Hierarchical Probabilistic Inference of Cosmic Shear
Abstract not provided
Engineering topics
Publications and source records attributed to Marshall, P J.
Abstract not provided
Abstract Not Provided
The complete 10-year survey from the Large Synoptic Survey Telescope (LSST) will image {approx} 20,000 square degrees of sky in six filter bands every few nights, bringing the final survey depth to r {approx} 27.5, with over 4 billion well measured galaxies. To take full advantage of this unprecedented statistical power, the systematic errors associated with weak lensing measurements need to be controlled to a level similar to the statistical errors. This work is the first attempt to quantitatively estimate the absolute level and statistical properties of the systematic errors on weak lensing shear measurements due to the most important physical effects in the LSST system via high fidelity ray-tracing simulations. We identify and isolate the different sources of algorithm-independent, additive systematic errors on shear measurements for LSST and predict their impact on the final cosmic shear measurements using conventional weak lensing analysis techniques. We find that the main source of the errors comes from an inability to adequately characterise the atmospheric point spread function (PSF) due to its high frequency spatial variation on angular scales smaller than {approx} 10{prime} in the single short exposures, which propagates into a spurious shear correlation function at the 10{sup -4}-10{sup -3} level on these scales. With the large multi-epoch dataset that will be acquired by LSST, the stochastic errors average out, bringing the final spurious shear correlation function to a level very close to the statistical errors. Our results imply that the cosmological constraints from LSST will not be severely limited by these algorithm-independent, additive systematic effects.
A main science goal for the Large Synoptic Survey Telescope (LSST) is to measure the cosmic shear signal from weak lensing to extreme accuracy. One difficulty, however, is that with the short exposure time ({approx_equal}15 seconds) proposed, the spatial variation of the Point Spread Function (PSF) shapes may be dominated by the atmosphere, in addition to optics errors. While optics errors mainly cause the PSF to vary on angular scales similar or larger than a single CCD sensor, the atmosphere generates stochastic structures on a wide range of angular scales. It thus becomes a challenge to infer the multi-scale, complex atmospheric PSF patterns by interpolating the sparsely sampled stars in the field. In this paper we present a new method, psfent, for interpolating the PSF shape parameters, based on reconstructing underlying shape parameter maps with a multi-scale maximum entropy algorithm. We demonstrate, using images from the LSST Photon Simulator, the performance of our approach relative to a 5th-order polynomial fit (representing the current standard) and a simple boxcar smoothing technique. Quantitatively, psfent predicts more accurate PSF models in all scenarios and the residual PSF errors are spatially less correlated. This improvement in PSF interpolation leads to a factor of 3.5 lower systematic errors in the shear power spectrum on scales smaller than {approx} 13, compared to polynomial fitting. We estimate that with psfent and for stellar densities greater than {approx_equal}1/arcmin{sup 2}, the spurious shear correlation from PSF interpolation, after combining a complete 10-year dataset from LSST, is lower than the corresponding statistical uncertainties on the cosmic shear power spectrum, even under a conservative scenario.
Stars and dark matter account for most of the mass of early-type galaxies, but uncertainties in the stellar population and the dark matter profile make it challenging to distinguish between the two components. Nevertheless, precise observations of stellar and dark matter are extremely valuable for testing the many models of structure formation and evolution. We present a measurement of the stellar mass and inner slope of the dark matter halo of a massive early-type galaxy at z = 0.222. The galaxy is the foreground deflector of the double Einstein ring gravitational lens system SDSSJ0946+1006, also known as the 'Jackpot'. By combining the tools of lensing and dynamics we first constrain the mean slope of the total mass density profile ({rho}{sub tot}{proportional_to}r{sup -{gamma}{sup '}}) within the radius of the outer ring to be {gamma}' = 1.98 {+-} 0.02 {+-} 0.01. Then we obtain a bulge-halo decomposition, assuming a power-law form for the dark matter halo. Our analysis yields {gamma}{sub DM} = 1.7 {+-} 0.2 for the inner slope of the dark matter profile, in agreement with theoretical findings on the distribution of dark matter in ellipticals, and a stellar mass from lensing and dynamics M{sup LD}{sub *} = 5.5{sub -1.3}{sup +0.4} Multiplication-Sign 10{sup 11} M{sub Sun }. By comparing this measurement with stellar masses inferred from stellar population synthesis fitting we find that a Salpeter initial mass function (IMF) provides a good description of the stellar population of the lens while the probability of the IMF being heavier than Chabrier is 95%. Our data suggest that growth by accretion of small systems from a compact red nugget is a plausible formation scenario for this object.
We infer the normalization and the radial and angular distributions of the number density of satellites of massive galaxies (log{sub 10}[M*{sub h}/M{sub Sun }] > 10.5) between redshifts 0.1 and 0.8 as a function of host stellar mass, redshift, morphology, and satellite luminosity. Exploiting the depth and resolution of the COSMOS Hubble Space Telescope images, we detect satellites up to 8 mag fainter than the host galaxies and as close as 0.3 (1.4) arcsec (kpc). Describing the number density profile of satellite galaxies to be a projected power law such that P(R){proportional_to}R{sup {gamma}{sub p}}, we find {gamma}{sub p} = -1.1 {+-} 0.3. We find no dependency of {gamma}{sub p} on host stellar mass, redshift, morphology, or satellite luminosity. Satellites of early-type hosts have angular distributions that are more flattened than the host light profile and are aligned with its major axis. No significant average alignment is detected for satellites of late-type hosts. The number of satellites within a fixed magnitude contrast from a host galaxy is dependent on its stellar mass, with more massive galaxies hosting significantly more satellites. Furthermore, high-mass late-type hosts have significantly fewer satellites than early-type galaxies of the same stellar mass, possibly indicating that they reside in more massive halos. No significant evolution in the number of satellites per host is detected. The cumulative luminosity function of satellites is qualitatively in good agreement with that predicted using SubHalo Abundance Matching techniques. However, there are significant residual discrepancies in the absolute normalization, suggesting that properties other than the host galaxy luminosity or stellar mass determine the number of satellites.