clouds (IRDCs) are cold and dense reservoirs of gas potentially available to form stars. Many of these clouds are likely to be pristine structures representing the initial conditions for star formation. The study presented here aims to construct and analyze accurate column density and dust temperature maps of IRDCs by using the first Herschel data from the Hi-GAL galactic plane survey. These fundamental quantities, are essential for understanding processes such as fragmentation in the early stages of the formation of stars in molecular clouds. We have developed a simple pixel-by-pixel SED fitting method, which accounts for the background emission. By fitting a grey-body function at each position, we recover the spatial variations in both the dust column density and temperature within the IRDCs. This method is applied to a sample of 22 IRDCs exhibiting a range of angular sizes and peak column densities. Our analysis shows that the dust temperature decreases significantly within IRDCs, from background temperatures of 20-30 K to minimum temperatures of 8-15 K within the clouds, showing that dense molecular clouds are not isothermal. Temperature gradients have most likely an important impact on the fragmentation of IRDCs. Local temperature minima are strongly correlated with column density peaks, which in a few cases reach NH2 = 1 x 10^{23} cm^{-2}, identifying these clouds as candidate massive prestellar cores. Applying this technique to the full Hi-GAL data set will provide important constraints on the fragmentation and thermal properties of IRDCs, and help identify hundreds of massive prestellar core candidates.Comment: Accepted for publication in A&A Herschel special issu