Source-lens clustering effects on the skewness of the lensing convergence

Monthly Notices of the Royal Astronomical Society 330:2 (2002) 365-377

Authors:

T Hamana, ST Colombi, A Thion, JEGT Devriendt, Y Mellier, F Bernardeau

Abstract:

potentials causes a systematic effect on measurements of cosmic shear statistics, known as the source-lens clustering (SLC) effect. The SLC effect on the skewness of lensing convergence, S3, is examined using a non-linear semi-analytic approach and is checked against numerical simulations. The semi-analytic calculations have been performed in a wide variety of generic models for the redshift distribution of source galaxies and power-law models for the bias parameter between the galaxy and dark matter distributions. The semi-analytic predictions are tested successfully against numerical simulations. We find the relative amplitude of the SLC effect on S3 to be of the order of 5 -40 per cent. It depends significantly on the redshift distribution of sources and on the way in which the bias parameter evolves. We discuss possible measurement strategies to minimize the SLC effects.

The 2dF BL Lac Survey

ArXiv astro-ph/0202386 (2002)

Authors:

D Londish, SM Croom, BJ Boyle, T Shanks, PJ Outram, EM Sadler, NS Loaring, RJ Smith, L Miller, PFL Maxted

Abstract:

We have optically identified a sample of 56 featureless continuum objects without significant proper motion from the 2dF QSO Redshift Survey (2QZ). The steep number--magnitude relation of the sample, $n(\bj) \propto 10^{0.7\bj}$, is similar to that derived for QSOs in the 2QZ and inconsistent with any population of Galactic objects. Follow up high resolution, high signal-to-noise, spectroscopy of five randomly selected objects confirms the featureless nature of these sources. Assuming the objects in the sample to be largely featureless AGN, and using the QSO evolution model derived for the 2QZ, we predict the median redshift of the sample to be $z=1.1$. This model also reproduces the observed number-magnitude relation of the sample using a renormalisation of the QSO luminosity function, $\Phi^* = \Phi^*_{\rm \sc qso}/66 \simeq 1.65 \times 10^{-8} $mag$^{-1}$Mpc$^{-3}$. Only $\sim$20 per cent of the objects have a radio flux density of $S_{1.4}>3 $mJy, and further VLA observations at 8.4 GHz place a $5\sigma$ limit of $S_{8.4} < 0.2$mJy on the bulk of the sample. We postulate that these objects could form a population of radio-weak AGN with weak or absent emission lines, whose optical spectra are indistinguishable from those of BL Lac objects.

Merger histories in warm dark matter structure formation scenarios

Monthly Notices of the Royal Astronomical Society 329:4 (2002) 813-828

Authors:

JEG Devriendt, Knebe, A., Mahmood, A., Silk, J.

Making maps of the cosmic microwave background: The MAXIMA example

Physical Review D 65:2 (2002)

Authors:

R Stompor, A Balbi, JD Borrill, PG Ferreira, S Hanany, AH Jaffe, AT Lee, S Oh, B Rabii, PL Richards, GF Smoot, CD Winant, JHP Wu

Abstract:

This work describes cosmic microwave background (CMB) data analysis algorithms and their implementations, developed to produce a pixelized map of the sky and a corresponding pixel-pixel noise correlation matrix from time ordered data for a CMB mapping experiment. We discuss in turn algorithms for estimating noise properties from the time ordered data, techniques for manipulating the time ordered data, and a number of variants of the maximum likelihood map-making procedure. We pay particular attention to issues pertinent to real CMB data, and present ways of incorporating them within the framework of maximum likelihood map making. Making a map of the sky is shown to be not only an intermediate step rendering an image of the sky, but also an important diagnostic stage, when tests for and/or removal of systematic effects can efficiently be performed. The case under study is the MAXIMA-I data set. However, the methods discussed are expected to be applicable to the analysis of other current and forthcoming CMB experiments. ©2001 The American Physical Society.

A Bayesian non-parametric method to detect clusters in Planck data

MONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY 336:4 (2002) 1351-1363

Authors:

JM Diego, P Vielva, E Martínez-González, J Silk, JL Sanz