Dust emission at sub-millimetre wavelengths allows us to trace the early phases of star formation in the Universe. In order to understand the physical processes involved in this mode of star formation, it is essential to gain knowledge about the dark
matter structures - most importantly their masses - that sub-millimetre galaxies live in. Here we use the magnification effect of gravitational lensing to determine the average mass and dust content of sub-millimetre galaxies with 250mu flux densities of S_250>15mJy selected using data from the Herschel Multi-tiered Extragalactic Survey. The positions of hundreds of sub-millimetre foreground lenses are cross-correlated with the positions of background Lyman-break galaxies at z~3-5 selected using optical data from the Canada-France Hawaii Telescope Legacy Survey. We detect a cross-correlation signal at the 7-sigma level over a sky area of one square degree, with ~80% of this signal being due to magnification, whereas the remaining ~20% comes from dust extinction. Adopting some simple assumptions for the dark matter and dust profiles and the redshift distribution enables us to estimate the average mass of the halos hosting the sub-millimetre galaxies to be log(M_200/M_sun)=13.17+0.05-0.08(stat.) and their average dust mass fraction (at radii of >10kpc) to be M_dust/M_200~6x10^-5. This supports the picture that sub-millimetre galaxies are dusty, forming stars at a high rate, reside in massive group-sized halos, and are a crucial phase in the assembly and evolution of structure in the Universe.
We introduce a novel method to measure the masses of galaxy clusters at high redshift selected from optical and IR Spitzer data via the red-sequence technique. Lyman-break galaxies are used as a well understood, high-redshift background sample allowi
ng mass measurements of lenses at unprecedented high redshifts using weak lensing magnification. By stacking a significant number of clusters at different redshifts with average masses of ~1-3x10^14M_sun, as estimated from their richness, we can calibrate the normalisation of the mass-richness relation. With the current data set (area: 6 deg^2) we detect a magnification signal at the >3-sigma level. There is good agreement between the masses estimated from the richness of the clusters and the average masses estimated from magnification, albeit with large uncertainties. We perform tests that suggest the absence of strong systematic effects and support the robustness of the measurement. This method - when applied to larger data sets in the future - will yield an accurate calibration of the mass-observable relations at z>~1 which will represent an invaluable input for cosmological studies using the galaxy cluster mass function and astrophysical studies of cluster formation. Furthermore this method will probably be the least expensive way to measure masses of large numbers of z>1 clusters detected in future IR-imaging surveys.
Here we introduce PHAT, the PHoto-z Accuracy Testing programme, an international initiative to test and compare different methods of photo-z estimation. Two different test environments are set up, one (PHAT0) based on simulations to test the basic fu
nctionality of the different photo-z codes, and another one (PHAT1) based on data from the GOODS survey. The accuracy of the different methods is expressed and ranked by the global photo-z bias, scatter, and outlier rates. Most methods agree well on PHAT0 but produce photo-z scatters that can differ by up to a factor of two even in this idealised case. A larger spread in accuracy is found for PHAT1. Few methods benefit from the addition of mid-IR photometry. Remaining biases and systematic effects can be explained by shortcomings in the different template sets and the use of priors on the one hand and an insufficient training set on the other hand. Scatters of 4-8% in Delta_z/(1+z) were obtained, consistent with other studies. However, somewhat larger outlier rates (>7.5% with Delta_z/(1+z)>0.15; >4.5% after cleaning) are found for all codes. There is a general trend that empirical codes produce smaller biases than template-based codes. The systematic, quantitative comparison of different photo-z codes presented here is a snapshot of the current state-of-the-art of photo-z estimation and sets a standard for the assessment of photo-z accuracy in the future. The rather large outlier rates reported here for PHAT1 on real data should be investigated further since they are most probably also present (and possibly hidden) in many other studies. The test data sets are publicly available and can be used to compare new methods to established ones and help in guiding future photo-z method development. (abridged)
