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At least 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

A global analysis of cities’ geosocial temporal signatures for points of interest hours of operation

The temporal nature of humans interaction with Points of Interest (POIs) in cities can differ depending on place type and regional location. Times when many people are likely to visit restaurants (place type) in Italy, may differ from times when many people are likely to visit restaurants in Lebanon (i.e. regional differences). Geosocial data are a powerful resource to model these temporal differences in cities, as traditional methods used to study cross-cultural differences do not scale to a global level. As cities continue to grow in population and economic development, research identifying the social and geophysical (e.g., climate) factors that influence city function remains important and incomplete. Here, we take a quantitative approach, applying dynamic time warping and hierarchical clustering on temporal signatures to model geosocial temporal patterns for Retail and Restaurant Facebook POIs hours of operation for more than 100 cities in 90 countries around the world. Results show cities’ temporal patterns cluster to reflect the cultural region they represent. Furthermore, temporal patterns are influenced by a mix of social and geophysical factors. Trends in the data imply social factors influence unique drops in temporal signatures, and geophysical factors influence when daily temporal patterns start and finish.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS1998

Cross Correlation of the 2-10 keV X-Ray Background with Radio Sources: Constraining the Large Scale Structure of the X-Ray Background

We present cross-correlation analyses of the HEAO 2-10 keV diffuse X-ray map with both the combined GB6/Parkes-MIT-NRAO (GB6-PMN) 5 GHz and the FIRST 1.4 GHz radio surveys. The cross-correlation functions (CCFs) of both radio surveys with the unresolved X-ray background were detected at the 5 u level. While the large angular resolution (3 deg) of the X-ray map makes it difficult to separate the contributions of clustering from those of Poisson fluctuations, the amplitude of the CCF provides important constraints on the X-ray emissivity of the radio sources, as well as on the clustering properties of radio and X-ray sources. These constraints are subject to a number of modeling parameters, e.g., X-ray luminosity evolution, clustering evolution, the radio luminosity function, cosmological model, etc. For reasonable choices of parameters the X-ray/FIRST CCF is consistent with a correlation scale length of 6/h Mpc. This is somewhat smaller than the scale length inferred from the autocorrelation function of the FIRST survey and implies that X-ray sources are less strongly clustered than strong radio sources, a result that is consistent with previous constraints on X-ray clustering. The X-ray/GB6-PMN CCF is several times larger and is likely to be dominated by Poisson fluctuations. This implies that approx. 2% of the diffuse X-ray background arises from the GB6-PMN sources.

Boughn, Stephen P.↗
DOE OSTI2024

Topological Interpretability for Deep Learning

With the growing adoption of AI-based systems across everyday life, the need to understand their decision-making mechanisms is correspondingly increasing. The level at which we can trust the statistical inferences made from AI-based decision systems is an increasing concern, especially in high-risk systems such as criminal justice or medical diagnosis, where incorrect inferences may have tragic consequences. Despite their successes in providing solutions to problems involving real-world data, deep learning (DL) models cannot quantify the certainty of their predictions. These models are frequently quite confident, even when their solutions are incorrect. This work presents a method to infer prominent features in two DL classification models trained on clinical and non-clinical text by employing techniques from topological and geometric data analysis. We create a graph of a model's feature space and cluster the inputs into the graph's vertices by the similarity of features and prediction statistics. We then extract subgraphs demonstrating high-predictive accuracy for a given label. These subgraphs contain a wealth of information about features that the DL model has recognized as relevant to its decisions. We infer these features for a given label using a distance metric between probability measures, and demonstrate the stability of our method compared to the LIME and SHAP interpretability methods. This work establishes that we may gain insights into the decision mechanism of a DL model. This method allows us to ascertain if the model is making its decisions based on information germane to the problem or identifies extraneous patterns within the data.

Spannaus, Adam↗
DOE OSTI2019

Tests of acoustic scale shifts in halo-based mock galaxy catalogues

ABSTRACT We utilize mock catalogues from high-accuracy cosmological N-body simulations to quantify shifts in the recovery of the acoustic scale that could potentially result from galaxy clustering bias. The relationship between galaxies and dark matter haloes presents a complicated source of systematic errors in modern redshift surveys, particularly when aiming to make cosmological measurements to sub-per cent precision. Apart from a scalar, linear bias parameter accounting for the density contrast ratio between matter tracers and the true matter distribution, other types of galaxy bias, such as assembly and velocity biases, may also significantly alter clustering signals from small to large scales. We create mocks based on generalized halo occupation populations of 36 periodic boxes from the abacus cosmosrelease, and test various biased models along with an unbiased base case in a total volume of $48 \, h^{-3} \, {\rm Gpc}^{3}$. Two reconstruction methods are applied to galaxy samples and the apparent acoustic scale is derived by fitting the two-point correlation function multipoles. With respect to the baseline, we find a 0.3 per cent shift in the line-of-sight acoustic scale for one variation in the satellite galaxy population, and we find a 0.7 per cent shift for an extreme level of velocity bias of the central galaxies. All other bias models are consistent with zero shift at the 0.2 per cent level after reconstruction. We note that the bias models explored are relatively large variations, producing sizeable and likely distinguishable changes in small-scale clustering, the modelling of which would further calibrate the baryon acoustic oscillations standard ruler.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Clustering constraints on the relative sizes of central and satellite galaxies

In this work, we empirically constrain how galaxy size relates to halo virial radius using new measurements of the size- and stellar mass-dependent clustering of galaxies in the Sloan Digital Sky Survey. We find that small galaxies cluster much more strongly than large galaxies of the same stellar mass. The magnitude of this clustering difference increases on small scales, and decreases with increasing stellar mass. Using forward-modelling techniques implemented in Halotools, we test an empirical model in which present-day galaxy size is proportional to the size of the virial radius at the time the halo reached its maximum mass. This simple model reproduces the observed size dependence of galaxy clustering in striking detail. The success of this model provides strong support for the conclusion that satellite galaxies have smaller sizes relative to central galaxies of the same halo mass. Our findings indicate that satellite size is set prior to the time of infall, and that a remarkably simple, linear size–virial radius relation emerges from the complex physics regulating galaxy size. We make quantitative predictions for future measurements of galaxy–galaxy lensing, including dependence upon size, scale, and stellar mass, and provide a scaling relation of the ratio of mean sizes of satellites and central galaxies as a function of their halo mass that can be used to calibrate hydrodynamical simulations and semi-analytic models.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1997

Degradation of Perfluorinated Ether Lubricants on Pure Aluminum Surfaces: Semiempirical Quantum Chemical Modeling

The AM1 semiempirical quantum chemical method was used to model the interaction of perfluoroethers with aluminum surfaces. Perfluorodimethoxymethane and perfluorodimethyl ether were studied interacting with aluminum surfaces, which were modeled by a five-atom cluster and a nine-atom cluster. Interactions were studied for edge (high index) sites and top (low index) sites of the clusters. Both dissociative binding and nondissociative binding were found, with dissociative binding being stronger. The two different ethers bound and dissociated on the clusters in different ways: perfluorodimethoxymethane through its oxygen atoms, but perfluorodimethyl ether through its fluorine atoms. The acetal linkage of perfluorodimeth-oxymethane was the key structural feature of this molecule in its binding and dissociation on the aluminum surface models. The high-index sites of the clusters caused the dissociation of both ethers. These results are consistent with the experimental observation that perfluorinated ethers decompose in contact with sputtered aluminum surfaces.

Slaby, Scott M.↗
DOE OSTI2018

The Influence of ENSO Flavors on Western North Pacific Tropical Cyclone Activity

El Niño–Southern Oscillation (ENSO) is a major source of seasonal western North Pacific (WNP) tropical cyclone (TC) predictability. However, the spatial characteristics of ENSO have changed in recent decades, from warming more typically in the eastern equatorial Pacific during canonical or cold tongue El Niño to warming more typically in the central equatorial Pacific during noncanonical or warm pool El Niño. We investigated the response in basinwide WNP TC activity and spatial clustering of TC tracks to the location and magnitude of El Niño using observations, TC-permitting tropical channel model simulations, and a TC track clustering methodology. We found that simulated western North Pacific TC activity, including accumulated cyclone energy (ACE) and the number of typhoons and intense typhoons, is more effectively enhanced by sea surface temperature warming of the central, compared to the eastern, equatorial Pacific. El Niño also considerably influenced simulated TC tracks regionally, with a decrease in TCs that were generated near the Asian continent and an increase in clusters that were dominated by TC genesis in the southeastern WNP. This response corresponds with the spatial pattern of reduced vertical wind shear and is most effectively driven by central Pacific SST warming. Finally, internal atmospheric variability generated a substantial range in the simulated season total ACE (±25% of the median). However, extremely active WNP seasons were linked with El Niño, rather than internal atmospheric variability, in both observations and climate model simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

A Service Oriented Architecture for Exploring High Performance Distributed Power Models

Power grids are increasingly incorporating high quality, high throughput sensor devices inside power distribution networks. These devices are driving an unprecedented increase in the volume and rate of available information. The real-time requirements for handling this data are beyond the capacity of conventional power models running in central utilities. Hence, we are exploring distributed power models deployed at the regional scale. The connection of these models for a larger geographic region is supported by a distributed system architecture. This architecture is built in a service oriented style, whereby distributed power models running on high performance clusters are exposed as services. Each service is semantically annotated and therefore can be discovered through a service catalog and composed into workflows. The overall architecture has been implemented as an integrated workflow environment useful for power researchers to explore newly developed distributed power models.

Service oriented architecture, high performance co↗
DOE OSTI2025

XRISM Reveals Low Nonthermal Pressure in the Core of the Hot, Relaxed Galaxy Cluster A2029

We present XRISM Resolve observations of the core of the hot, relaxed galaxy cluster Abell 2029 (A2029). We find that the line-of-sight bulk velocity of the intracluster medium (ICM) within the central 180 kpc is at rest with respect to the brightest cluster galaxy, with a 3σ upper limit of ∣vbulk∣ < 100 km s−1. We robustly measure the field-integrated ICM velocity dispersion to be σv = 169 ± 10 km s−1, obtaining similar results for both single-temperature and two-temperature plasma models to account for the cluster cool core. This result, if ascribed to isotropic turbulence, implies a subsonic ICM with Mach number M 3D ≈ 0.22 and a nonthermal pressure fraction of 2.6 ± 0.3%. The turbulent velocity is similar to what was measured in the core of the Perseus cluster by Hitomi, but here in a more massive cluster with an ICM temperature of 7 keV, the limit on the nonthermal pressure fraction is even more stringent. Our result is consistent with expectations from simulations of relaxed clusters, but it is on the low end of the predicted distribution, indicating that A2029 is an exceptionally relaxed cluster with no significant impacts from either a recent minor merger or active galactic nucleus activity.

Audard, Marc (ORCID:000000034721034X)↗
DOE OSTI2012

Modeling Dynamic Regulatory Processes in Stroke.

The ability to examine in silico the behavior of biological systems can greatly accelerate the pace of discovery in disease pathologies, such as stroke, where in vivo experimentation is lengthy and costly. In this paper we describe an approach to in silico examination of blood genomic responses to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) relating regulators and functional clusters from the data. These ODEs were used to develop dynamic models that simulate the expression of regulated functional clusters using system dynamics as the modeling paradigm. The dynamic model has the considerable advantage of only requiring an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. The manipulation of input model parameters, such as changing the magnitude of gene expression, made it possible to assess the behavior of the networks through time under varying conditions. We report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different preconditioning paradigms.

dynamic modeling↗
DOE OSTI2012

THE SLOAN DIGITAL SKY SURVEY CO-ADD: CROSS-CORRELATION WEAK LENSING AND TOMOGRAPHY OF GALAXY CLUSTERS

The shapes of distant galaxies are sheared by intervening galaxy clusters. We examine this effect in Stripe 82, a 275 deg{sup 2} region observed multiple times in the Sloan Digital Sky Survey (SDSS) and co-added to achieve greater depth. We obtain a mass-richness calibration that is similar to other SDSS analyses, demonstrating that the co-addition process did not adversely affect the lensing signal. We also propose a new parameterization of the effect of tomography on the cluster lensing signal which does not require binning in redshift, and we show that using this parameterization we can detect tomography for stacked clusters at varying redshifts. Finally, due to the sensitivity of the tomographic detection to accurately marginalize over the effect of the cluster mass, we show that tomography at low redshift (where dependence on exact cosmological models is weak) can be used to constrain mass profiles in clusters.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2005

Solar Effects on Global Climate Due to Cosmic Rays and Solar Energetic Particles

Although the work reported here does not directly connect solar variability with global climate change, this research establishes a plausible quantitative causative link between observed solar activity and apparently correlated variations in terrestrial climate parameters. Specifically, we have demonstrated that ion-mediated nucleation of atmospheric particles is a likely, and likely widespread, phenomenon that relates solar variability to changes in the microphysical properties of clouds. To investigate this relationship, we have constructed and applied a new model describing the formation and evolution of ionic clusters under a range of atmospheric conditions throughout the lower atmosphere. The activation of large ionic clusters into cloud nuclei is predicted to be favorable in the upper troposphere and mesosphere, and possibly in the lower stratosphere. The model developed under this grant needs to be extended to include additional cluster families, and should be incorporated into microphysical models to further test the cause-and-effect linkages that may ultimately explain key aspects of the connections between solar variability and climate.

Turco, R. P.↗
DOE OSTI2012

MASS AND LUMINOSITY EVOLUTION OF YOUNG STELLAR OBJECTS

A model of protostar mass and luminosity evolution in clusters gives new estimates of cluster age, protostar birthrate, accretion rate, and mean accretion time. The model assumes constant protostar birthrate, core-clump accretion, and equally likely accretion stopping. Its parameters are set to reproduce the initial mass function and to match protostar luminosity distributions in nearby star-forming regions. It obtains cluster ages and birthrates from the observed numbers of protostars and pre-main sequence (PMS) stars, and from the modal value of the protostar luminosity. In 31 embedded clusters and complexes, the global cluster age is 1-3 Myr, matching available estimates based on optical spectroscopy (OS) and evolutionary tracks. This method of age estimation is simpler than OS and is more useful for young embedded clusters where optical spectroscopy is not possible. In the youngest clusters, the protostar fraction decreases outward from the densest gas, indicating that the local star-forming age increases outward from a few 0.1 Myr in small protostar-dominated zones to a few Myr in large PMS-dominated zones.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Synthesis of Co‐Doped MoS 2 Monolayers with Enhanced Valley Splitting

Abstract Internal magnetic moments induced by magnetic dopants in MoS 2 monolayers are shown to serve as a new means to engineer valley Zeeman splitting (VZS). Specifically, successful synthesis of monolayer MoS 2 doped with the magnetic element Co is reported, and the magnitude of the valley splitting is engineered by manipulating the dopant concentration. Valley splittings of 3.9, 5.2, and 6.15 meV at 7 T in Co‐doped MoS 2 with Co concentrations of 0.8%, 1.7%, and 2.5%, respectively, are achieved as revealed by polarization‐resolved photoluminescence (PL) spectroscopy. Atomic‐resolution electron microscopy studies clearly identify the magnetic sites of Co substitution in the MoS 2 lattice, forming two distinct types of configurations, namely isolated single dopants and tridopant clusters. Density functional theory (DFT) and model calculations reveal that the observed enhanced VZS arises from an internal magnetic field induced by the tridopant clusters, which couples to the spin, atomic orbital, and valley magnetic moment of carriers from the conduction and valence bands. The present study demonstrates a new method to control the valley pseudospin via magnetic dopants in layered semiconducting materials, paving the way toward magneto‐optical and spintronic devices.

Zhou, Jiadong↗
DOE OSTI2016

Fuzzy jets

Collimated streams of particles produced in high energy physics experiments are organized using clustering algorithms to form jets . To construct jets, the experimental collaborations based at the Large Hadron Collider (LHC) primarily use agglomerative hierarchical clustering schemes known as sequential recombination. We propose a new class of algorithms for clustering jets that use infrared and collinear safe mixture models. These new algorithms, known as fuzzy jets , are clustered using maximum likelihood techniques and can dynamically determine various properties of jets like their size. We show that the fuzzy jet size adds additional information to conventional jet tagging variables in boosted topologies. Furthermore, we study the impact of pileup and show that with some slight modifications to the algorithm, fuzzy jets can be stable up to high pileup interaction multiplicities.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Projected coupled cluster theory

Coupled cluster theory is the method of choice for weakly correlated systems. But in the strongly correlated regime, it faces a symmetry dilemma, where it either completely fails to describe the system or has to artificially break certain symmetries. On the other hand, projected Hartree-Fock theory captures the essential physics of many kinds of strong correlations via symmetry breaking and restoration. Here, we combine and try to retain the merits of these two methods by applying symmetry projection to broken symmetry coupled cluster wave functions. The non-orthogonal nature of states resulting from the application of symmetry projection operators furnishes particle-hole excitations to all orders, thus creating an obstacle for the exact evaluation of overlaps. Here we provide a solution via a disentanglement framework theory that can be approximated rigorously and systematically. Results of projected coupled cluster theory are presented for molecules and the Hubbard model, showing that spin projection significantly improves unrestricted coupled cluster theory while restoring good quantum numbers. The energy of projected coupled cluster theory reduces to the unprojected one in the thermodynamic limit, albeit at a much slower rate than projected Hartree-Fock.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Dynamic Price Vector Formation Model-Based Automatic Demand Response Strategy for PV-Assisted EV Charging Stations

A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and upper bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.

14 SOLAR ENERGY↗
NASA NTRS1985

The young SMC cluster NGC 330

A color-magnitude diagram has been obtained for the young SMC cluster NGC 330. The diagram shows a well-defined main sequence, a group of blue supergiants, a group of red supergiants between B-V = 1.2 m and 1.6 m about one magnitude fainter, and an empty Hertzsprung gap. The surrounding field is a composite of a very gold population resembling galactic globular clusters and a very young population. DDO and infrared photometry strongly suggest that the cluster is metal-poor, but a definitive measure could not be made because of calibration difficulties. The cluster's age is estimated at 12 million years, with the surrounding field about 50 percent older. The cluster will prove very useful in testing stellar evolution models for young, metal-poor stars if the cluster's metallicity can be established via high-resolution spectroscopy.

Carney, B. W.↗