Rubin-LSST

Abstract:

(Abridged) The effective extinction law (attenuation behavior) in galaxies in the emitted ultraviolet is well known only for actively star-forming objects and combines effects of the grain properties, fine structure in the dust distribution, and relative distributions of stars and dust. We use GALEX, XMM Optical Monitor, and HST data to explore the UV attenuation in the outer parts of spiral disks which are backlit by other UV-bright galaxies, starting with candidates provided by Galaxy Zoo participants. Our analysis incorporates galaxy symmetry, using non-overlapping regions of each galaxy to derive error estimates on the attenuation measurements. The entire sample has an attenuation law close to the Calzetti et al. (1994) form; the UV slope for the overall sample is substantially shallower than found by Wild et al. (2011), a reasonable match to the more distant galaxies in our sample but not to the weighted combination including NGC 2207. The nearby, bright spiral NGC 2207 alone gives accuracy almost equal to the rest of our sample, and its outer arms have a very low level of foreground starlight. This "grey" law can be produced from the distribution of dust alone, without a necessary contribution from differential escape of stars from dense clouds. The extrapolation needed to compare attenution between backlit galaxies at moderate redshifts, and local systems from SDSS data, is mild enough to allow use of galaxy overlaps to trace the cosmic history of dust. For NGC 2207, the covering factor of clouds with small optical attenuation becomes a dominant factor farther into the ultraviolet, which opens the possibility that widespread diffuse dust dominates over dust in star-forming regions deep into the ultraviolet. Comparison with published radiative-transfer models indicates that the role of dust clumping dominates over differences in grain populations, at this spatial resolution.

Abstract:

Astronomy at or below the survey threshold has expanded significantly since the publication of the original Science with the Square Kilometer Array in 1999 and its update in 2004. The techniques in this regime may be broadly (but far from exclusively) defined as confusion or P(D) analyses (analyses of one-point statistics), and stacking, accounting for the flux-density distribution of noise-limited images co-added at the positions of objects detected/isolated in a different waveband. Here we discuss the relevant issues, present some examples of recent analyses, and consider some of the consequences for the design and use of surveys with the SKA and its pathfinders.

Abstract:

We present a statistical method based on a maximum-likelihood approach to constrain the number counts of extragalactic sources below the nominal flux-density limit of continuum imaging surveys. We extract flux densities from a radio map using positional information from an auxiliary catalogue and show that we can model the number counts of this undetected population down to flux-density levels well below the detection threshold of the radio survey. We demonstrate the capabilities that our method will have with future generation wide-area radio surveys by performing simulations over various sky areas. We show that it is possible to accurately constrain the number counts of the simulated distribution down to one-tenth of the flux noise rms with just a sky area of 100 deg2.We then test the application of our method using data from the Faint Images of the Radio Sky at Twenty-Centimetres survey (FIRST). We extract flux densities from the FIRST map, sensitive to 150 μJy beam-1 (1 σ), using the positional information from a catalogue in the same field, also acquired at the same frequency, sensitive to 12 μJy beam-1 (1 σ). Implementing our method, with known source positions, we are able to recover the right differential number counts of the noise-dominated FIRST map fluxes down to a flux-density level which is one-tenth the FIRST detection threshold. © 2013 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society.