Mapping and simulating systematics due to spatially-varying observing conditions in DES Science Verification data

Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. We illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on $N(z)$, the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. The framework presented here is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope (LSST), which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky

Dark energy survey year 1 results: Redshift distributions of the weak-lensing source galaxies

We describe the derivation and validation of redshift distribution estimates and their uncertainties for the populations of galaxies used as weak-lensing sources in the Dark Energy Survey (DES) Year 1 cosmological analyses. The Bayesian Photometric Redshift (BPZ) code is used to assign galaxies to four redshift bins between z ≈ 0.2 and ≈1.3, and to produce initial estimates of the lensing-weighted redshift distributions nPZi(z) ∝ dni/dz for members of bin i. Accurate determination of cosmological parameters depends critically on knowledge of ni, but is insensitive to bin assignments or redshift errors for individual galaxies. The cosmological analyses allow for shifts ni (z) = nPZi(z - Δzi) to correct themean redshift of ni(z) for biases in nPZi. The Δzi are constrained by comparison of independently estimated 30-band photometric redshifts of galaxies in the Cosmic Evolution Survey (COSMOS) field to BPZ estimates made from the DES griz fluxes, for a sample matched in fluxes, pre-seeing size, and lensing weight to the DES weak-lensing sources. In companion papers, the Δzi of the three lowest redshift bins are further constrained by the angular clustering of the source galaxies around red galaxies with secure photometric redshifts at 0.15 < z < 0.9. This paper details the BPZ and COSMOS procedures, and demonstrates that the cosmological inference is insensitive to details of the ni(z) beyond the choice of Δzi. The clustering and COSMOS validation methods produce consistent estimates of Δzi in the bins where both can be applied, with combined uncertainties of σΔzi = 0.015, 0.013, 0.011, and 0.022 in the four bins. Repeating the photo-z procedure instead using the Directional Neighbourhood Fitting algorithm, or using the ni(z) estimated from the matched sample in COSMOS, yields no discernible difference in cosmological inferences

Effect of Size, Content and Shape of Reinforcements on the Behavior of Metal Matrix Composites (MMCs) Under Tension

The objective of this research was to investigate the mechanical behavior of metal matrix composites (MMCs) 6061 aluminum, reinforced with silicon carbide particles, under unidirectional tensile loading by finite element analysis. The effects of particle’s shape, size and content on the tensile properties of the composites were studied and compared with each other. In addition, stress and strain distributions and possible particle fracture or debonding were investigated. It was found that, among different shapes, a certain shape of reinforcement particle provided better tensile properties for MMCs and, within each shape category, composites with smaller particle size and higher particle content (20%) also showed better properties. It was also found that when the reinforcement content was 10%, the effects of shape and size of the particles were negligible. Not only interfacial length between the reinforcement and matrix materials, but also state of matrix material, due to the presence of the reinforcement particles, affected the stiffness of the MMCs. In almost all of the cases, except for MMCs with triangular particles, when the stress increased, with the increase in the applied positive displacement, the stress distributions remained unchanged

Intellectual Capital and Innovation for Sustainable Smart Cities: The Case of N-Tuple of Helices

The purpose of this chapter is to explore and discuss, in the context of Smart Cities (SC), the relations between three concepts: Intellectual Capital (IC), Innovation Process (IP) and Sustainability (S). It is important to note that, in this context, the concept of IC refers to Smart Cities Intellectual Capital (SCIC), which is characterised by four components (Human Capital, Process Capital, Renewal Capital, Clients Capital), also used for Nations IC. The Innovation analysis considers two models: the first one expresses the dependencies and limits of innovation, resulting from physical limitations such as city area and city population; and the second one is the N-Tuple of Helices model. The concept of Smart City will be modelled as a living being capable of rational behaviour, knowledge production, and intellectual activity

Cosmology from cosmic shear with Dark Energy Survey Science Verification data

We present the first constraints on cosmology from the Dark Energy Survey (DES), using weak lensing measurements from the preliminary Science Verification (SV) data. We use 139 square degrees of SV data, which is less than 3% of the full DES survey area. Using cosmic shear 2-point measurements over three redshift bins we find σ8(Ωm/0.3)0.5=0.81±0.06 (68% confidence), after marginalizing over 7 systematics parameters and 3 other cosmological parameters. We examine the robustness of our results to the choice of data vector and systematics assumed, and find them to be stable. About 20% of our error bar comes from marginalizing over shear and photometric redshift calibration uncertainties. The current state-of-the-art cosmic shear measurements from CFHTLenS are mildly discrepant with the cosmological constraints from Planck CMB data; our results are consistent with both data sets. Our uncertainties are ∼30% larger than those from CFHTLenS when we carry out a comparable analysis of the two data sets, which we attribute largely to the lower number density of our shear catalogue. We investigate constraints on dark energy and find that, with this small fraction of the full survey, the DES SV constraints make negligible impact on the Planck constraints. The moderate disagreement between the CFHTLenS and Planck values of σ8(Ωm/0.3)0.5 is present regardless of the value of w

Redshift distributions of galaxies in the Dark Energy Survey Science Verification shear catalogue and implications for weak lensing

We present photometric redshift estimates for galaxies used in the weak lensing analysis of the Dark Energy Survey Science Verification (DES SV) data. Four model- or machine learning-based photometric redshift methods - annz2, bpz calibrated against BCC-Ufig simulations, skynet, and tpz - are analyzed. For training, calibration, and testing of these methods, we construct a catalogue of spectroscopically confirmed galaxies matched against DES SV data. The performance of the methods is evaluated against the matched spectroscopic catalogue, focusing on metrics relevant for weak lensing analyses, with additional validation against COSMOS photo-z's. From the galaxies in the DES SV shear catalogue, which have mean redshift 0.72±0.01 over the range 0.