Photometric Accretion Signatures Near the Substellar Boundary

Multi-epoch imaging of the Orion equatorial region by the Sloan Digital Sky Survey has revealed that significant variability in the blue continuum persists into the late-M spectral types, indicating that magnetospheric accretion processes occur below the substellar boundary in the Orion OB1 association. We investigate the strength of the accretion-related continuum veiling by comparing the reddening-invariant colors of the most highly variable stars against those of main sequence M dwarfs and evolutionary models. A gradual decrease in the g band veiling is seen for the cooler and less massive members, as expected for a declining accretion rate with decreasing mass. We also see evidence that the temperature of the accretion shock decreases in the very low mass regime, reflecting a reduction in the energy flux carried by the accretion columns. We find that the near-IR excess attributed to circumstellar disk thermal emission drops rapidly for spectral types later than M4. This is likely due to the decrease in color contrast between the disk and the cooler stellar photosphere. Since accretion, which requires a substantial stellar magnetic field and the presence of a circumstellar disk, is inferred for masses down to 0.05 Msol we surmise that brown dwarfs and low mass stars share a common mode of formation.Comment: 37 pages, 14 figures, accepted by A

A method for space-variant deblurring with application to adaptive optics imaging in astronomy

Images from adaptive optics systems are generally affected by significant distortions of the point spread function (PSF) across the field of view, depending on the position of natural and artificial guide stars. Image reduction techniques circumventing or mitigating these effects are important tools to take full advantage of the scientific information encoded in AO images. The aim of this paper is to propose a method for the deblurring of the astronomical image, given a set of samples of the space-variant PSF. The method is based on a partitioning of the image domain into regions of isoplanatism and on applying suitable deconvolution methods with boundary effects correction to each region. The effectiveness of the boundary effects correction is proved. Moreover, the criterion for extending the disjoint sections to partially overlapping sections is validated. The method is applied to simulated images of a stellar system characterized by a spatially variable PSF. We obtain good photometric quality, and therefore good science quality, by performing aperture photometry on the deblurred images. The proposed method is implemented in IDL in the Software Package "Patch", which is available on http://www.airyproject.eu.Comment: 11 pages, 9 figures, 7 tables, accepted by A&

The Clustering of Luminous Red Galaxies in the Sloan Digital Sky Survey Imaging Data

We present the 3D real space clustering power spectrum of a sample of \~600,000 luminous red galaxies (LRGs) measured by the Sloan Digital Sky Survey (SDSS), using photometric redshifts. This sample of galaxies ranges from redshift z=0.2 to 0.6 over 3,528 deg^2 of the sky, probing a volume of 1.5 (Gpc/h)^3, making it the largest volume ever used for galaxy clustering measurements. We measure the angular clustering power spectrum in eight redshift slices and combine these into a high precision 3D real space power spectrum from k=0.005 (h/Mpc) to k=1 (h/Mpc). We detect power on gigaparsec scales, beyond the turnover in the matter power spectrum, on scales significantly larger than those accessible to current spectroscopic redshift surveys. We also find evidence for baryonic oscillations, both in the power spectrum, as well as in fits to the baryon density, at a 2.5 sigma confidence level. The statistical power of these data to constrain cosmology is ~1.7 times better than previous clustering analyses. Varying the matter density and baryon fraction, we find \Omega_M = 0.30 \pm 0.03, and \Omega_b/\Omega_M = 0.18 \pm 0.04, The detection of baryonic oscillations also allows us to measure the comoving distance to z=0.5; we find a best fit distance of 1.73 \pm 0.12 Gpc, corresponding to a 6.5% error on the distance. These results demonstrate the ability to make precise clustering measurements with photometric surveys (abridged).Comment: 23 pages, 27 figures, submitted to MNRA

The Faintest X-ray Sources from z=0-8

We use the new 4 Ms exposure of the CDF-S field obtained with the Chandra X-ray satellite to investigate the properties of the faintest X-ray sources over a wide range of redshifts. We use an optimized averaging procedure to investigate the weighted mean X-ray fluxes of optically selected sources in the CDF-S over the redshift range z=0-8 and down to 0.5-2 keV fluxes as low as 5e-19 erg/cm^2/s. None of the samples of sources at high redshifts (z>5) show any significant flux, and at z=6.5 we place an upper limit on the X-ray luminosity of 4e41 erg/s in the rest-frame 3.75-15 keV band for the sample of Bouwens et al. (2006). This is consistent with any X-ray production in the galaxies being solely due to star formation. At lower redshifts we find significant weighted mean X-ray fluxes in many samples of sources over the redshift range z=0-4. We use these to argue that (1) the relation between star formation and X-ray production remains invariant over this redshift range, (2) X-ray sources below the direct detection threshold in the CDF-S are primarily star-forming, and (3) there is full consistency between UV and X-ray estimations of the star formation history.Comment: 13 pages, ApJ, in press. This accepted version includes a new figure on the star formation history determined from the X-ray dat

Image Segmentation Using Weak Shape Priors

The problem of image segmentation is known to become particularly challenging in the case of partial occlusion of the object(s) of interest, background clutter, and the presence of strong noise. To overcome this problem, the present paper introduces a novel approach segmentation through the use of "weak" shape priors. Specifically, in the proposed method, an segmenting active contour is constrained to converge to a configuration at which its geometric parameters attain their empirical probability densities closely matching the corresponding model densities that are learned based on training samples. It is shown through numerical experiments that the proposed shape modeling can be regarded as "weak" in the sense that it minimally influences the segmentation, which is allowed to be dominated by data-related forces. On the other hand, the priors provide sufficient constraints to regularize the convergence of segmentation, while requiring substantially smaller training sets to yield less biased results as compared to the case of PCA-based regularization methods. The main advantages of the proposed technique over some existing alternatives is demonstrated in a series of experiments.Comment: 27 pages, 8 figure