Submillimeter Number Counts From Statistical Analysis of BLAST Maps

We describe the application of a statistical method to estimate submillimeter galaxy number counts from confusion limited observations by the Balloon-borne Large Aperture Submillimeter Telescope (BLAST). Our method is based on a maximum likelihood fit to the pixel histogram, sometimes called 'P(D)', an approach which has been used before to probe faint counts, the difference being that here we advocate its use even for sources with relatively high signal-to-noise ratios. This method has an advantage over standard techniques of source extraction in providing an unbiased estimate of the counts from the bright end down to flux densities well below the confusion limit. We specifically analyse BLAST observations of a roughly 10 sq. deg. map centered on the Great Observatories Origins Deep Survey South (GOODS-S) field. We provide estimates of number counts at the three BLAST wavelengths, 250, 350, and 500 microns; instead of counting sources in flux bins we estimate the counts at several flux density nodes connected with power-laws. We observe a generally very steep slope for the counts of about -3.7 at 250 microns and -4.5 at 350 and 500 microns, over the range ~0.02-0.5 Jy, breaking to a shallower slope below about 0.015 Jy at all three wavelengths. We also describe how to estimate the uncertainties and correlations in this method so that the results can be used for model-fitting. This method should be well-suited for analysis of data from the Herschel satellite.Comment: Accepted for publication in the Astrophysical Journal; see associated data and other papers at http://blastexperiment.info

BLAST: Correlations in the Cosmic Far-Infrared Background at 250, 350, and 500 microns Reveal Clustering of Star-Forming Galaxies

We detect correlations in the cosmic far-infrared background due to the clustering of star-forming galaxies in observations made with the Balloon-borne Large Aperture Submillimeter Telescope, BLAST, at 250, 350, and 500 microns. We perform jackknife and other tests to confirm the reality of the signal. The measured correlations are well fit by a power law over scales of 5-25 arcminutes, with Delta I/I = 15.1 +/- 1.7%. We adopt a specific model for submillimeter sources in which the contribution to clustering comes from sources in the redshift ranges 1.3 <= z <= 2.2, 1.5 <= z <= 2.7, and 1.7 <= z <= 3.2, at 250, 350, and 500 microns, respectively. With these distributions, our measurement of the power spectrum, P(k_theta), corresponds to linear bias parameters, b = 3.8 +/- 0.6, 3.9 +/- 0.6 and 4.4 +/- 0.7, respectively. We further interpret the results in terms of the halo model, and find that at the smaller scales, the simplest halo model fails to fit our results. One way to improve the fit is to increase the radius at which dark matter halos are artificially truncated in the model, which is equivalent to having some star-forming galaxies at z >= 1 located in the outskirts of groups and clusters. In the context of this model we find a minimum halo mass required to host a galaxy is log (M_min / M_sun) = 11.5 (+0.4/-0.1), and we derive effective biases $b_eff = 2.2 +/- 0.2, 2.4 +/- 0.2, and 2.6 +/- 0.2, and effective masses log (M_eff / M_sun) = 12.9 +/- 0.3, 12.8 +/- 0.2, and 12.7 +/- 0.2, at 250, 350, and 500 microns, corresponding to spatial correlation lengths of r_0 = 4.9, 5.0, and 5.2 +/- 0.7 h^-1 Mpc, respectively. Finally, we discuss implications for clustering measurement strategies with Herschel and Planck.Comment: Accepted for publication in the Astrophysical Journal. Maps and other results available at http://blastexperiment.info

Scientific Assessment of Ozone Depletion: 2010, Chapter 2 - Stratospheric Ozone and Surface Ultraviolet Radiation

As a result of the Montreal Protocol, ozone is expected to recover from the effect of ozone-depleting substances (ODSs) as their abundances decline in the coming decades. The 2006 Assessment showed that globally averaged column ozone ceased to decline around 1996, meeting the criterion for the first stage of recovery. Ozone is expected to increase as a result of continued decrease in ODSs (second stage of recovery). This chapter discusses recent observations of ozone and ultraviolet radiation in the context of their historical records. Natural variability, observational uncertainty, and stratospheric cooling necessitate a long record in order to attribute an ozone increase to decreases in ODSs. The primary tools used in this Assessment for prediction of ozone are chemistry-climate models (CCMs). These CCMs are designed to represent the processes determining the amount of stratospheric ozone and its response to changes in ODSs and greenhouse gases. Eighteen CCMs have been recently evaluated using a variety of process-based compari-sons to measurements. The CCMs are further evaluated here by comparison of trends calculated from measurements with trends calculated from simulations designed to reproduce ozone behavior during an observing period