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.

SourceResearch connectionFrom yearThrough year

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

At least 739 records · Page 41

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Correlated mechanochemical maps of Arabidopsis thaliana primary cell walls using atomic force microscope infrared spectroscopy

Spatial heterogeneity in composition and organisation of the primary cell wall affects the mechanics of cellular morphogenesis. However, directly correlating cell wall composition, organisation and mechanics has been challenging. To overcome this barrier, we applied atomic force microscopy coupled with infrared (AFM-IR) spectroscopy to generate spatially correlated maps of chemical and mechanical properties for paraformaldehyde-fixed, intact Arabidopsis thaliana epidermal cell walls. AFM-IR spectra were deconvoluted by non-negative matrix factorisation (NMF) into a linear combination of IR spectral factors representing sets of chemical groups comprising different cell wall components. This approach enables quantification of chemical composition from IR spectral signatures and visualisation of chemical heterogeneity at nanometer resolution. Cross-correlation analysis of the spatial distribution of NMFs and mechanical properties suggests that the carbohydrate composition of cell wall junctions correlates with increased local stiffness. Together, our work establishes new methodology to use AFM-IR for the mechanochemical analysis of intact plant primary cell walls.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

Digital Speckle Photography of Subpixel Displacements of Speckle Structures Based on Analysis of Their Spatial Spectra

We have investigated the capabilities of the method of digital speckle interferometry for determining subpixel displacements of a speckle structure formed by a displaceable or deformable object with a scattering surface. An analysis of spatial spectra of speckle structures makes it possible to perform measurements with a subpixel accuracy and to extend the lower boundary of the range of measurements of displacements of speckle structures to the range of subpixel values. The method is realized on the basis of digital recording of the images of undisplaced and displaced speckle structures, their spatial frequency analysis using numerically specified constant phase shifts, and correlation analysis of spatial spectra of speckle structures. Transformation into the frequency range makes it possible to obtain quantities to be measured with a subpixel accuracy from the shift of the interference-pattern minimum in the diffraction halo by introducing an additional phase shift into the complex spatial spectrum of the speckle structure or from the slope of the linear plot of the function of accumulated phase difference in the field of the complex spatial spectrum of the displaced speckle structure. The capabilities of the method have been investigated in natural experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRS2017

TPSAS-NF1676L-26925-DND

Observationally-based atmospheric energy balance is analyzed using Clouds and the Earth's Radiant Energy System (CERES)-derived TOA and surface irradiance, Global Precipitation Climatology Project (GPCP)-derived precipitation, dry static and kinetic energy tendency and divergence estimated from ERA-Interim, and surface sensible heat flux from SeaFlux. The residual tends to be negative over tropics and positive over mid-latitudes. A negative residual implies that precipitation rate is too small, divergence is too large, or radiative cooling is too large. The residual of atmospheric energy is spatially and temporally correlated with cloud objects to identify cloud types associated with the residual. Spatially, shallow cumulus, cirrostratus, and deep convective cloud object occurrence are positively correlated with the absolute value of the residual. The temporal correlation coefficient between the number of deep convective cloud objects and individual energy components, net atmospheric irradiance, precipitation rate, and the sum of dry static and kinetic energy divergence and their tendency over western Pacific are, respectively, 0.84, 0.95, and 0.93. However, when all energy components are added, the atmospheric energy residual over tropical Pacific temporally correlates well with the number of shallow cumulus cloud objects over tropical Pacific. Because shallow cumulus does not alter enough atmospheric energy compared to the residual, these suggest 1) if retrieval errors associated with deep convective clouds are causing the column integrated atmospheric energy residual, the errors vary among individual deep convective clouds, 2) it is possible that the residual is associated with processes in which shallow cumulus clouds affect deep convective clouds and hence atmospheric energy budget over tropical western Pacific, and 3) it is also possible that cumulus congestus present cirrostratus that missed in massive sensor retrieval contribute the residual. Cloud objects used in the study that leads to the above conclusions are derived from Moderate Resolution Imaging Spectroradiometer (MODIS). In this investigation, we use Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat data to evaluate and verify above findings. Specifically, we focus on 3) above and analyze frequency of occurrence of cumulus congestus present under cirrostratus and correlation to the energy balance residual.

Seiji Kato↗

DOE OSTI2016

Investigation of the Residual in Column-Integrated Atmospheric Energy Balance Using Cloud Objects

Observationally based atmospheric energy balance is analyzed using Clouds and the Earth’s Radiant Energy System (CERES)-derived TOA and surface irradiance, Global Precipitation Climatology Project (GPCP)-derived precipitation, dry static and kinetic energy tendency and divergence estimated from ERA-Interim, and surface sensible heat flux from SeaFlux. The residual tends to be negative over the tropics and positive over midlatitudes. A negative residual implies that the precipitation rate is too small, divergence is too large, or radiative cooling is too large. The residual of atmospheric energy is spatially and temporally correlated with cloud objects to identify cloud types associated with the residual. Spatially, shallow cumulus, cirrostratus, and deep convective cloud-object occurrence are positively correlated with the absolute value of the residual. The temporal correlation coefficient between the number of deep convective cloud objects and individual energy components, net atmospheric irradiance, precipitation rate, and the sum of dry static and kinetic energy divergence and their tendency over the western Pacific are 0.84, 0.95, and 0.93, respectively. However, when all energy components are added, the atmospheric energy residual over the tropical Pacific is temporally correlated well with the number of shallow cumulus cloud objects over tropical Pacific. Because shallow cumulus alters not enough atmospheric energy compared to the residual, this suggests the following: 1) if retrieval errors associated with deep convective clouds are causing the column-integrated atmospheric energy residual, the errors vary among individual deep convective clouds, and 2) it is possible that the residual is associated with processes in which shallow cumulus clouds affect deep convective clouds and hence atmospheric energy budget over the tropical western Pacific.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Modeling the effects of molecular disorder on the properties of Frenkel excitons in organic molecular semiconductors

The Frenkel exciton model offers a convenient framework for simulating electronic excitations in organic conjugated systems that are too large to address with atomistic level electronic structure methods. Parameterization of this model is typically based on analytical expressions that incompletely describe the spatial and temporal correlations that are inherent to many condensed phase molecular systems. In this manuscript, we introduce a general procedure for including these correlations in the Frenkel exciton model, by mapping them directly from all-atom molecular configurations, for instance from classical molecular dynamics. Regardless of system morphology, this mapping automatically captures the spatial and temporal molecular correlations that are otherwise difficult or impossible to represent in terms of low-dimensional correlation functions. We apply this procedure to study the excited state properties of condensed phase materials made up of thiophene oligomers. We demonstrate that Frenkel model parameters can be mapped from a series of single molecule electronic structure calculations, and that for these materials efficient semi-empirical methods are sufficient to accurately reproduce experimental spectral measurements. By analyzing the statistics of model parameters derived from materials with different characteristic morphologies, we highlight failures in some assumptions that are commonly applied when generating model parameters. Finally, by simulating exciton dynamics on a mapped Frenekel exciton model, we demonstrate the ability to quantify the effect of material morphology on the dynamic properties of excitons.

74 ATOMIC AND MOLECULAR PHYSICS↗

NASA NTRS2017

Continuation of Long-Term Global SO2 Pollution Monitoring from OMI to OMPS

Over the past 20 years, advances in satellite remote sensing of pollution-relevant species have made space-borne observations an increasingly important part of atmospheric chemistry research and air quality management. This progress has been facilitated by advanced UV-vis spectrometers, such as the Ozone Monitoring Instrument (OMI) on board the NASA Earth Observing System (EOS) Aura satellite, and continues with new instruments, such as the Ozone Mapping and Profiler Suite (OMPS) on board the NASA-NOAA Suomi National Polar-orbiting Partnership (SNPP) satellite. In this study, we demonstrate that it is possible, using our state-of-the-art principal component analysis (PCA) retrieval technique, to continue the long-term global SO2 pollution monitoring started by OMI with the current and future OMPS instruments that will fly on the NOAA Joint Polar Satellite System (JPSS) 1, 2, 3, and 4 satellites in addition to SNPP, with a very good consistency of retrievals from these instruments. Since OMI SO2 data have been primarily used for (1) providing regional context on air pollution and long-range transport on a daily basis and (2) providing information on point emission sources on an annual basis after data averaging, we focused on these two aspects in our OMI-OMPS comparisons. Four years of retrievals (2012-2015) have been compared for three regions: eastern China, Mexico, and South Africa. In general, the comparisons show relatively high correlations (r = 0. 79-0.96) of daily regional averaged SO2 mass between the two instruments and near-unity regression slopes (0.76-0.97). The annual averaged SO2 loading differences between OMI and OMPS are small (< 0.03 Dobson unit (DU) over South Africa and up to 0.1 DU over eastern China). We also found a very good correlation (r = 0. 92-0.97) in the spatial distribution of annual averaged SO2 between OMI and OMPS over the three regions during 2012-2015. The emissions from ∼ 400 SO2 sources calculated with the two instruments also show a very good correlation (r = ∼ 0.9) in each year during 2012-2015. OMPS-detected SO2 point source emissions are slightly lower than those from OMI, but OMI-OMPS differences decrease with increasing strength of source. The OMI-OMPS SO2 mass differences on a pixel by pixel (daily) basis in each region can show substantial differences. The two instruments have a spatial correlation coefficient of 0.7 or better on < ∼ 50 % of the days. It is worth noting that consistent SO2 retrievals were achieved without any explicit adjustments to OMI or OMPS radiance data and that the retrieval agreement may be further improved by introducing a more comprehensive Jacobian lookup table than is currently used.

satellite remote sensing of pollution↗

NASA NTRS2013

Cross-correlating Cosmic IR and X-ray Background Fluctuations: Evidence of Significant Black Hole Populations Among the CIB Sources

In order to understand the nature of the sources producing the recently uncovered cosmic infrared background (CIB) fluctuations, we study cross-correlations between the fluctuations in the source-subtracted CIB from Spitzer/IRAC data and the unresolved cosmic X-ray background from deep Chandra observations. Our study uses data from the EGS/AEGIS field, where both data sets cover an approx = 8' x 45' region of the sky. Our measurement is the cross-power spectrum between the IR and X-ray data. The cross-power signal between the IRAC maps at 3.6 micron and 4.5 micron and the Chandra [0.5-2] keV data has been detected, at angular scales approx >20'', with an overall significance of approx = 3.8 sigma and approx. = 5.6 sigma, respectively. At the same time we find no evidence of significant cross-correlations at the harder Chandra bands. The cross-correlation signal is produced by individual IR sources with 3.6 micron and 4.5 micron magnitudes m(sub AB) approx. > 25-26 and [0.5-2] keV X-ray fluxes << 7 × 10(exp -177 erg sq. cm/ s. We determine that at least 15%-25% of the large scale power of the CIB fluctuations is correlated with the spatial power spectrum of the X-ray fluctuations. If this correlation is attributed to emission from accretion processes at both IR and X-ray wavelengths, this implies a much higher fraction of accreting black holes than among the known populations. We discuss the various possible origins for the cross-power signal and show that neither local foregrounds nor the known remaining normal galaxies and active galactic nuclei can reproduce the measurements. These observational results are an important new constraint on theoretical modeling of the near-IR CIB fluctuations. local foregrounds, nor the known remaining normal galaxies and active galactic nuclei (AGN) can reproduce the measurements. These observational results are an important new constraint on theoretical modeling of the near-IR CIB fluctuations

Cosmic X-ray Background (CXB)↗

DOE OSTI2017

Cluster Mass Calibration at High Redshift: HST Weak Lensing Analysis of 13 Distant Galaxy Clusters from the South Pole Telescope Sunyaev-Zel’dovich Survey

We present an HST/Advanced Camera for Surveys (ACS) weak gravitational lensing analysis of 13 massive high-redshift (z(median) = 0.88) galaxy clusters discovered in the South Pole Telescope (SPT) Sunyaev-Zel'dovich Survey. This study is part of a larger campaign that aims to robustly calibrate mass-observable scaling relations over a wide range in redshift to enable improved cosmological constraints from the SPT cluster sample. We introduce new strategies to ensure that systematics in the lensing analysis do not degrade constraints on cluster scaling relations significantly. First, we efficiently remove cluster members from the source sample by selecting very blue galaxies in V - I colour. Our estimate of the source redshift distribution is based on Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) data, where we carefully mimic the source selection criteria of the cluster fields. We apply a statistical correction for systematic photometric redshift errors as derived from Hubble Ultra Deep Field data and verified through spatial cross-correlations. We account for the impact of lensing magnification on the source redshift distribution, finding that this is particularly relevant for shallower surveys. Finally, we account for biases in the mass modelling caused by miscentring and uncertainties in the concentration-mass relation using simulations. In combination with temperature estimates from Chandra we constrain the normalization of the mass-temperature scaling relation ln (E(z) M-500c/10(14)M(circle dot)) = A + 1.5ln (kT/7.2 keV) to A = 1.81(-0.14)(+0.24)(stat.)+/- 0.09(sys.), consistent with self-similar redshift evolution when compared to lower redshift samples. Additionally, the lensing data constrain the average concentration of the clusters to c(200c) = 5.6(-1.8)(+3.7).

cosmology: observations↗

DOE OSTI2025

Spatial proteomics reveals signal sequence characteristics correlated with localization in cyanobacteria

Abstract Cyanobacteria have an inner and outer cell membrane enclosing the periplasm and cell wall and an additional set of internal membranes (called the thylakoid membranes) enclosing the thylakoid lumen. The periplasm and thylakoid lumen have unique proteomes, but the mechanisms regulating protein sorting to these locations have remained elusive. Here, proximity-based proteomics using the engineered peroxidase APEX2 was performed in the cyanobacteria Synechococcus sp. PCC 7002 to profile the proteomes of the cytoplasm, thylakoid lumen, and the periplasm and outer membrane (P-OM). Our analyses revealed specific roles for the thylakoid lumen in photosynthesis and energy generation, as well as roles for the periplasm in metabolite transport and binding, cell motility, and cell wall maintenance. Forty proteins localized to both the thylakoid lumen and the P-OM; however, their biological functions remain unclear. We also analyzed the correlation between signal sequence characteristics and differential protein localization to either the thylakoid lumen or the P-OM. In PCC 7002, as well as Synechocystis sp. PCC 6803 and Nostoc sp. PCC 7120, thylakoid lumen proteins translocated across membranes via the Secretory (Sec) system possessed more hydrophobic and alpha-helical signal sequence H-regions than P-OM proteins. The signal sequences of homologous proteins in Gloeobacter violaceus PCC 7421, a cyanobacterial species with a combined thylakoid lumen and periplasmic space, did not exhibit such differences. Therefore, the pattern of increased H-region hydrophobicity and alpha helix content is specific to cyanobacteria with a separate thylakoid lumen space and likely contributes to proper protein sorting between the thylakoid lumen and periplasm.

Plant Sciences↗

NASA NTRS1989

Liquid-Crystal Optical Correlator

Optical correlator uses commercially-available liquid-crystal television (LCTV) screen as spatial light modulator. Correlations with this device done at video frame rates, making such operations as bar-code recognition possible at reasonable cost. With further development, such correlator useful in automation, robotic vision, and optical image processing.

Liu, Hua-Kuang↗

NASA NTRS1987

An optical processor for object recognition and tracking

The design and development of a miniaturized optical processor that performs real time image correlation are described. The optical correlator utilizes the Vander Lugt matched spatial filter technique. The correlation output, a focused beam of light, is imaged onto a CMOS photodetector array. In addition to performing target recognition, the device also tracks the target. The hardware, composed of optical and electro-optical components, occupies only 590 cu cm of volume. A complete correlator system would also include an input imaging lens. This optical processing system is compact, rugged, requires only 3.5 watts of operating power, and weighs less than 3 kg. It represents a major achievement in miniaturizing optical processors. When considered as a special-purpose processing unit, it is an attractive alternative to conventional digital image recognition processing. It is conceivable that the combined technology of both optical and ditital processing could result in a very advanced robot vision system.

Sloan, J.↗

DOE OSTI2019

Limited evidence for spatial resource partitioning across temperate grassland biodiversity experiments

Locally, plant species richness supports many ecosystem functions. Yet, the mechanisms driving these often-positive biodiversity–ecosystem functioning relationships are not well understood. Spatial resource partitioning across vertical resource gradients is one of the main hypothesized causes for enhanced ecosystem functioning in more biodiverse grasslands. Spatial resource partitioning occurs if species differ in where they acquire resources and can happen both above- and belowground. However, studies investigating spatial resource partitioning in grasslands provide inconsistent evidence. We present the results of a meta-analysis of 21 data sets from experimental species-richness gradients in grasslands. We test the hypothesis that increasing spatial resource partitioning along vertical resource gradients enhances ecosystem functioning in diverse grassland plant communities above- and belowground. To test this hypothesis, we asked three questions. (1) Does species richness enhance biomass production or community resource uptake across sites? (2) Is there evidence of spatial resource partitioning as indicated by resource tracer uptake and biomass allocation above- and belowground? (3) Is evidence of spatial resource partitioning correlated with increased biomass production or community resource uptake? Although plant species richness enhanced community nitrogen and potassium uptake and biomass production above- and belowground, we found that plant communities did not meet our criteria for spatial resource partitioning, though they did invest in significantly more aboveground biomass in higher canopy layers in mixture relative to monoculture. Furthermore, the extent of spatial resource partitioning across studies was not positively correlated with either biomass production or community resource uptake. Our results suggest that spatial resource partitioning across vertical resource gradients alone does not offer a general explanation for enhanced ecosystem functioning in more diverse temperate grasslands.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

MAGIC: M arching Cubes Isosurface Uncertainty Visualization for G auss i an Uncertain Data With Spatial C orrelation

Here, in this paper, we study the propagation of data uncertainty through the marching cubes algorithm for isosurface visualization for correlated uncertain data. Consideration of correlation has been shown paramount for avoiding errors in uncertainty quantification and visualization in multiple prior studies. Although the problem of isosurface uncertainty with spatial data correlation has been previously addressed, there are two major limitations to prior treatments. First, there are no analytical formulations for uncertainty quantification of isosurfaces when the data uncertainty is characterized by a Gaussian distribution with spatial correlation. Second, as a consequence of the lack of analytical formulations,existing techniques resort to a Monte Carlo sampling approach, which is expensive and difficult to integrate into visualization tools. To address these limitations, we present a closed-form framework to efficiently derive uncertainty in marching cubes level-sets for Gaussian uncertain data with spatial correlation (MAGIC). To derive closed-form solutions, we leverage the Hinkley's derivation on the ratio of Gaussian distributions. With our analytical framework, we achieve a significant speed-up and enhanced accuracy of uncertainty quantification over classical Monte Carlo methods. We further accelerate our analytical solutions using many-core processors to achieve speed-ups up to 585× and integrability with production visualization tools for broader impact. We demonstrate the effectiveness of our correlation-aware uncertainty framework through experiments on meteorology, urban flow, and astrophysics simulation datasets.

Gaussian↗

DOE OSTI2020

Investigating the linkage between simulated precipitation climatology and ENSO-related precipitation anomaly based on multi-model and perturbed parameter ensembles

It remains a challenge for climate models to correctly capture the relationship between precipitation and ENSO. This studyexamines the linkage between the simulated precipitation climatology and ENSO-related precipitation anomaly during borealwinter based on the multi-model ensemble from the Atmospheric Model Intercomparison Project Phase 5 (AMIP5) and perturbedparameter ensemble (PPE) with the Beijing Climate Center (BCC) atmospheric model. The AMIP5 models have large biases insimulating the tropical precipitation anomaly during El Niño, such as the shifts of the Inter-Tropical Convergence Zone (ITCZ)and South Pacific Convergence Zone (SPCZ). The inter-model differences show that the precipitation change in response to seasurface temperature (SST) change increases with enhanced precipitation climatology. The ENSO-related precipitation anomalycan also be related to the spatial distribution of the mean-state precipitation. The simulated ITCZ/SPCZ displacements aresignificantly correlated with the spatial precipitation-SST relationship in the mean state. Models with stronger mean-stateprecipitation-SST relationship also produce stronger SPCZ/ITCZ displacements. The mean-state tropical precipitation also hasstrong impacts on the ENSO-related precipitation anomalies over East Asia. In the BCC PPE, the connection between the mean-state precipitation and ENSO-related precipitation anomaly is overall consistent with that in AMIP5. Parameters associated withthe low-cloud and deep convection processes are the most influential ones for the precipitation simulations in BCC. Comparedwith the version in AMIP5, the new BCC model can better simulate the precipitation climatology and the relationship betweenENSO and precipitation over southern China. These results have important implications for model development and model-basedclimate predictions.

Yang, Ben↗

NASA NTRS1987

Synthetic estimation filters for a control system

Hybrid optical correlators, which use spatial light modulators and solid state imagers to interface computers and optical Fourier correlators, will allow the rapid changing of filters and digital pre- or post-correlation processing in vision systems. However, optical correlation (particulary with phase-only filtration) is notoriously sensitive to mismatches of rotation and magnification between the reference image and the input image. Such sharpness is not always desirable if the correlation pattern is to be used in a control system. Two methods of conforming the response of an inherently sharp-response optical correlation to an in plane rotation between reference and object images are discussed. The objective is to condition the correlation for better suitability to a vision-controlled system. The first method is controlled convolutional blurring of a reference image followed by construction of a matched filter (perhaps implemented as a phase-only filter). An alternative is discussed in more detail: it is a synthesis from sharp filters, so weighted as to produce a specified off-center behavior.

Juday, Richard D.↗

NASA NTRS2007

Mapped Landmark Algorithm for Precision Landing

A report discusses a computer vision algorithm for position estimation to enable precision landing during planetary descent. The Descent Image Motion Estimation System for the Mars Exploration Rovers has been used as a starting point for creating code for precision, terrain-relative navigation during planetary landing. The algorithm is designed to be general because it handles images taken at different scales and resolutions relative to the map, and can produce mapped landmark matches for any planetary terrain of sufficient texture. These matches provide a measurement of horizontal position relative to a known landing site specified on the surface map. Multiple mapped landmarks generated per image allow for automatic detection and elimination of bad matches. Attitude and position can be generated from each image; this image-based attitude measurement can be used by the onboard navigation filter to improve the attitude estimate, which will improve the position estimates. The algorithm uses normalized correlation of grayscale images, producing precise, sub-pixel images. The algorithm has been broken into two sub-algorithms: (1) FFT Map Matching (see figure), which matches a single large template by correlation in the frequency domain, and (2) Mapped Landmark Refinement, which matches many small templates by correlation in the spatial domain. Each relies on feature selection, the homography transform, and 3D image correlation. The algorithm is implemented in C++ and is rated at Technology Readiness Level (TRL) 4.

Johnson, Andrew↗

DOE OSTI2022

Tracer-field cross-correlations with k -nearest neighbour distributions

ABSTRACT In astronomy and cosmology significant effort is devoted to characterizing and understanding spatial cross-correlations between points – e.g galaxy positions, high energy neutrino arrival directions, X-ray and AGN sources, and continuous fields – e.g. weak lensing meiand Cosmic Microwave Background maps. Recently, we introduced the k-nearest neighbour (kNN) formalism to better characterize the clustering of discrete (point) data sets. Here, we extend it to the point – field cross-correlations analysis. It combines kNN measurements of the point data set with measurements of the field smoothed at many scales. The resulting statistics are sensitive to all orders in the joint clustering of the points and the field. We demonstrate that this approach, unlike the 2-pt cross-correlation, can measure the statistical dependence of two data sets even when there are no linear (Gaussian) correlations between them. We further demonstrate that this framework is far more effective than the two point function in detecting cross-correlations when the continuous field is contaminated by high levels of noise. For a particularly high level of noise, the cross-correlation between haloes and the underlying matter field in a cosmological simulation, between 10 h−1 Mpc and 30 h−1 Mpc, is detected at >5σ significance using the technique presented here, when the two-point cross-correlation significance is ∼1σ. Finally, we show that kNN cross-correlations of haloes and the matter field can be well modelled on quasi-linear scales using the Hybrid Effective Field Theory (HEFT) framework, with the same set of bias parameters as are used for 2-pt cross-correlations. The substantial improvement in the statistical power of detecting cross-correlations using this method makes it a promising tool for various cosmological applications.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1984

Research in extragalactic astrophysics

The spatial distribution of clusters of galaxies and the large scale structure of the universe is investigated. Correlations in the spatial cluster distribution are much stronger than those seen for galaxies, and over scales much larger than previously anticipated. The following main studies are completed and published; (1) The determination of the correlation functions of rich clusters of galaxies, and its dependence on richness and other parameters. Very large scale structure exists in the universe, and rich clusters participate in this structure more efficiently than galaxies. (2) A complete catalog of superclusters, is determined. The selection criteria is that of a volume density enhancement, and is done in 3 dimensions. (3) The giant galaxy void in Bootes is found to be surrouned by rich, large superclusters from the catalog described above. (4) A very large scale void of rich clusters of galaxies is found in the study of the spatial distribution of rich clusters.

Bahcall, N.↗