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CLUSTERING OF SLOAN DIGITAL SKY SURVEY III PHOTOMETRIC LUMINOUS GALAXIES: THE MEASUREMENT, SYSTEMATICS, AND COSMOLOGICAL IMPLICATIONS
The Sloan Digital Sky Survey (SDSS) surveyed 14,555 deg{sup 2}, and delivered over a trillion pixels of imaging data. We present a study of galaxy clustering using 900,000 luminous galaxies with photometric redshifts, spanning between z = 0.45 and z = 0.65, constructed from the SDSS using methods described in Ross et al. This data set spans 11,000 deg{sup 2} and probes a volume of 3 h {sup -3} Gpc{sup 3}, making it the largest volume ever used for galaxy clustering measurements. We describe in detail the construction of the survey window function and various systematics affecting our measurement. With such a large volume, high-precision cosmological constraints can be obtained given careful control and understanding of the observational systematics. We present a novel treatment of the observational systematics and its applications to the clustering signals from the data set. In this paper, we measure the angular clustering using an optimal quadratic estimator at four redshift slices with an accuracy of {approx}15%, with a bin size of {delta}{sub l} = 10 on scales of the baryon acoustic oscillations (BAOs; at l {approx} 40-400). We also apply corrections to the power spectra due to systematics and derive cosmological constraints using the full shape of the power spectra. For a flat {Lambda}CDM model, when combined with cosmic microwave background Wilkinson Microwave Anisotropy Probe 7 (WMAP7) and H{sub 0} constraints from using 600 Cepheids observed by Wide Field Camera 3 (WFC3; HST), we find {Omega}{sub {Lambda}} = 0.73 {+-} 0.019 and H{sub 0} to be 70.5 {+-} 1.6 s{sup -1} Mpc{sup -1} km. For an open {Lambda}CDM model, when combined with WMAP7 + HST, we find {Omega}{sub K} = 0.0035 {+-} 0.0054, improved over WMAP7+HST alone by 40%. For a wCDM model, when combined with WMAP7+HST+SN, we find w = -1.071 {+-} 0.078, and H{sub 0} to be 71.3 {+-} 1.7 s{sup -1} Mpc{sup -1} km, which is competitive with the latest large-scale structure constraints from large spectroscopic surveys such as the SDSS Data Release 7 (DR7) and WiggleZ. We also find that systematic-corrected power spectra give consistent constraints on cosmological models when compared with pre-systematic correction power spectra in the angular scales of interest. The SDSS-III Data Release 8 (SDSS-III DR8) Angular Clustering Data allow a wide range of investigations into the cosmological model, cosmic expansion (via BAO), Gaussianity of initial conditions, and neutrino masses. Here, we refer to our companion papers for further investigations using the clustering data. Our calculation of the survey selection function, systematics maps, and likelihood function for the COSMOMC package will be released at http://portal.nersc.gov/project/boss/galaxy/photoz/.
Experience of Migrating a Parallel Graph Coloring Program from CUDA to SYCL
We describe the experience of converting a CUDA implementation of a parallel graph coloring algorithm to SYCL. The goals are for our work to be useful to application and compiler developers by providing a detailed description of migration paths between CUDA and SYCL. We will describe how CUDA functions are mapped to SYCL functions. Evaluating the CUDA and SYCL implementations of the algorithm shows that the performance of SYCL and CUDA kernels are comparable over the test graph set on NVIDIA P100 and V100 GPUs. The SYCL program also allows for performance evaluation with the OpenCL and Level Zero interfaces and power profiling on an Intel GPU computing platform.
Functional and structural mapping of human cerebral cortex: solutions are in the surfaces
No abstract available
Five-Year Wilkinson Microwave Anisotropy Probe (WMAP)Observations: Beam Maps and Window Functions
Cosmology and other scientific results from the WMAP mission require an accurate knowledge of the beam patterns in flight. While the degree of beam knowledge for the WMAP one-year and three-year results was unprecedented for a CMB experiment, we have significantly improved the beam determination as part of the five-year data release. Physical optics fits are done on both the A and the B sides for the first time. The cutoff scale of the fitted distortions on the primary mirror is reduced by a factor of approximately 2 from previous analyses. These changes enable an improvement in the hybridization of Jupiter data with beam models, which is optimized with respect to error in the main beam solid angle. An increase in main-beam solid angle of approximately 1% is found for the V2 and W1-W4 differencing assemblies. Although the five-year results are statistically consistent with previous ones, the errors in the five-year beam transfer functions are reduced by a factor of approximately 2 as compared to the three-year analysis. We present radiometry of the planet Jupiter as a test of the beam consistency and as a calibration standard; for an individual differencing assembly. errors in the measured disk temperature are approximately 0.5%.
Scaling Functional Traits From Leaves to Canopies
In this chapter, we begin by exploring the relationship between plant functional traits and functional diversity and how this relates to the characterization and monitoring of global plant biodiversity. We then discuss the connection between leaf functional traits and their resulting optical properties (i.e. reflectance, transmittance, andabsorption) and how this related to remote sensing (RS) of functional diversity. Building on this, we briefly discuss the history of RS of functional traits using spectroscopy and imaging spectroscopy data. We include a discussion of the key considerations with the use of imaging spectroscopy data for scaling and mapping plant functional traits across diverse landscapes. From here we provide a review of the general methods for scaling and mapping functional traits, including empirical and radiative transfer model (RTM) approaches. We complete the chapter with a discussion of other key considerations, such as field sampling protocols, as well as current caveats and future opportunities.
High-throughput characterization, correlation, and mapping of leaf photosynthetic and functional traits in the soybean ( Glycine max ) nested association mapping population
We report photosynthesis is a key target to improve crop production in many species including soybean [Glycine max (L.) Merr.]. A challenge is that phenotyping photosynthetic traits by traditional approaches is slow and destructive. There is proof-of-concept for leaf hyperspectral reflectance as a rapid method to model photosynthetic traits. However, the crucial step of demonstrating that hyperspectral approaches can be used to advance understanding of the genetic architecture of photosynthetic traits is untested. To address this challenge, we used full-range (500–2,400 nm) leaf reflectance spectroscopy to build partial least squares regression models to estimate leaf traits, including the rate-limiting processes of photosynthesis, maximum Rubisco carboxylation rate, and maximum electron transport. In total, 11 models were produced from a diverse population of soybean sampled over multiple field seasons to estimate photosynthetic parameters, chlorophyll content, leaf carbon and leaf nitrogen percentage, and specific leaf area (with R 2 from 0.56 to 0.96 and root mean square error approximately <10% of the range of calibration data). We explore the utility of these models by applying them to the soybean nested association mapping population, which showed variability in photosynthetic and leaf traits. Genetic mapping provided insights into the underlying genetic architecture of photosynthetic traits and potential improvement in soybean. Notably, the maximum Rubisco carboxylation rate mapped to a region of chromosome 19 containing genes encoding multiple small subunits of Rubisco. We also mapped the maximum electron transport rate to a region of chromosome 10 containing a fructose 1,6-bisphosphatase gene, encoding an important enzyme in the regeneration of ribulose 1,5-bisphosphate and the sucrose biosynthetic pathway. The estimated rate-limiting steps of photosynthesis were low or negatively correlated with yield suggesting that these traits are not influenced by the same genetic mechanisms and are not limiting yield in the soybean NAM population. Leaf carbon percentage, leaf nitrogen percentage, and specific leaf area showed strong correlations with yield and may be of interest in breeding programs as a proxy for yield. This work is among the first to use hyperspectral reflectance to model and map the genetic architecture of the rate-limiting steps of photosynthesis.
Integration of a satellite ground support system based on analysis of the satellite ground support domain
This analysis defines a complete set of ground support functions based on those practiced in real space flight operations during the on-orbit phase of a mission. These functions are mapped against ground support functions currently in use by NASA and DOD. Software components to provide these functions can be hosted on RISC-based work stations and integrated to provide a modular, integrated ground support system. Such modular systems can be configured to provide as much ground support functionality as desired. This approach to ground systems has been widely proposed and prototyped both by government institutions and commercial vendors. The combined set of ground support functions we describe can be used as a standard to evaluate candidate ground systems. This approach has also been used to develop a prototype of a modular, loosely-integrated ground support system, which is discussed briefly. A crucial benefit to a potential user is that all the components are flight-qualified, thus giving high confidence in their accuracy and reliability.
Heat Analysis Manager (HAM), a Thermal Desktop API Based Heat Map Generation Software
Thermal engineers often create custom heat maps to analyze their thermal model. However, generating a heat map is difficult because thermal simulation only readily provide attributes of simulated nodes such as temperature, capacitance, heat generation, and a network of conductances. Heat flow values are a derived quantity from the nodal attributes, and the data processing and management of heat flow between nodes quickly become difficult for large models. Deriving a network of heat flow values requires vast amount of calculations and data handling, heat map generation process generally suffers from processing speed, loss of accuracy, and/or presentation of data in a useful format. Heat Analysis Manager (HAM) is a Thermal Desktop (TD) based free multi-purpose tool developed to aid thermal engineers in analyzing their thermal model, including a heat map generation functionality. HAM’s heat map generator retains accuracy and fast processing speed by utilizing TD’s application programming interface (API) and built-in TD’s “Qflow from Results.” Furthermore, HAM’s heat map output is presented in an easily customizable format in Excel, allowing users to create various custom visual heat maps. A full description of how HAM utilizes TD’s API to create a customizable heat map is provided. A simple model demonstration is included along with step-by-step procedures on creating custom heat maps. HAM’s heat map result has been verified against TD’s and other heat map generation software, and verification methods are also included.
Local mapping relations and global implicit function theorems
Nonlinear equation solution based on local mapping relations and global implicit function theorems for Banach space problems
Local thermodynamic mapping for effective liquid density-functional theory
The structural-mapping approximation introduced by Lutsko and Baus (1990) in the generalized effective-liquid approximation is extended to include a local thermodynamic mapping based on a spatially dependent effective density for approximating the solid phase in terms of the uniform liquid. This latter approximation, called the local generalized effective-liquid approximation (LGELA) yields excellent predictions for the free energy of hard-sphere solids and for the conditions of coexistence of a hard-sphere fcc solid with a liquid. Moreover, the predicted free energy remains single valued for calculations with more loosely packed crystalline structures, such as the diamond lattice. The spatial dependence of the weighted density makes the LGELA useful in the study of inhomogeneous solids.
Mapping the genome of meta-generalized gradient approximation density functionals: The search for B97M-V
A meta-generalized gradient approximation density functional paired with the VV10 nonlocal correlation functional is presented. The functional form is selected from more than 10{sup 10} choices carved out of a functional space of almost 10{sup 40} possibilities. Raw data come from training a vast number of candidate functional forms on a comprehensive training set of 1095 data points and testing the resulting fits on a comprehensive primary test set of 1153 data points. Functional forms are ranked based on their ability to reproduce the data in both the training and primary test sets with minimum empiricism, and filtered based on a set of physical constraints and an often-overlooked condition of satisfactory numerical precision with medium-sized integration grids. The resulting optimal functional form has 4 linear exchange parameters, 4 linear same-spin correlation parameters, and 4 linear opposite-spin correlation parameters, for a total of 12 fitted parameters. The final density functional, B97M-V, is further assessed on a secondary test set of 212 data points, applied to several large systems including the coronene dimer and water clusters, tested for the accurate prediction of intramolecular and intermolecular geometries, verified to have a readily attainable basis set limit, and checked for grid sensitivity. Compared to existing density functionals, B97M-V is remarkably accurate for non-bonded interactions and very satisfactory for thermochemical quantities such as atomization energies, but inherits the demonstrable limitations of existing local density functionals for barrier heights.
Self-Organizing Maps and Parton Distribution Functions
We present a new method to extract parton distribution functions from high energy experimental data based on a specific type of neural networks, the Self-Organizing Maps. We illustrate the features of our new procedure that are particularly useful for an anaysis directed at extracting generalized parton distributions from data. We show quantitative results of our initial analysis of the parton distribution functions from inclusive deep inelastic scattering.
Boundary regularity of Nevanlinna domains and univalent functions in model subspaces
In the paper we study boundary regularity of Nevanlinna domains, which have appeared in problems of uniform approximation by polyanalytic polynomials. A new method for constructing Nevanlinna domains with essentially irregular nonanalytic boundaries is suggested; this method is based on finding appropriate univalent functions in model subspaces, that is, in subspaces of the form K{sub {Theta}=}H{sup 2} ominus {Theta}H{sup 2}, where {Theta} is an inner function. To describe the irregularity of the boundaries of the domains obtained, recent results by Dolzhenko about boundary regularity of conformal mappings are used. Bibliography: 18 titles.
The Mercury Resistance Operon: From an Origin in a Geothermal Environment to an Efficient Detoxification Machine
Mercuric mercury (Hg[II]) is a highly toxic and mobile element that is likely to have had a pronounced and adverse effect on biology since Earth’s oxygenation ~2.4 billion years ago due to its high affinity for protein sulfhydryl groups, which upon binding destabilize protein structure and decrease enzyme activity, resulting in a decreased organismal fitness. The central enzyme in the microbial mercury detoxification system is the mercuric reductase (MerA) protein, which catalyzes the reduction of Hg(II) to volatile Hg(0). In addition to MerA, mer operons encode for proteins involved in regulation, Hg binding, and organomercury degradation. Mer-mediated approaches have had broad applications in the bioremediation of mercury-contaminated environments and industrial waste streams. Here, we examine the composition of 272 individual mer operons and quantitatively map the distribution of mer-encoded functions on both taxonomic SSU rRNA gene and MerA phylogenies. The results indicate an origin and early evolution of MerA among thermophilic bacteria and an overall increase in the complexity of mer operons through evolutionary time, suggesting continual gene recruitment and evolution leading to an improved efficiency and functional potential of the Mer detoxification system. Consistent with a positive relationship between the evolutionary history and topology of MerA and SSU rRNA gene phylogenies (Mantel R = 0.81, p < 0.01), the distribution of the majority of mer functions, when mapped on these phylograms, indicates an overall tendency to inherit mer-encoded functions through vertical descent. However, individual mer functions display evidence of a variable degree of vertical inheritance, with several genes exhibiting strong evidence for acquisition via lateral gene transfer and/or gene loss. Collectively, these data suggest that (i) mer has evolved from a simple system in geothermal environments to a widely distributed and more complex and efficient detoxification system, and (ii) merA is a suitable biomarker for examining the functional diversity of Hg detoxification and for predicting the composition of mer operons in natural environments.
Learning the boundary-to-domain mapping using Lifting Product Fourier Neural Operators for partial differential equations
Neural operators such as the Fourier Neural Operator (FNO) have been shown to provide resolution-independent deep learning models that can learn mappings between function spaces. For example, an initial condition can be mapped to the solution of a partial differential equation (PDE) at a future time-step using a neural operator. Despite the popularity of neural operators, their use to predict solution functions over a domain given only data over the boundary (such as a spatially varying Dirichlet boundary condition) remains unexplored. In this paper, we refer to such problems as boundary-to-domain problems; they have a wide range of applications in areas such as fluid mechanics, solid mechanics, heat transfer etc. We present a novel FNO-based architecture, named Lifting Product FNO (or LP-FNO) which can map arbitrary boundary functions defined on the lower-dimensional boundary to a solution in the entire domain. Specifically, two FNOs defined on the lower-dimensional boundary are lifted into the higher dimensional domain using our proposed lifting product layer. We demonstrate the efficacy and resolution independence of the proposed LP-FNO for the 2D Poisson equation.
Magnetic Field Mapping and Integral Transfer Function Matching of the Prototype Dipoles for the NSLS-II at BNL
The National Synchrotron Light Source-II (NSLS-II) storage ring at Brookhaven National Laboratory (BNL) will be equipped with 54 dipole magnets having a gap of 35 mm, and 6 dipoles having a gap of 90 mm. Each dipole has a field of 0.4 T and provides 6 degrees of bending for a 3 GeV electron beam. The large aperture magnets are necessary to allow the extraction of long-wavelength light from the dipole magnet to serve a growing number of users of low energy radiation. The dipoles must not only have good field homogeneity (0.015% over a 40 mm x 20 mm region), but the integral transfer functions and integral end harmonics of the two types of magnets must also be matched. The 35 mm aperture dipole has a novel design where the yoke ends are extended up to the outside dimension of the coil using magnetic steel nose pieces. This design increases the effective length of the dipole without increasing the physical length. These nose pieces can be tailored to adjust the integral transfer function as well as the homogeneity of the integrated field. One prototype of each dipole type has been fabricated to validate the designs and to study matching of the two dipoles. A Hall probe mapping system has been built with three Group 3 Hall probes mounted on a 2-D translation stage. The probes are arranged with one probe in the midplane of the magnet and the others vertically offset by {+-}10 mm. The field is mapped around a nominal 25 m radius beam trajectory. The results of measurements in the as-received magnets, and with modifications made to the nose pieces are presented.
Monotonicity of a relative Rényi entropy
We show that a recent definition of relative Rényi entropy is monotone under completely positive, trace preserving maps. This proves a recent conjecture of Müller-Lennert et al. [“On quantum Rényi entropies: A new definition, some properties,” J. Math. Phys. 54, 122203 (2013); e-print http://arxiv.org/abs/arXiv:1306.3142v1 ; see also e-print http://arxiv.org/abs/arXiv:1306.3142 ].