Search NASA⌕ Search

SEARCH · Search NASA

Results for “Spatial correlation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Correlated observations of a spatially resolved type III solar radio burst group and the associated hard X-ray emission

The first measurements of the spatial structure of a group of type III solar radio bursts associated with an impulsive hard X-ray burst are presented. At 169 MHz the radio source has been found to consist of two principal regions separated by about 300,000 km. The two regions together produced a total of four component bursts in good time correlation with spikes in the hard X-ray emission. The observations indicate that electron acceleration/injection occurs over a region which covers a wide range of magnetic field lines.

Kane, S. R.↗
DOE OSTI2023

Assessing individual movement, habitat use, and behavior of non-breeding marine birds in relation to prey availability in the US Atlantic

Resource availability is a key factor driving marine bird movements and distributions, but direct information on prey availability is difficult to obtain at relevant scales. We present novel methods for describing multi-scale trophic associations, combining movement analyses of marine birds with estimates of forage fish surface aggregations from digital aerial survey data and species occupancy from bottom trawl survey data. We analyzed satellite telemetry data from northern gannets Morus bassanus , red-throated loons Gavia stellata , and long-tailed ducks Clangula hyemalis in the US Atlantic during the non-breeding period. Using discrete-time hidden Markov models to distinguish area-restricted (i.e. putative foraging) from transit movements, we examined how environmental factors influence movement, and how forage fish species distributions and surface aggregations influence habitat use by gannets and loons that have greater dietary reliance. Our results suggest that chlorophyll a concentration significantly affected movement behavior across species, highlighting the importance of higher-productivity areas around estuaries during colder months when regional productivity is low. Though variable across species and seasons, spatial cross-correlation analysis revealed that herring species (Family Clupeidae), including Atlantic menhaden Brevoortia tyrannus , may be important resources; it also showed positive spatial correlations with forage fish aggregations. This suggests that prey patch dynamics and factors driving aggregation formation may be as important as species composition. However, spatial patterns were generally low (<0.3), suggesting a mismatch in spatiotemporal resolution, exemplifying the challenges in quantifying trophic relationships in marine systems. Disentangling predator-prey relationships is critical to understanding the mechanisms driving marine bird behavior in rapidly changing marine systems.

Environmental Sciences & Ecology↗
DOE OSTI2021

A composite likelihood approach for inference under photometric redshift uncertainty

ABSTRACT Obtaining accurately calibrated redshift distributions of photometric samples is one of the great challenges in photometric surveys like LSST, Euclid, HSC, KiDS, and DES. We present an inference methodology that combines the redshift information from the galaxy photometry with constraints from two-point functions, utilizing cross-correlations with spatially overlapping spectroscopic samples, and illustrate the approach on CosmoDC2 simulations. Our likelihood framework is designed to integrate directly into a typical large-scale structure and weak lensing analysis based on two-point functions. We discuss efficient and accurate inference techniques that allow us to scale the method to the large samples of galaxies to be expected in LSST. We consider statistical challenges like the parametrization of redshift systematics, discuss and evaluate techniques to regularize the sample redshift distributions, and investigate techniques that can help to detect and calibrate sources of systematic error using posterior predictive checks. We evaluate and forecast photometric redshift performance using data from the CosmoDC2 simulations, within which we mimic a DESI-like spectroscopic calibration sample for cross-correlations. Using a combination of spatial cross-correlations and photometry, we show that we can provide calibration of the mean of the sample redshift distribution to an accuracy of at least 0.002(1 + z), consistent with the LSST-Y1 science requirements for weak lensing and large-scale structure probes.

(cosmology:) large-scale structure of Universe↗
DOE OSTI2018

Modeling the Influence of Correlated Molecular Disorder on the Dynamics of Excitons in Organic Molecular Semiconductors

In this paper, we investigate the role of correlated molecular disorder on the dynamics of excitons in oligothiophene-based organic semiconductors. We simulate exciton dynamics using the Frenkel exciton model and derive parameters for this model so that they reflect the specific characteristics of all-atom molecular systems. By systematically modifying the parameters of the Frenkel exciton model, we isolate the influence of spatial and temporal molecular correlations on the dynamics of excitons in these systems. For the oligothiophene systems considered here, we find that the molecular fluctuations exhibit long-lived memory effects, but these effects do not significantly influence the dynamic properties of excitons. We also find that excitons can be sensitive to the molecular-scale spatial correlations, and that this sensitivity grows with the amount of energetic disorder within the material. We conclude that control over spatial correlations can mitigate the negative influence of disorder on exciton transport.

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

Prospects for Cherenkov Telescope Array Observations of the Young Supernova Remnant RX J1713.7−3946

We perform simulations for future Cherenkov Telescope Array (CTA) observations of RX J1713.7−3946, a young supernova remnant (SNR) and one of the brightest sources ever discovered in very high energy (VHE) gamma rays. Special attention is paid to exploring possible spatial (anti)correlations of gamma rays with emission at other wavelengths, in particular X-rays and CO/H i emission. We present a series of simulated images of RX J1713.7−3946 for CTA based on a set of observationally motivated models for the gamma-ray emission. In these models, VHE gamma rays produced by high-energy electrons are assumed to trace the nonthermal X-ray emission observed by XMM-Newton , whereas those originating from relativistic protons delineate the local gas distributions. The local atomic and molecular gas distributions are deduced by the NANTEN team from CO and H i observations. Our primary goal is to show how one can distinguish the emission mechanism(s) of the gamma rays (i.e., hadronic versus leptonic, or a mixture of the two) through information provided by their spatial distribution, spectra, and time variation. This work is the first attempt to quantitatively evaluate the capabilities of CTA to achieve various proposed scientific goals by observing this important cosmic particle accelerator.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

MSASGCN : Multi-Head Self-Attention Spatiotemporal Graph Convolutional Network for Traffic Flow Forecasting

Traffic flow forecasting is an essential task of an intelligent transportation system (ITS), closely related to intelligent transportation management and resource scheduling. Dynamic spatial-temporal dependencies in traffic data make traffic flow forecasting to be a challenging task. Most existing research cannot model dynamic spatial and temporal correlations to achieve well-forecasting performance. The multi-head self-attention mechanism is a valuable method to capture dynamic spatial-temporal correlations, and combining it with graph convolutional networks is a promising solution. Therefore, we propose a multi-head self-attention spatiotemporal graph convolutional network (MSASGCN) model. It can effectively capture local correlations and potential global correlations of spatial structures, can handle dynamic evolution of the road network, and, in the time dimension, can effectively capture dynamic temporal correlations. Experiments on two real datasets verify the stability of our proposed model, obtaining a better prediction performance than the baseline algorithms. The correlation metrics get significantly reduced compared with traditional time series prediction methods and deep learning methods without using graph neural networks, according to MAE and RMSE results. Compared with advanced traffic flow forecasting methods, our model also has a performance improvement and a more stable prediction performance. We also discuss some problems and challenges in traffic forecasting.

Cao, Yang↗
DOE OSTI2022

Understanding the Seismic Ground Motion Spatial Variability Using Network Analysis Community Detection

This project is to explore ground motion spatial distribution using a new approach graph-based network analysis. In this study, we combine a large-N seismic array and graph analytics to explore spatial variability and correlation at a local scale using small local and regional earthquakes. In this method, each seismic station is modeled as a node and the similarities of the waveforms that represent ground motions between two stations are modeled as edges. By analyzing this graph network using the similarity matrices and community detection algorithm, we can group the stations spatially with similar patterns. A random forest algorithm is used to reveal the important features that affect the spatial grouping. The result suggests site conditions, and how they interact with the incident seismic wavefield, strongly condition the spatial correlation of ground motion. Future progress in characterizing ground motion spatial variability will require dense wavefield measurements, either through nodal deployments, or perhaps distributed acoustic sensing measurements of seismic wavefields.

58 GEOSCIENCES↗
DOE OSTI2025

Spatial Signatures of Electron Correlation in Least-Squares Tensor Hypercontraction

Least Squares Tensor Hypercontraction (LS-THC) has received some attention in recent years as an approach to reduce the significant computational costs of wavefunc- tion based methods in quantum chemistry. However, previous work has demonstrated that the LS-THC factorization performs disproportionately worse in the description of wavefunction components (e.g. cluster amplitudes T 2 ) than Hamiltonian compo- nents (e.g. electron repulsion integrals (pq|rs)). This work develops novel theoretical methods to study the source of these errors in the context of the real-space T 2 kernel, and reports, for the first time, the existence of a “correlation feature” in the errors of the LS-THC representation of the “exchange-like” correlation energy EX and T 2 that is remarkably consistent across ten molecular species, three correlated wavefunctions, and four basis sets. This correlation feature portends the existence of a “pair-point kernel” missing in the usual LS-THC representation of the wavefunction, which critically depends upon pairs of grid points situated close to atoms and with inter-pair distances between one and two Bohr radii. These findings point the way for future LS-THC developments to address these shortcomings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1980

HOE/lensless matched spatial filter wavelength-scaling correlator

A scaling correlator optical pattern recognition system is described in which a lensless matched spatial filter (with the second Fourier transform lens and the matched spatial filter recorded on the same plate) is used with a first Fourier transform lens that is also an holographic optical element. The matched spatial filter is recorded at one wavelength and correlation is obtained at a second wavelength. Experimental demonstration and output correlation SNR data are reported, together with a comparison of the system's noise level using conventional optics and holographic elements.

Shen, M.↗
NASA NTRS1996

ROSAT observations and correlated X-ray, radio, and optical features in cluster cooling flows

Images from the Rosat high resolution imager (HRI) of the central regions of cluster cooling flows are compared to optical continuum and radio continuum images. The radio sources associated with cooling flows show two distinct morphologies. In most sources, the jets appear to be inflating distinct lobes of radio plasma. These sources show strong Faraday rotation, radio pressures in agreement with the X-ray gas pressure, and a radio X-ray spatial anti-correlation. A few cooling sources are seen to have amorphous radio morphologies, Faraday depolarization, low radio pressure and a possible radio-X-ray spatial correlation. These properties suggest that the radio jets are disrupted and that the radio plasma is mixed with the thermal X-ray plasma. Blue continuum lobes are seen in several cooling flow central galaxies. These could be due to star formation induced by the hydrodynamical effects of the radio source or due to the scattered light from beamed emission from the active galactic nucleus.

Sarazin, C. L.↗
DOE OSTI2016

Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those it is found that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely because of differences in instrumentation, calibration, and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat-dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory), and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but they poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration, or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Finally, data from models and observations should be put on the same spatial and temporal scales before comparison.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Spatial distribution of large-scale solar magnetic fields and their relation to the interplanetary magnetic field

The spatial organization of the observed photospheric magnetic field as well as its relation to the polarity of the IMF have been studied using high resolution magnetograms from the Kitt Peak National Observatory. Systematic patterns in the large scale field are due to contributions from both concentrated flux and more diffuse flux. The polarity of the photospheric field, determined on various spatial scales, correlates with the polarity of the IMF. Analyses based on several spatial scales in the photosphere suggest that new flux in the interplanetary medium is often due to relatively small photospheric features which appear in the photosphere up to one month before they are manifest at the earth.

Levine, R. H.↗
NASA NTRS1997

Image registration by parts

In spite of the large number of different image registration techniques, most of these techniques use the correlation operation to match spatial image characteristics. Correlation is known to be one of the most computationally intensive operations and its computational needs grow rapidly with the increase in the image sizes. In this article, we show that, in many cases, it might be sufficient to determine image transformations by considering only one or several parts of the image rather than the entire image, which could result in substantial computational savings. This paper introduces the concept of registration by parts and investigates its viability. It describes alternative techniques for such image registration by parts and presents early empirical results that address the underlying trade-offs.

Chalermwat, Prachya↗
NASA NTRS2018

Comparison of Magnetic Fields from a New Satellite Magnetic Model of the Lithosphere with Magnetic Fields Predicted from Crust 1.0

Both magnetic and seismic techniques can provide information about the Moho (Mohorovicic discontinuity). We develop a new technique that provides a better estimate of the magnetic thickness of the crust, as compared with previous approaches. It uses prior knowledge from seismology (Crust 1.0), a new high-degree model from CHAMP (CHAllenging Mini-satellite Payload) and Swarm (LCS-1 - a model of Earth's lithospheric field) and a newly developed technique. The technique is appropriate for regions where induced magnetization dominates over remanent magnetization. We compare the predictions from LCS-1 with those from Crust 1.0, with some simple assumptions, and find that the correlations increase until about spherical harmonic degree 30, and then decrease globally. Spatially, the correlations between the seismic and magnetic techniques are strongest over North America and Australia, and weakest over South America and northern Africa. Strong correlations also exist between the two approaches over the Antarctic, northern Europe, and Greenland. While we might expect the seismic and magnetic approaches to correlate over well-characterized regions (i.e. North America), and show weaker correlations over poorly-characterized regions (i.e. South America and north Africa), the strong correlation in the Antarctic and Greenland is puzzling, because both of these regions are poorly-characterized. We discuss some possible explanations, and implications, of this attempt to correlate seismic and magnetic approaches to characterizing the lithosphere.

Seismic↗
DOE OSTI2024

Space-time generalization of mutual information

The mutual information characterizes correlations between spatially separated regions of a system. Yet, in experiments we often measure dynamical correlations, which involve probing operators that are also separated in time. Here, we introduce a space-time generalization of mutual information which, by construction, satisfies several natural properties of the mutual information and at the same time characterizes correlations across subsystems that are separated in time. In particular, this quantity, that we call the space-time mutual information, bounds all dynamical correlations. We construct this quantity based on the idea of the quantum hypothesis testing. As a by-product, our definition provides a transparent interpretation in terms of an experimentally accessible setup. We draw connections with other notions in quantum information theory, such as quantum channel discrimination. Finally, we study the behavior of the space-time mutual information in several settings and contrast its long-time behavior in many-body localizing and thermalizing systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1987

Achromatic optical correlator for white light pattern recognition

An achromatic optical correlator using spatially multiplexed achromatic matched spatial filters (MSFs) for white light optical pattern recognition is presented. The MSF array is synthesizd using a monochromatic laser and its achromaticity is achieved by adjusting the scale and spatial carrier frequency of each MSF to accommodate the wavelength variations in white light correlation detections. Systems analysis and several experimental results showing the correlation peak intensity using white-light illumination are presented.

Chao, Tien-Hsin↗