Towards Precision LSST Weak-Lensing Measurement - I: Impacts of Atmospheric Turbulence and Optical Aberration

The weak-lensing science of the LSST project drives the need to carefully model and separate the instrumental artifacts from the intrinsic lensing signal. The dominant source of the systematics for all ground based telescopes is the spatial correlation of the PSF modulated by both atmospheric turbulence and optical aberrations. In this paper, we present a full FOV simulation of the LSST images by modeling both the atmosphere and the telescope optics with the most current data for the telescope specifications and the environment. To simulate the effects of atmospheric turbulence, we generated six-layer phase screens with the parameters estimated from the on-site measurements. For the optics, we combined the ray-tracing tool ZEMAX and our simulated focal plane data to introduce realistic aberrations and focal plane height fluctuations. Although this expected flatness deviation for LSST is small compared with that of other existing cameras, the fast f-ratio of the LSST optics makes this focal plane flatness variation and the resulting PSF discontinuities across the CCD boundaries significant challenges in our removal of the systematics. We resolve this complication by performing PCA CCD-by-CCD, and interpolating the basis functions using conventional polynomials. We demonstrate that this PSF correction scheme reduces the residual PSF ellipticity correlation below 10^-7 over the cosmologically interesting scale. From a null test using HST/UDF galaxy images without input shear, we verify that the amplitude of the galaxy ellipticity correlation function, after the PSF correction, is consistent with the shot noise set by the finite number of objects. Therefore, we conclude that the current optical design and specification for the accuracy in the focal plane assembly are sufficient to enable the control of the PSF systematics required for weak-lensing science with the LSST.Comment: Accepted to PASP. High-resolution version is available at http://dls.physics.ucdavis.edu/~mkjee/LSST_weak_lensing_simulation.pd

Long-Distance Wind-Dispersal of Spores in a Fungal Plant Pathogen: Estimation of Anisotropic Dispersal Kernels from an Extensive Field Experiment

Given its biological significance, determining the dispersal kernel (i.e., the distribution of dispersal distances) of spore-producing pathogens is essential. Here, we report two field experiments designed to measure disease gradients caused by sexually- and asexually-produced spores of the wind-dispersed banana plant fungus Mycosphaerella fijiensis. Gradients were measured during a single generation and over 272 traps installed up to 1000 m along eight directions radiating from a traceable source of inoculum composed of fungicide-resistant strains. We adjusted several kernels differing in the shape of their tail and tested for two types of anisotropy. Contrasting dispersal kernels were observed between the two types of spores. For sexual spores (ascospores), we characterized both a steep gradient in the first few metres in all directions and rare long-distance dispersal (LDD) events up to 1000 m from the source in two directions. A heavy-tailed kernel best fitted the disease gradient. Although ascospores distributed evenly in all directions, average dispersal distance was greater in two different directions without obvious correlation with wind patterns. For asexual spores (conidia), few dispersal events occurred outside of the source plot. A gradient up to 12.5 m from the source was observed in one direction only. Accordingly, a thin-tailed kernel best fitted the disease gradient, and anisotropy in both density and distance was correlated with averaged daily wind gust. We discuss the validity of our results as well as their implications in terms of disease diffusion and management strategy

Computer model calibration with large non-stationary spatial outputs: application to the calibration of a climate model

Bayesian calibration of computer models tunes unknown input parameters by comparing outputs with observations. For model outputs that are distributed over space, this becomes computationally expensive because of the output size. To overcome this challenge, we employ a basis representation of the model outputs and observations: we match these decompositions to carry out the calibration efficiently. In the second step, we incorporate the non-stationary behaviour, in terms of spatial variations of both variance and correlations, in the calibration. We insert two integrated nested Laplace approximation-stochastic partial differential equation parameters into the calibration. A synthetic example and a climate model illustration highlight the benefits of our approach

Space-Varying Coefficient Models for Brain Imaging

The methodological development and the application in this paper originate from diffusion tensor imaging (DTI), a powerful nuclear magnetic resonance technique enabling diagnosis and monitoring of several diseases as well as reconstruction of neural pathways. We reformulate the current analysis framework of separate voxelwise regressions as a 3d space-varying coefficient model (VCM) for the entire set of DTI images recorded on a 3d grid of voxels. Hence by allowing to borrow strength from spatially adjacent voxels, to smooth noisy observations, and to estimate diffusion tensors at any location within the brain, the three-step cascade of standard data processing is overcome simultaneously. We conceptualize two VCM variants based on B-spline basis functions: a full tensor product approach and a sequential approximation, rendering the VCM numerically and computationally feasible even for the huge dimension of the joint model in a realistic setup. A simulation study shows that both approaches outperform the standard method of voxelwise regressions with subsequent regularization. Due to major efficacy, we apply the sequential method to a clinical DTI data set and demonstrate the inherent ability of increasing the rigid grid resolution by evaluating the incorporated basis functions at intermediate points. In conclusion, the suggested fitting methods clearly improve the current state-of-the-art, but ameloriation of local adaptivity remains desirable

Analysis of textile composite structures with finite Volume-p-Elements

Anisotropic textile composites show nonlinear deformation and complex fai- lure behaviour. In particular three-dimensional reinforced textile composites are characterised by an orthotropic material behaviour. To achieve the full po- tential of textile composites the material and especially the failure behaviour has to be analysed particularly for regions dominated by three-dimensional stress distributions, e. g. load introduction areas. For these purposes finite volume-p-elements based on hierarchical shape functions are being developed. Furthermore the constitutive model is en- hanced to simulate material degradation and failure processes. Based on an anisotropic continuum damage model the material degradation is described with tensorial damage variables that characterise the crack density observed in experimental studies of Non-Crimp-Fabrics with E-Glass fibres. The deter- mination of the onset of degradation and the strength prediction is enabled by coupling the damage model with a failure criterion for three-dimensional reinforced plastics. Due to control the spatial adaptivity of polynomial order of the shape functi- ons different a posteriori error estimators are evaluated and compared espe- cially with respect to the applicability on structural models representing or- thotropic material behaviour. Experimental analyses were used to determine the parameters of the consti- tutive model. Besides the in-plane properties the through-thickness material properties are assumed to be primarily important for textile composites. The- refore a modified Arcan testing device was developed which provides test results for biaxial tension and shear load combinations taking the material thickness direction into account. Finally simulations and experimental analyses of a thick double holed plate - the loadintroduction of an elevator bucket - demonstrate the applicability of the material model and finite element implementation