Showing papers by "University of Waterloo published in 2013"

Global carbon dioxide emissions from inland waters

Abstract: Carbon dioxide (CO2) transfer from inland waters to the atmosphere, known as CO2 evasion, is a component of the global carbon cycle. Global estimates of CO2 evasion have been hampered, however, by the lack of a framework for estimating the inland water surface area and gas transfer velocity and by the absence of a global CO2 database. Here we report regional variations in global inland water surface area, dissolved CO2 and gas transfer velocity. We obtain global CO2 evasion rates of 1.8(-0.25)(+0.25) petagrams of carbon (Pg C) per year from streams and rivers and 0.32(-0.26)(+0.52) Pg C yr(-1) from lakes and reservoirs, where the upper and lower limits are respectively the 5th and 95th confidence interval percentiles. The resulting global evasion rate of 2.1 Pg C yr(-1) is higher than previous estimates owing to a larger stream and river evasion rate. Our analysis predicts global hotspots in stream and river evasion, with about 70 per cent of the flux occurring over just 20 per cent of the land surface. The source of inland water CO2 is still not known with certainty and new studies are needed to research the mechanisms controlling CO2 evasion globally.

New approaches for high energy density lithium-sulfur battery cathodes.

Abstract: The goal of replacing combustion engines or reducing their use presents a daunting problem for society. Current lithium-ion technologies provide a stepping stone for this dramatic but inevitable change. However, the theoretical gravimetric capacity (∼300 mA h g–1) is too low to overcome the problems of limited range in electric vehicles, and their cost is too high to sustain the commercial viability of electrified transportation. Sulfur is the one of the most promising next generation cathode materials. Since the 1960s, researchers have studied sulfur as a cathode, but only recently have great strides been made in preparing viable composites that can be used commercially. Sulfur batteries implement inexpensive, earth-abundant elements at the cathode while offering up to a five-fold increase in energy density compared with present Li-ion batteries.Over the past few years, researchers have come closer to solving the challenges associated with the sulfur cathode. Using carbon or conducting polymers, research...

Terrestrial water fluxes dominated by transpiration

Abstract: An analysis of the relative effects of transpiration and evaporation, which can be distinguished by how they affect isotope ratios in water, shows that transpiration is by far the largest water flux from Earth’s continents, representing 80 to 90 per cent of terrestrial evapotranspiration and using half of all solar energy absorbed by land surfaces Water fluxes from the land surface to the atmosphere are divided between evaporation, and transpiration from leaf stomata Although a seemingly basic division between the physical and biological, there is still no consensus on the global partitioning between the two fluxes, resulting in uncertainties as to responses to future climate variations Now, Scott Jasechko and colleagues use the isotopic signatures of transpiration and evaporation from a global data set of large lakes and reveal that enormous quantities of water — as much as 90% of total terrestrial evapotranspiration — are cycled through vegetation via transpiration One conclusion to be drawn from this study is that the accuracy of biological — rather than physical — fluxes should be prioritized in work to improve climate models Renewable fresh water over continents has input from precipitation and losses to the atmosphere through evaporation and transpiration Global-scale estimates of transpiration from climate models are poorly constrained owing to large uncertainties in stomatal conductance and the lack of catchment-scale measurements required for model calibration, resulting in a range of predictions spanning 20 to 65 per cent of total terrestrial evapotranspiration (14,000 to 41,000 km3 per year) (refs 1, 2, 3, 4, 5) Here we use the distinct isotope effects of transpiration and evaporation to show that transpiration is by far the largest water flux from Earth’s continents, representing 80 to 90 per cent of terrestrial evapotranspiration On the basis of our analysis of a global data set of large lakes and rivers, we conclude that transpiration recycles 62,000 ± 8,000 km3 of water per year to the atmosphere, using half of all solar energy absorbed by land surfaces in the process We also calculate CO2 uptake by terrestrial vegetation by connecting transpiration losses to carbon assimilation using water-use efficiency ratios of plants, and show the global gross primary productivity to be 129 ± 32 gigatonnes of carbon per year, which agrees, within the uncertainty, with previous estimates6 The dominance of transpiration water fluxes in continental evapotranspiration suggests that, from the point of view of water resource forecasting, climate model development should prioritize improvements in simulations of biological fluxes rather than physical (evaporation) fluxes

Carbon-Nanotube-Embedded Hydrogel Sheets for Engineering Cardiac Constructs and Bioactuators

Abstract: We engineered functional cardiac patches by seeding neonatal rat cardiomyocytes onto carbon nanotube (CNT)-incorporated photo-cross-linkable gelatin methacrylate (GelMA) hydrogels. The resulting cardiac constructs showed excellent mechanical integrity and advanced electrophysiological functions. Specifically, myocardial tissues cultured on 50 μm thick CNT-GelMA showed 3 times higher spontaneous synchronous beating rates and 85% lower excitation threshold, compared to those cultured on pristine GelMA hydrogels. Our results indicate that the electrically conductive and nanofibrous networks formed by CNTs within a porous gelatin framework are the key characteristics of CNT-GelMA leading to improved cardiac cell adhesion, organization, and cell–cell coupling. Centimeter-scale patches were released from glass substrates to form 3D biohybrid actuators, which showed controllable linear cyclic contraction/extension, pumping, and swimming actuations. In addition, we demonstrate for the first time that cardiac tiss...

CFHTLenS tomographic weak lensing cosmological parameter constraints: Mitigating the impact of intrinsic galaxy alignments

Abstract: We present a finely-binned tomographic weak lensing analysis of the Canada-FranceHawaii Telescope Lensing Survey, CFHTLenS, mitigating contamination to the signal from the presence of intrinsic galaxy alignments via the simultaneous fit of a cosmological model and an intrinsic alignment model. CFHTLenS spans 154 square degrees in five optical bands, with accurate shear and photometric redshifts for a galaxy sample with a median redshift of zm = 0:70. We estimate the 21 sets of cosmic shear correlation functions associated with six redshift bins, each spanning the angular range of 1:5 < < 35 arcmin. We combine this CFHTLenS data with auxiliary cosmological probes: the cosmic microwave background with data from WMAP7, baryon acoustic oscillations with data from BOSS, and a prior on the Hubble constant from the HST distance ladder. This leads to constraints on the normalisation of the matter power spectrum 8 = 0:799 0:015 and the matter density parameter m = 0:271 0:010 for a flat CDM cosmology. For a flat wCDM cosmology we constrain the dark energy equation of state parameter w = 1:02 0:09. We also provide constraints for curved CDM and wCDM cosmologies. We find the intrinsic alignment contamination to be galaxy-type dependent with a significant intrinsic alignment signal found for early-type galaxies, in contrast to the late-type galaxy sample for which the intrinsic alignment signal is found to be consistent with zero.

Hyperopt: A Python Library for Optimizing the Hyperparameters of Machine Learning Algorithms

Abstract: Sequential model-based optimization (also known as Bayesian optimization) is one of the most efficient methods (per function evaluation) of function minimization. This efficiency makes it appropriate for optimizing the hyperparameters of machine learning algorithms that are slow to train. The Hyperopt library provides algorithms and parallelization infrastructure for performing hyperparameter optimization (model selection) in Python. This paper presents an introductory tutorial on the usage of the Hyperopt library, including the description of search spaces, minimization (in serial and parallel), and the analysis of the results collected in the course of minimization. The paper closes with some discussion of ongoing and future work.

Data Center Network Virtualization: A Survey

Abstract: With the growth of data volumes and variety of Internet applications, data centers (DCs) have become an efficient and promising infrastructure for supporting data storage, and providing the platform for the deployment of diversified network services and applications (e.g., video streaming, cloud computing). These applications and services often impose multifarious resource demands (storage, compute power, bandwidth, latency) on the underlying infrastructure. Existing data center architectures lack the flexibility to effectively support these applications, which results in poor support of QoS, deployability, manageability, and defence against security attacks. Data center network virtualization is a promising solution to address these problems. Virtualized data centers are envisioned to provide better management flexibility, lower cost, scalability, better resources utilization, and energy efficiency. In this paper, we present a survey of the current state-of-the-art in data center networks virtualization, and provide a detailed comparison of the surveyed proposals. We discuss the key research challenges for future research and point out some potential directions for tackling the problems related to data center design.

Resilient Asymptotic Consensus in Robust Networks

Abstract: This paper addresses the problem of resilient in-network consensus in the presence of misbehaving nodes. Secure and fault-tolerant consensus algorithms typically assume knowledge of nonlocal information; however, this assumption is not suitable for large-scale dynamic networks. To remedy this, we focus on local strategies that provide resilience to faults and compromised nodes. We design a consensus protocol based on local information that is resilient to worst-case security breaches, assuming the compromised nodes have full knowledge of the network and the intentions of the other nodes. We provide necessary and sufficient conditions for the normal nodes to reach asymptotic consensus despite the influence of the misbehaving nodes under different threat assumptions. We show that traditional metrics such as connectivity are not adequate to characterize the behavior of such algorithms, and develop a novel graph-theoretic property referred to as network robustness. Network robustness formalizes the notion of redundancy of direct information exchange between subsets of nodes in the network, and is a fundamental property for analyzing the behavior of certain distributed algorithms that use only local information.

Current density dependence of peroxide formation in the Li–O2 battery and its effect on charge

Abstract: We report a significant difference in the growth mechanism of Li2O2 in Li–O2 batteries for toroidal and thin-film morphologies which is dependent on the current rate that governs the electrochemical pathway. Evidence from diffraction, electrochemical, FESEM and STEM measurements shows that slower current densities favor aggregation of lithium peroxide nanocrystallites nucleated via solution dismutase on the surface of the electrode; whereas fast rates deposit quasi-amorphous thin films. The latter provide a lower overpotential on charge due to their nature and close contact with the conductive electrode surface, albeit at the expense of lower discharge capacity.

SCUBA-2: the 10 000 pixel bolometer camera on the James Clerk Maxwell Telescope

Abstract: SCUBA-2 is an innovative 10000 pixel bolometer camera operating at submillimetre wavelengths on the James Clerk Maxwell Telescope (JCMT). The camera has the capability to carry out wide-field surveys to unprecedented depths, addressing key questions relating to the origins of galaxies, stars and planets. With two imaging arrays working simultaneously in the atmospheric windows at 450 and 850µm, the vast increase in pixel count means that SCUBA-2 maps the sky 100–150 times faster than the previous SCUBA instrument. In this paper we present an overview of the instrument, discuss the physical characteristics of the superconducting detector arrays, outline the observing modes and data acquisition, and present the early performance figures on the telescope. We also showcase the capabilities of the instrument via some early examples of the science SCUBA-2 has already undertaken. In February 2012, SCUBA-2 began a series of unique legacy surveys for the JCMT community. These surveys will take 2.5years and the results are already providing complementary data to the shorter wavelength, shallower, larger-area surveys from Herschel. The SCUBA-2 surveys will also provide a wealth of information for further study with new facilities such as ALMA, and future telescopes such as CCAT and SPICA.

High mobility diketopyrrolopyrrole (DPP)-based organic semiconductor materials for organic thin film transistors and photovoltaics

Abstract: In recent years, the electron-accepting diketopyrrolopyrrole (DPP) moiety has been receiving considerable attention for constructing donor–acceptor (D–A) type organic semiconductors for a variety of applications, particularly for organic thin film transistors (OTFTs) and organic photovoltaics (OPVs). Through association of the DPP unit with appropriate electron donating building blocks, the resulting D–A molecules interact strongly in the solid state through intermolecular D–A and π–π interactions, leading to highly ordered structures at the molecular and microscopic levels. The closely packed molecules and crystalline domains are beneficial for intermolecular and interdomain (or intergranular) charge transport. Furthermore, the energy levels can be readily adjusted, affording p-type, n-type, or ambipolar organic semiconductors with highly efficient charge transport properties in OTFTs. In the past few years, a number of DPP-based small molecular and polymeric semiconductors have been reported to show mobility close to or greater than 1 cm2 V−1 s−1. DPP-based polymer semiconductors have achieved record high mobility values for p-type (hole mobility: 10.5 cm2 V−1 s−1), n-type (electron mobility: 3 cm2 V−1 s−1), and ambipolar (hole/electron mobilities: 1.18/1.86 cm2 V−1 s−1) OTFTs among the known polymer semiconductors. Many DPP-based organic semiconductors have favourable energy levels and band gaps along with high hole mobility, which enable them as promising donor materials for OPVs. Power conversion efficiencies (PCE) of up to 6.05% were achieved for OPVs using DPP-based polymers, demonstrating their potential usefulness for the organic solar cell technology. This article provides an overview of the recent exciting progress made in DPP-containing polymers and small molecules that have shown high charge carrier mobility, around 0.1 cm2 V−1 s−1 or greater. It focuses on the structural design, optoelectronic properties, molecular organization, morphology, as well as performances in OTFTs and OPVs of these high mobility DPP-based materials.

Objective Quality Assessment of Tone-Mapped Images

Abstract: Tone-mapping operators (TMOs) that convert high dynamic range (HDR) to low dynamic range (LDR) images provide practically useful tools for the visualization of HDR images on standard LDR displays. Different TMOs create different tone-mapped images, and a natural question is which one has the best quality. Without an appropriate quality measure, different TMOs cannot be compared, and further improvement is directionless. Subjective rating may be a reliable evaluation method, but it is expensive and time consuming, and more importantly, is difficult to be embedded into optimization frameworks. Here we propose an objective quality assessment algorithm for tone-mapped images by combining: 1) a multiscale signal fidelity measure on the basis of a modified structural similarity index and 2) a naturalness measure on the basis of intensity statistics of natural images. Validations using independent subject-rated image databases show good correlations between subjective ranking score and the proposed tone-mapped image quality index (TMQI). Furthermore, we demonstrate the extended applications of TMQI using two examples - parameter tuning for TMOs and adaptive fusion of multiple tone-mapped images.

A Meet-in-the-Middle Algorithm for Fast Synthesis of Depth-Optimal Quantum Circuits

Abstract: We present an algorithm for computing depth-optimal decompositions of logical operations, leveraging a meet-in-the-middle technique to provide a significant speedup over simple brute force algorithms. As an illustration of our method, we implemented this algorithm and found factorizations of commonly used quantum logical operations into elementary gates in the Clifford+T set. In particular, we report a decomposition of the Toffoli gate over the set of Clifford and T gates. Our decomposition achieves a total T-depth of 3, thereby providing a 40% reduction over the previously best known decomposition for the Toffoli gate. Due to the size of the search space, the algorithm is only practical for small parameters, such as the number of qubits, and the number of gates in an optimal implementation.

A tutorial on sensitivity analyses in clinical trials: the what, why, when and how

Abstract: Background Sensitivity analyses play a crucial role in assessing the robustness of the findings or conclusions based on primary analyses of data in clinical trials. They are a critical way to assess the impact, effect or influence of key assumptions or variations—such as different methods of analysis, definitions of outcomes, protocol deviations, missing data, and outliers—on the overall conclusions of a study. The current paper is the second in a series of tutorial-type manuscripts intended to discuss and clarify aspects related to key methodological issues in the design and analysis of clinical trials.

One-pot synthesis of a mesoporous NiCo2O4 nanoplatelet and graphene hybrid and its oxygen reduction and evolution activities as an efficient bi-functional electrocatalyst

Abstract: Mesoporous NiCo2O4 nanoplatelets and graphene sheets (NiCo2O4–G) are combined as a hybrid material via a one-pot synthesis process to demonstrate excellent bi-functional catalytic activity towards both the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Physical characterizations have confirmed the formation of NiCo2O4 nanoplatelets created by selective adsorption of PVP onto specific crystal orientations, which provides spatial confinement for an anisotropic growth into 2-dimensional nanostructures. In addition, the decomposition of surface adsorbed PVP during the calcination process creates uniformly distributed meso-sized pores in the NiCo2O4 nanoplatelets. The beneficial hybrid and PVP effects are investigated via half-cell testing with NiCo2O4–G in comparison to graphene-free NiCo2O4 and PVP-free NiCo2O4–G, respectively, where much lower activation energy and higher current densities are observed with the mesoporous NiCo2O4–G hybrid for both ORR and OER. Furthermore, the positive impact of Ni incorporation was exclusively demonstrated, whereby NiCo2O4–G outperformed Co3O4–G in terms of onset potential and current densities for both ORR and OER. This is attributed to the increased electrical conductivity and the creation of new active sites with much lower activation energy due to the incorporation of Ni cations into the octahedral sites of the spinel crystal structure. This cost effective and highly efficient bi-functional catalyst is highly suitable for rechargeable metal–air battery technologies.

VeMAC: A TDMA-Based MAC Protocol for Reliable Broadcast in VANETs

Abstract: The need of a medium access control (MAC) protocol for an efficient broadcast service is of great importance to support the high-priority safety applications in vehicular ad hoc networks (VANETs). This paper introduces VeMAC, a novel multichannel TDMA MAC protocol proposed specifically for a VANET scenario. The VeMAC supports efficient one-hop and multihop broadcast services on the control channel by using implicit acknowledgments and eliminating the hidden terminal problem. The protocol reduces transmission collisions due to node mobility on the control channel by assigning disjoint sets of time slots to vehicles moving in opposite directions and to road side units. Analysis and simulation results in highway and city scenarios are presented to evaluate the performance of VeMAC and compare it with ADHOC MAC, an existing TDMA MAC protocol for VANETs. It is shown that, due to its ability to decrease the rate of transmission collisions, the VeMAC protocol can provide significantly higher throughput on the control channel than ADHOC MAC.

Sulfur Speciation in Li–S Batteries Determined by Operando X-ray Absorption Spectroscopy

Abstract: Among the most challenging issues in electrochemical energy storage is developing insightful in situ probes of redox processes for a working cell. This is particularly true for cells that operate on the basis of chemical transformations such as Li–S and Li–O2, where the factors that govern capacity and cycling stability are difficult to access owing to the amorphous nature of the intermediate species. Here, we investigate cathodes for the Li–S cell comprised of sulfur-imbibed robust spherical carbon shells with tailored porosity that exhibit excellent cycling stability. Their highly regular nanoscale dimensions and thin carbon shells allow highly uniform electrochemical response and further enable direct monitoring of sulfur speciation within the cell over the entire redox range by operando X-ray absorption spectroscopy on the S K-edge. The results reveal the first detailed evidence of the mechanisms of sulfur redox chemistry on cycling, showing how sulfur fraction (under-utilization) and sulfide precipit...

Optimal Placement and Sizing Method to Improve the Voltage Stability Margin in a Distribution System Using Distributed Generation

Abstract: Recently, integration of distributed generation (DG) in distribution systems has increased to high penetration levels. The impact of DG units on the voltage stability margins has become significant. Optimization techniques are tools which can be used to locate and size the DG units in the system, so as to utilize these units optimally within certain limits and constraints. Thus, the impacts of DG units issues, such as voltage stability and voltage profile, can be analyzed effectively. The ultimate goal of this paper is to propose a method of locating and sizing DG units so as to improve the voltage stability margin. The load and renewable DG generation probabilistic nature are considered in this study. The proposed method starts by selecting candidate buses into which to install the DG units on the system, prioritizing buses which are sensitive to voltage profile and thus improve the voltage stability margin. The DG units' placement and sizing is formulated using mixed-integer nonlinear programming, with an objective function of improving the stability margin; the constraints are the system voltage limits, feeders' capacity, and the DG penetration level.

CFHTLenS: the Canada–France–Hawaii Telescope Lensing Survey – imaging data and catalogue products

Abstract: We present data products from the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS). CFHTLenS is based on the Wide component of the Canada–France–Hawaii Telescope Legacy Survey (CFHTLS). It encompasses 154 deg^2 of deep, optical, high-quality, sub-arcsecond imaging data in the five optical filters u*g′r′i′z′. The scientific aims of the CFHTLenS team are weak gravitational lensing studies supported by photometric redshift estimates for the galaxies. This paper presents our data processing of the complete CFHTLenS data set. We were able to obtain a data set with very good image quality and high-quality astrometric and photometric calibration. Our external astrometric accuracy is between 60 and 70 mas with respect to Sloan Digital Sky Survey (SDSS) data, and the internal alignment in all filters is around 30 mas. Our average photometric calibration shows a dispersion of the order of 0.01–0.03 mag for g′r′i′z′ and about 0.04 mag for u* with respect to SDSS sources down to i_(SDSS) ≤ 21. We demonstrate in accompanying papers that our data meet necessary requirements to fully exploit the survey for weak gravitational lensing analyses in connection with photometric redshift studies. In the spirit of the CFHTLS, all our data products are released to the astronomical community via the Canadian Astronomy Data Centre at http://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/community/CFHTLens/query.html. We give a description and how-to manuals of the public products which include image pixel data, source catalogues with photometric redshift estimates and all relevant quantities to perform weak lensing studies.

Constraining self-interacting dark matter with the Milky Way’s dwarf spheroidals

Abstract: Self-Interacting Dark Matter is an attractive alternative to the Cold Dark Matter paradigm only if it is able to substantially reduce the central densities of dwarf-size haloes while keeping the densities and shapes of cluster-size haloes within current constraints. Given the seemingly stringent nature of the latter, it was thought for nearly a decade that Self-Interacting Dark Matter would be viable only if the cross section for self-scattering was strongly velocitydependent. However, it has recently been suggested that a constant cross section per unit mass of T=m 0:1cm 2 g 1 is sufficient to accomplish the desired effect. We explicitly investigate this claim using high resolution cosmological simulations of a Milky-Way size halo and find that, similarly to the Cold Dark Matter case, such cross section produces a population of massive subhaloes that is inconsistent with the kinematics of the classical dwarf spheroidals, in particular with the inferred slopes of the mass profiles of Fornax and Sculptor. This problem is resolved if T=m 1cm 2 g 1 at the dwarf spheroidal scales. Since this value is likely inconsistent with the halo shapes of several clusters, our results leave only a small window open for a velocity-independent Self-Interacting Dark Matter model to work as a distinct alternative to Cold Dark Matter.

Bayesian galaxy shape measurement for weak lensing surveys – III. Application to the Canada–France–Hawaii Telescope Lensing Survey

Abstract: A likelihood-based method for measuring weak gravitational lensing shear in deep galaxy surveys is described and applied to the Canada–France–Hawaii Telescope (CFHT) Lensing Survey (CFHTLenS) CFHTLenS comprises 154 deg^2 of multi-colour optical data from the CFHT Legacy Survey, with lensing measurements being made in the i′ band to a depth i′_(AB) < 247, for galaxies with signal-to-noise ratio ν_(SN) ≳ 10 The method is based on the lensfit algorithm described in earlier papers, but here we describe a full analysis pipeline that takes into account the properties of real surveys The method creates pixel-based models of the varying point spread function (PSF) in individual image exposures It fits PSF-convolved two-component (disc plus bulge) models to measure the ellipticity of each galaxy, with Bayesian marginalization over model nuisance parameters of galaxy position, size, brightness and bulge fraction The method allows optimal joint measurement of multiple, dithered image exposures, taking into account imaging distortion and the alignment of the multiple measurements We discuss the effects of noise bias on the likelihood distribution of galaxy ellipticity Two sets of image simulations that mirror the observed properties of CFHTLenS have been created to establish the method's accuracy and to derive an empirical correction for the effects of noise bias

Tailoring Porosity in Carbon Nanospheres for Lithium–Sulfur Battery Cathodes

Abstract: Porous hollow carbon spheres with different tailored pore structures have been designed as conducting frameworks for lithium-sulfur battery cathode materials that exhibit stable cycling capacity. By deliberately creating shell porosity and utilizing the interior void volume of the carbon spheres, sufficient space for sulfur storage as well as electrolyte pathways is guaranteed. The effect of different approaches to develop shell porosity is examined and compared in this study. The most highly optimized sulfur-porous carbon nanosphere composite, created using pore-formers to tailor shell porosity, exhibits excellent cycling performance and rate capability. Sulfur is primarily confined in 4-5 nm mesopores in the carbon shell and inner lining of the shells, which is beneficial for enhancing charge transfer and accommodating volume expansion of sulfur during redox cycling. Little capacity degradation (∼0.1% /cycle) is observed over 100 cycles for the optimized material.

Universal Computation by Multiparticle Quantum Walk

Abstract: A quantum walk is a time-homogeneous quantum-mechanical process on a graph defined by analogy to classical random walk. The quantum walker is a particle that moves from a given vertex to adjacent vertices in quantum superposition. We consider a generalization to interacting systems with more than one walker, such as the Bose-Hubbard model and systems of fermions or distinguishable particles with nearest-neighbor interactions, and show that multiparticle quantum walk is capable of universal quantum computation. Our construction could, in principle, be used as an architecture for building a scalable quantum computer with no need for time-dependent control.

CFHTLenS: combined probe cosmological model comparison using 2D weak gravitational lensing

Abstract: We present cosmological constraints from 2D weak gravitational lensing by the large-scale structure in the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) which spans 154 deg^2 in five optical bands. Using accurate photometric redshifts and measured shapes for 4.2 million galaxies between redshifts of 0.2 and 1.3, we compute the 2D cosmic shear correlation function over angular scales ranging between 0.8 and 350 arcmin. Using non-linear models of the dark-matter power spectrum, we constrain cosmological parameters by exploring the parameter space with Population Monte Carlo sampling. The best constraints from lensing alone are obtained for the small-scale density-fluctuations amplitude σ_8 scaled with the total matter density Ωm. For a flat Λcold dark matter (ΛCDM) model we obtain σ_8(Ω_m/0.27)0.6 = 0.79 ± 0.03. We combine the CFHTLenS data with 7-year Wilkinson Microwave Anisotropy Probe (WMAP7), baryonic acoustic oscillations (BAO): SDSS-III (BOSS) and a Hubble Space Telescope distance-ladder prior on the Hubble constant to get joint constraints. For a flat ΛCDM model, we find Ω_m = 0.283 ± 0.010 and σ_8 = 0.813 ± 0.014. In the case of a curved wCDM universe, we obtain Ω_m = 0.27 ± 0.03, σ_8 = 0.83 ± 0.04, w0 = −1.10 ± 0.15 and Ω_K = 0.006^(+0.006)_(− 0.004). We calculate the Bayesian evidence to compare flat and curved ΛCDM and dark-energy CDM models. From the combination of all four probes, we find models with curvature to be at moderately disfavoured with respect to the flat case. A simple dark-energy model is indistinguishable from ΛCDM. Our results therefore do not necessitate any deviations from the standard cosmological model.