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At least 955 records · Page 53

Lowest-energy broad 𝛼-cluster resonances in 19 F

There is strong astrophysical interest in the structure of 19 F states near the α-decay threshold, as their properties are important for understanding the development of α clustering in the 20 Ne region. The emergence of clustered states, and more generally of states that couple strongly to reaction channels near their decay thresholds, is also a topic of current interest in theoretical nuclear physics. In this work, we determine the parameters of broad low-spin states in 19 F near the α-decay threshold and present a theoretical study of these states. The analysis is restricted to ℓ = 0 and 1 resonances in the α + 15 N system close to the α threshold in 19 F. Excitation functions for 15 N(α,α) elastic scattering were measured using the Thick Target Inverse Kinematics (TTIK) method, and these new data, together with older high–energy-resolution measurements, were analyzed within the R-matrix framework. The nuclear structure of 19 F was calculated using configuration-interaction methods with a recently developed effective interaction Hamiltonian. As a result, we identify a sequence of α-cluster resonances in 19 F and map the distribution of clustering strength, which is relevant for astrophysical reaction modeling and for the theoretical understanding of many-body dynamics and the emergence of clustering in loosely bound or unstable nuclei. Furthermore, the work advances theoretical insight into the origins of clustering and highlights open questions for future theoretical and experimental studies.

19F↗

A novel cosmic filament catalogue from SDSS data

Here, in this work, we present a new catalogue of cosmic filaments obtained from the latest Sloan Digital Sky Survey (SDSS) public data. In order to detect filaments, we implement a version of the Subspace-Constrained Mean-Shift algorithm that is boosted by machine learning techniques. This allows us to detect cosmic filaments as one-dimensional maxima in the galaxy density distribution. Our filament catalogue uses the cosmological sample of SDSS, including Data Release 16, and therefore inherits its sky footprint (aside from small border effects) and redshift coverage. In particular, this means that, taking advantage of the quasar sample, our filament reconstruction covers redshifts up to z = 2.2, making it one of the deepest filament reconstructions to our knowledge. We follow a tomographic approach and slice the galaxy data in 269 shells at different redshift. The reconstruction algorithm is applied to 2D spherical maps. The catalogue provides the position and uncertainty of each detection for each redshift slice. The quality of our detections, which we assess with several metrics, show improvement with respect to previous public catalogues obtained with similar methods. We also detect a highly significant correlation between our filament catalogue and galaxy cluster catalogues built from microwave observations of the Planck Satellite and the Atacama Cosmology Telescope.

79 ASTRONOMY AND ASTROPHYSICS↗

A Step Beyond Simple Keyword Searches: Services Enabled by a Full Content Digital Journal Archive

The problems of managing and searching large archives of scientific journal articles can potentially be addressed through data mining and statistical techniques matured primarily for quantitative scientific data analysis. A journal paper could be represented by a multivariate descriptor, e.g., the occurrence counts of a number key technical terms or phrases (keywords), perhaps derived from a controlled vocabulary ( e . g . , the American Meteorological Society's Glossary of Meteorology) or bootstrapped from the journal archive itself. With this technique, conventional statistical classification tools can be leveraged to address challenges faced by both scientists and professional societies in knowledge management. For example, cluster analyses can be used to find bundles of "most-related" papers, and address the issue of journal bifurcation (when is a new journal necessary, and what topics should it encompass). Similarly, neural networks can be trained to predict the optimal journal (within a society's collection) in which a newly submitted paper should be published. Comparable techniques could enable very powerful end-user tools for journal searches, all premised on the view of a paper as a data point in a multidimensional descriptor space, e.g.: "find papers most similar to the one I am reading", "build a personalized subscription service, based on the content of the papers I am interested in, rather than preselected keywords", "find suitable reviewers, based on the content of their own published works", etc. Such services may represent the next "quantum leap" beyond the rudimentary search interfaces currently provided to end-users, as well as a compelling value-added component needed to bridge the print-to-digital-medium gap, and help stabilize professional societies' revenue stream during the print-to-digital transition.

Boccippio, Dennis J.↗

Galaxy–galaxy lensing with the DES-CMASS catalogue: measurement and constraints on the galaxy-matter cross-correlation

ABSTRACT The DMASS sample is a photometric sample from the DES Year 1 data set designed to replicate the properties of the CMASS sample from BOSS, in support of a joint analysis of DES and BOSS beyond the small overlapping area. In this paper, we present the measurement of galaxy–galaxy lensing using the DMASS sample as gravitational lenses in the DES Y1 imaging data. We test a number of potential systematics that can bias the galaxy–galaxy lensing signal, including those from shear estimation, photometric redshifts, and observing conditions. After careful systematic tests, we obtain a highly significant detection of the galaxy–galaxy lensing signal, with total S/N = 25.7. With the measured signal, we assess the feasibility of using DMASS as gravitational lenses equivalent to CMASS, by estimating the galaxy-matter cross-correlation coefficient rcc. By jointly fitting the galaxy–galaxy lensing measurement with the galaxy clustering measurement from CMASS, we obtain $r_{\rm cc}=1.09^{+0.12}_{-0.11}$ for the scale cut of $4 \, h^{-1}{\rm \,\,Mpc}$ and $r_{\rm cc}=1.06^{+0.13}_{-0.12}$ for $12 \, h^{-1}{\rm \,\,Mpc}$ in fixed cosmology. By adding the angular galaxy clustering of DMASS, we obtain rcc = 1.06 ± 0.10 for the scale cut of $4 \, h^{-1}{\rm \,\,Mpc}$ and rcc = 1.03 ± 0.11 for $12 \, h^{-1}{\rm \,\,Mpc}$. The resulting values of rcc indicate that the lensing signal of DMASS is statistically consistent with the one that would have been measured if CMASS had populated the DES region within the given statistical uncertainty. The measurement of galaxy–galaxy lensing presented in this paper will serve as part of the data vector for the forthcoming cosmology analysis in preparation.

79 ASTRONOMY AND ASTROPHYSICS↗

Automated Production of Movies on a Cluster of Computers

A method of accelerating and facilitating production of video and film motion-picture products, and software and generic designs of computer hardware to implement the method, are undergoing development. The method provides for automation of most of the tedious and repetitive tasks involved in editing and otherwise processing raw digitized imagery into final motion-picture products. The method was conceived to satisfy requirements, in industrial and scientific testing, for rapid processing of multiple streams of simultaneously captured raw video imagery into documentation in the form of edited video imagery and video derived data products for technical review and analysis. In the production of such video technical documentation, unlike in production of motion-picture products for entertainment, (1) it is often necessary to produce multiple video derived data products, (2) there are usually no second chances to repeat acquisition of raw imagery, (3) it is often desired to produce final products within minutes rather than hours, days, or months, and (4) consistency and quality, rather than aesthetics, are the primary criteria for judging the products. In the present method, the workflow has both serial and parallel aspects: processing can begin before all the raw imagery has been acquired, each video stream can be subjected to different stages of processing simultaneously on different computers that may be grouped into one or more cluster(s), and the final product may consist of multiple video streams. Results of processing on different computers are shared, so that workers can collaborate effectively.

Nail, Jasper↗

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: BAO and RSD measurements from the anisotropic power spectrum of the quasar sample between redshift 0.8 and 2.2

ABSTRACT We measure the clustering of quasars of the final data release (DR16) of eBOSS. The sample contains $343\, 708$ quasars between redshifts 0.8 ≤ z ≤ 2.2 over $4699\, \mathrm{deg}^2$. We calculate the Legendre multipoles (0,2,4) of the anisotropic power spectrum and perform a BAO and a Full-Shape (FS) analysis at the effective redshift zeff = 1.480. The errors include systematic errors that amount to 1/3 of the statistical error. The systematic errors comprise a modelling part studied using a blind N-body mock challenge and observational effects studied with approximate mocks to account for various types of redshift smearing and fibre collisions. For the BAO analysis, we measure the transverse comoving distance DM(zeff)/rdrag = 30.60 ± 0.90 and the Hubble distance DH(zeff)/rdrag = 13.34 ± 0.60. This agrees with the configuration space analysis, and the consensus yields: DM(zeff)/rdrag = 30.69 ± 0.80 and DH(zeff)/rdrag = 13.26 ± 0.55. In the FS analysis, we fit the power spectrum using a model based on Regularised Perturbation Theory, which includes redshift space distortions and the Alcock–Paczynski effect. The results are DM(zeff)/rdrag = 30.68 ± 0.90 and DH(zeff)/rdrag = 13.52 ± 0.51 and we constrain the linear growth rate of structure f(zeff)σ8(zeff) = 0.476 ± 0.047. Our results agree with the configuration space analysis. The consensus analysis of the eBOSS quasar sample yields: DM(zeff)/rdrag = 30.21 ± 0.79, DH(zeff)/rdrag = 3.23 ± 0.47, and f(zeff)σ8(zeff) = 0.462 ± 0.045 and is consistent with a flat ΛCDM cosmological model using Planck results.

Neveux, Richard↗

GPU acceleration of Swendsen–Wang dynamics

When simulating a lattice system near its critical temperature, local algorithms for modeling the system’s evolution can introduce very large autocorrelation times into sampled data. Here, this critical slowing down places restrictions on the analysis that can be completed in a timely manner of the behavior of systems around the critical point. Because it is often desirable to study such systems around this point, a new algorithm must be introduced. Therefore, we turn to cluster algorithms, such as the Swendsen–Wang algorithm and the Wolff clustering algorithm. They incorporate global updates which generate new lattice configurations with little correlation to previous states, even near the critical point. We look to accelerate the rate at which these algorithm are capable of running by implementing and benchmarking a parallel implementation of each algorithm designed to run on GPUs under NVIDIA’s CUDA framework. A 17 and 90 fold increase in the computational rate was, respectively, experienced when measured against the equivalent algorithm implemented in serial code.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A study of various methods for calculating locations of lightning events

This article reports on the results of numerical experiments on finding the location of lightning events using different numerical methods. The methods include linear least squares, nonlinear least squares, statistical estimations, cluster analysis and angular filters and combinations of such techniques. The experiments involved investigations of methods for excluding fake solutions which are solutions that appear to be reasonable but are in fact several kilometers distant from the actual location. Some of the conclusions derived from the study are that bad data produces fakes, that no fool-proof method of excluding fakes was found, that a short base-line interferometer under development at Kennedy Space Center to measure the direction cosines of an event shows promise as a filter for excluding fakes. The experiments generated a number of open questions, some of which are discussed at the end of the report.

Cannon, John R.↗

Phylogenetic diversity in the genus Bacillus as seen by 16S rRNA sequencing studies

Comparative sequence analysis of 16S ribosomal (r)RNAs or DNAs of Bacillus alvei, B. laterosporus, B. macerans, B. macquariensis, B. polymyxa and B. stearothermophilus revealed the phylogenetic diversity of the genus Bacillus. Based on the presently available data set of 16S rRNA sequences from bacilli and relatives at least four major "Bacillus clusters" can be defined: a "Bacillus subtilis cluster" including B. stearothermophilus, a "B. brevis cluster" including B. laterosporus, a "B. alvei cluster" including B. macerans, B. maquariensis and B. polymyxa and a "B. cycloheptanicus branch".

NASA Discipline Number 52-30↗

Cosmological Effects of Powerful AGN Outbursts in Galaxy Clusters: Insights from an XMM-Newton Observation of MS 0735+7421

We report on the results of an analysis o f XMM-Newton observations o f MS 0735+7421, the galaxy cluster that hosts the most energetic AGN outburst currently known. .The previous chandra image shows twin giant x-ray cavities (approx.200 kpc diameter) filled with radio emission and surrounded by a weak shock front. XMM data are consistent with these findings. The total energy in cavities and shock (1E62 erg(approx.100 kpc), to heat the gas within 1 Mpc by approx.1/4 kev per particle. The cluster exhibits an upward departure (factor approx.2) from the mean L-T relation. The boost in emissivity produced by the ICM compression in the bright shells due to the cavity expansion may contribute to explain the high luminosity and high central gas mass fraction that we measure. The scaled temperature and metallicity profiles are in general agreement with those observed in re1axed clusters. Also, the quantities we measure are consistent with the observed M-T relation. We conclude that violent outbursts such as the one in MS 0735+7421 do not cause dramatic scaling relations (other than the L-T relation). However, if they are relatively common they may play a role in creating the global cluster properties.

Gitti, M.↗

Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization

In topological data analysis and visualization, topological descriptors such as persistence diagrams, merge trees, contour trees, Reeb graphs, and Morse–Smale complexes play an essential role in capturing the shape of scalar field data. Herein we present a state–of–the–art report on scalar field comparison using topological descriptors. We provide a taxonomy of existing approaches based on visualization tasks associated with three categories of data: single fields, time–varying fields, and ensembles. These tasks include symmetry detection, periodicity detection, key event/feature detection, feature tracking, clustering, and structure statistics. Our main contributions include the formulation of a set of desirable mathematical and computational properties of comparative measures, and the classification of visualization tasks and applications that are enabled by these measures.

97 MATHEMATICS AND COMPUTING↗

Analysis of usefulness of ERTS-1 MSS data in detecting and measuring coastal marshes

The author has identified the following significant results. The usefulness of ERTS-1 data in detecting and measuring coastal marshes has been analyzed. The data chosen for study was taken over the Houston Area Test Site on August 29, 1972. A study site was selected which contained marshes of varying size. Using a computerized clustering algorithm which groups areas of spectral homogeneity, it was possible to distinguish twenty-five classes or features. To determine the total acreage of the marshes, the pure picture elements were counted. Using a technique developed by the team, the boundary picture elements were also counted. Ground truth was provided from rectified, enlarged, and scaled high altitude aircraft photography acquired during the same time frame. Comparison of the ground truth coverage depicted by the aircraft photography to the clustering acreage displayed from the ERTS-1 data showed a percentage of accuracy ranging from 89% to 99% for determining areal extent of coastal marshes.

Erb, R. B.↗

Time-dependent clustering analysis of the second BATSE gamma-ray burst catalog

A time-dependent two-point correlation-function analysis of the Burst and Transient Source Experiment (BATSE) 2B catalog finds no evidence of burst repetition. As part of this analysis, we discuss the effects of sky exposure on the observability of burst repetition and present the equation describing the signature of burst repetition in the data. For a model of all burst repetition from a source occurring in less than five days we derive upper limits on the number of bursts in the catalog from repeaters and model-dependent upper limits on the fraction of burst sources that produce multiple outbursts.

Brainerd, J. J.↗

Dark Energy Survey Year 3 results: optimized $w$CDM simulation-based inference with weak lensing map-level hybrid statistics

We present cosmological constraints from the Dark Energy Survey Year 3 (DES Y3) weak lensing data using hierarchical hybrid statistics within a Bayesian simulation-based inference framework that is based on the Gower Street simulations. To maximize the precision of the inference, we have developed a new, information-theory based, data compression of the weak lensing maps to just seven highly informative summary statistics. The hybrid scheme exploits the high information content of the power spectrum, compressing both the power spectrum and neural-based summaries that are designed to extract further information. Our simulation-based approach enables principled forward modelling of all major sources of systematic uncertainty and survey properties into realistic mock observations, including the survey mask, photometric redshift uncertainties, intrinsic galaxy alignments, multiplicative shear calibration bias, source galaxy clustering, non-Gaussian shape noise, and non-linear structure formation. The summary statistics are then used in a Bayesian simulation-based inference pipeline. The inference is validated through coverage tests and checks for robustness against baryonic feedback. Assuming a $w$CDM cosmology, our analysis yields $S_8 = 0.808 \pm 0.017$, $Ω_{\rm m} = 0.325 \pm 0.024$, and $w < -0.766$ (marginalized posterior 68 per cent credible intervals). This rigorous combination of information theory, physics- and neural network-based extreme data compression, and principled Bayesian analysis improves the figure of merit for $(Ω_{\rm m}, S_8, w)$ by 60 per cent over the previous state-of-the-art, and by almost a factor of 3 over two-point analyses of the same data. They are the most precise joint constraints on $(Ω_{\rm m}, S_8, w)$ from weak gravitational lensing data alone of any survey to date. We intend to apply this analysis to the more recent DES Y6 data.

Williamson, J. [University Coll. London]↗

Conquering Data Chaos: Research Data Management with Kubernetes

Managing massive volumes of data and effectively making it accessible to researchers poses significant challenges and is a barrier to scientific discovery. In many cases, critical data is locked up in unwieldy file formats or one-off databases and is too large to effectively process on a single machine. This talk explores the role of Kubernetes, an open-source container orchestration platform, in addressing research data management challenges. I will discuss how we are using a set of publicly available open-source and home-grown tools in the National Renewable Energy Lab (NREL) Data, Analysis, and Visualization (DAV) group to help researchers overcome data-related bottlenecks. The talk will begin by providing an overview of the data challenges faced in research data management, including data storage, processing, and analysis. I will highlight Kubernetes' ability to handle large-scale data by leveraging containerization and distributed computing, including distributed storage. Kubernetes allows researchers to encapsulate data processing infrastructure and workflows into portable containers, enabling reproducibility and ease of deployment. Kubernetes can then schedule and manage the resource allocation of these containers to enable efficient utilization of limited computing resources, leading to more efficient data processing and analysis. I will discuss some limitations of traditional, siloed approaches to dealing with data and emphasize the need for solutions which foster collaboration. I will highlight how we are using Kubernetes at NREL to facilitate data sharing and cooperation among research teams. Kubernetes' flexible architecture enables the deployment of shared computing environments, such as Apache Superset, where researchers can seamlessly access and analyze shared datasets. Providing the ability to have one research team easily consume data generated by another, utilizing Kubernetes' as a central data platform, is one of the major wins we've encountered by adopting the platform. Finally, I will showcase real-world use cases from NREL where we have used Kubernetes to solve some persistent data challenges involving large volumes of sensor and monitoring data. I will discuss the challenges we encountered when creating our cluster and making it available as a production-ready resource. I will also discuss the specific suite of tools, including Postgres and Apache Druid for columnar and timeseries data, and Redpanda Kafka for streaming data we have deployed in our infrastructure, and the process that went into the selection of these tools.

collaborative environment↗

Distilling physical origins of hardness in multi-principal element alloys directly from ensemble neural network models

Abstract Despite a plethora of data being generated on the mechanical behavior of multi-principal element alloys, a systematic assessment remains inaccessible via Edisonian approaches. We approach this challenge by considering the specific case of alloy hardness, and present a machine-learning framework that captures the essential physical features contributing to hardness and allows high-throughput exploration of multi-dimensional compositional space. The model, tested on diverse datasets, was used to explore and successfully predict hardness in Al x Ti y (CrFeNi) 1- x - y , Hf x Co y (CrFeNi) 1- x - y and Al x (TiZrHf) 1- x systems supported by data from density-functional theory predicted phase stability and ordering behavior. The experimental validation of hardness was done on TiZrHfAl x . The selected systems pose diverse challenges due to the presence of ordering and clustering pairs, as well as vacancy-stabilized novel structures. We also present a detailed model analysis that integrates local partial-dependencies with a compositional-stimulus and model-response study to derive material-specific insights from the decision-making process.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The magnetic field investigation on Cluster

The magnetic field investigation of the Cluster four-spacecraft mission is designed to provide intercalibrated measurements of the B magnetic field vector. The instrumentation and data processing of the mission are discussed. The instrumentation is identical on the four spacecraft. It consists of two triaxial fluxgate sensors and of a failure tolerant data processing unit. The combined analysis of the four spacecraft data will yield such parameters as the current density vector, wave vectors, and the geometry and structure of discontinuities.

Balogh, A.↗

Radio Occultation Investigation of the Rings of Saturn and Uranus

The proposed work addresses two main objectives: (1) to pursue the development of the random diffraction screen model for analytical/computational characterization of the extinction and near-forward scattering by ring models that include particle crowding, uniform clustering, and clustering along preferred orientations (anisotropy). The characterization is crucial for proper interpretation of past (Voyager) and future (Cassini) ring, occultation observations in terms of physical ring properties, and is needed to address outstanding puzzles in the interpretation of the Voyager radio occultation data sets; (2) to continue the development of spectral analysis techniques to identify and characterize the power scattered by all features of Saturn's rings that can be resolved in the Voyager radio occultation observations, and to use the results to constrain the maximum particle size and its abundance. Characterization of the variability of surface mass density among the main ring, features and within individual features is important for constraining the ring mass and is relevant to investigations of ring dynamics and origin. We completed the developed of the stochastic geometry (random screen) model for the interaction of electromagnetic waves with of planetary ring models; used the model to relate the oblique optical depth and the angular spectrum of the near forward scattered signal to statistical averages of the stochastic geometry of the randomly blocked area. WE developed analytical results based on the assumption of Poisson statistics for particle positions, and investigated the dependence of the oblique optical depth and angular spectrum on the fractional area blocked, vertical ring profile, and incidence angle when the volume fraction is small. Demonstrated agreement with the classical radiative transfer predictions for oblique incidence. Also developed simulation procedures to generate statistical realizations of random screens corresponding to uniformly packed ring models, and used the results to characterize dependence of the extinction and near-forward scattering on ring thickness, packing fraction, and the ring opening angle.

Marouf, Essam A.↗