Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “distributed clustering methods”

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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Scattering Properties of Heterogeneous Mineral Particles with Absorbing Inclusions

We analyze the results of numerically exact computer modeling of scattering and absorption properties of randomly oriented poly-disperse heterogeneous particles obtained by placing microscopic absorbing grains randomly on the surfaces of much larger spherical mineral hosts or by imbedding them randomly inside the hosts. These computations are paralleled by those for heterogeneous particles obtained by fully encapsulating fractal-like absorbing clusters in the mineral hosts. All computations are performed using the superposition T-matrix method. In the case of randomly distributed inclusions, the results are compared with the outcome of Lorenz-Mie computations for an external mixture of the mineral hosts and absorbing grains. We conclude that internal aggregation can affect strongly both the integral radiometric and differential scattering characteristics of the heterogeneous particle mixtures.

minerals↗
NASA NTRS1994

X-ray clusters from a high-resolution hydrodynamic PPM simulation of the cold dark matter universe

A new three-dimensional hydrodynamic code based on the piecewise parabolic method (PPM) is utilized to compute the distribution of hot gas in the standard Cosmic Background Explorer (COBE)-normalized cold dark matter (CDM) universe. Utilizing periodic boundary conditions, a box with size 85 h(exp-1) Mpc, having cell size 0.31 h(exp-1) Mpc, is followed in a simulation with 270(exp 3)=10(exp 7.3) cells. Adopting standard parameters determined from COBE and light-element nucleosynthesis, Sigma(sub 8)=1.05, Omega(sub b)=0.06, we find the X-ray-emitting clusters, compute the luminosity function at several wavelengths, the temperature distribution, and estimated sizes, as well as the evolution of these quantities with redshift. The results, which are compared with those obtained in the preceding paper (Kang et al. 1994a), may be used in conjuction with ROSAT and other observational data sets. Overall, the results of the two computations are qualitatively very similar with regard to the trends of cluster properties, i.e., how the number density, radius, and temeprature depend on luminosity and redshift. The total luminosity from clusters is approximately a factor of 2 higher using the PPM code (as compared to the 'total variation diminishing' (TVD) code used in the previous paper) with the number of bright clusters higher by a similar factor. The primary conclusions of the prior paper, with regard to the power spectrum of the primeval density perturbations, are strengthened: the standard CDM model, normalized to the COBE microwave detection, predicts too many bright X-ray emitting clusters, by a factor probably in excess of 5. The comparison between observations and theoretical predictions for the evolution of cluster properties, luminosity functions, and size and temperature distributions should provide an important discriminator among competing scenarios for the development of structure in the universe.

Bryan, Greg L.↗
DOE OSTI2025

Cosmological Constraints from Full-Scale Clustering and Galaxy-Galaxy Lensing with DESI DR1

We present constraints on cosmic structure growth from the analysis of galaxy clustering and galaxy-galaxy lensing with galaxies from the Dark Energy Spectroscopic Instrument (DESI) Data Release 1. We analyze four samples drawn from the Bright Galaxy Survey (BGS) and the Luminous Red Galaxy (LRG) target classes. Projected galaxy clustering measurements from DESI are supplemented with lensing measurements from the Dark Energy Survey (DES), the Kilo-Degree Survey (KiDS), and the Hyper Suprime-Cam (HSC) survey around the same targets. Our method relies on a simulation-based modeling framework using the AbacusSummit simulations and a complex halo occupation distribution model that incorporates assembly bias. We analyze scales down to $0.4 \, h^{-1} \, \mathrm{Mpc}$ for clustering and $2.5 \, h^{-1} \, \mathrm{Mpc}$ for lensing, leading to stringent constraints on $S_8 = σ_8 \sqrt{Ω_\mathrm{m} / 0.3}$ and $Ω_\mathrm{m}$ when fixing other cosmological parameters to those preferred by the CMB. We find $S_8 = 0.794 \pm 0.023$ and $Ω_\mathrm{m} = 0.295 \pm 0.012$ when using lensing measurements from DES and KiDS. Similarly, for HSC, we find $S_8 = 0.793 \pm 0.017$ and $Ω_\mathrm{m} = 0.303 \pm 0.010$ when assuming the best-fit photometric redshift offset suggested by the HSC collaboration. Overall, our results are in good agreement with other results in the literature while continuing to highlight the constraining power of non-linear scales.

Lange, Johannes U. [American U.] (ORCID:0000000224↗
NASA NTRS1986

Far-infrared image restoration analysis of the protostellar cluster in S140

Image restoration techniques are applied to one-dimensional scans at 50 and 100 microns of the protostellar cluster in S140. These measurements resolve the surrounding nebula clearly, and Fourier methods are used to match the effective beam profiles at these wavelengths. This allows the radial distribution of temperature and dust column density to be derived at a diffraction limited spatial resolution of 23 arcsec (0.1 pc). Evidence for heating of the S140 molecular cloud by a nearby ionization front is established, and the dissociation of molecules inside the ionization front is spatially well correlated with the heating of the dust. The far-infrared spectral distribution of the three near-infrared sources within 10 arcsesc of the cluster center is presented.

Lester, D. F.↗
DOE OSTI2022

Automated Identification of Characteristic Droplet Size Distributions in Stratocumulus Clouds Utilizing a Data Clustering Algorithm

Abstract Droplet-level interactions in clouds are often parameterized by a modified gamma fitted to a “global” droplet size distribution. Do “local” droplet size distributions of relevance to microphysical processes look like these average distributions? This paper describes an algorithm to search and classify characteristic size distributions within a cloud. The approach combines hypothesis testing, specifically, the Kolmogorov–Smirnov (KS) test, and a widely used class of machine learning algorithms for identifying clusters of samples with similar properties: density-based spatial clustering of applications with noise (DBSCAN) is used as the specific example for illustration. The two-sample KS test does not presume any specific distribution, is parameter free, and avoids biases from binning. Importantly, the number of clusters is not an input parameter of the DBSCAN-type algorithms but is independently determined in an unsupervised fashion. As implemented, it works on an abstract space from the KS test results, and hence spatial correlation is not required for a cluster. The method is explored using data obtained from the Holographic Detector for Clouds (HOLODEC) deployed during the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. The algorithm identifies evidence of the existence of clusters of nearly identical local size distributions. It is found that cloud segments have as few as one and as many as seven characteristic size distributions. To validate the algorithm’s robustness, it is tested on a synthetic dataset and successfully identifies the predefined distributions at plausible noise levels. The algorithm is general and is expected to be useful in other applications, such as remote sensing of cloud and rain properties. Significance Statement A typical cloud can have billions of drops spread over tens or hundreds of kilometers in space. Keeping track of the sizes, positions, and interactions of all of these droplets is impractical, and, as such, information about the relative abundance of large and small drops is typically quantified with a “size distribution.” Droplets in a cloud interact locally, however, so this work is motivated by the question of whether the cloud droplet size distribution is different in different parts of a cloud. A new method, based on hypothesis testing and machine learning, determines how many different size distributions are contained in a given cloud. This is important because the size distribution describes processes such as cloud droplet growth and light transmission through clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Detection efficiency of a water condensation particle counter using electrically neutral sulfuric acid and sulfuric acid-dimethylamine clusters

Recent advances in condensation particle counters (CPCs) have improved the detection of sub-3 nm particles, increasing the accuracy of new particle formation (NPF) measurements. However, the detection efficiencies for neutrally charged, atmospherically relevant, sub-1 nm particles, which are critical for the accurate derivation of atmospheric NPF rates, are currently unknown. Here, this study presents a method to measure the detection efficiency of sulfuric acid and clusters of sulfuric acid and dimethylamine using measured CPC concentrations and modeled cluster distributions at atmospherically relevant concentrations. This study finds that water-based CPCs can measure these clusters at detection efficiencies relevant to NPF studies.

Cheng, Darren [Carnegie Mellon Univ., Pittsburgh, ↗
DOE OSTI2023

Integrated Land Suitability Assessment for Depots Siting in a Sustainable Biomass Supply Chain

A sustainable biomass supply chain would require not only an effective and fluid transportation system with a reduced carbon footprint and costs, but also good soil characteristics ensuring durable biomass feedstock presence. Unlike existing approaches that fail to account for ecological factors, this work integrates ecological as well as economic factors for developing sustainable supply chain development. For feedstock to be sustainably supplied, it necessitates adequate environmental conditions, which need to be captured in supply chain analysis. Using geospatial data and heuristics, we present an integrated framework that models biomass production suitability, capturing the economic aspect via transportation network analysis and the environmental aspect via ecological indicators. Production suitability is estimated using scores, considering both ecological factors and road transportation networks. These factors include land cover/crop rotation, slope, soil properties (productivity, soil texture, and erodibility factor) and water availability. This scoring determines the spatial distribution of depots with priority to fields scoring the highest. Two methods for depot selection are presented using graph theory and a clustering algorithm to benefit from contextualized insights from both and potentially gain a more comprehensive understanding of biomass supply chain designs. Graph theory, via the clustering coefficient, helps determine dense areas in the network and indicate the most appropriate location for a depot. Clustering algorithm, via K-means, helps form clusters and determine the depot location at the center of these clusters. An application of this innovative concept is performed on a case study in the US South Atlantic, in the Piedmont region, determining distance traveled and depot locations, with implications on supply chain design. The findings from this study show that a more decentralized depot-based supply chain design with 3depots, obtained using the graph theory method, can be more economical and environmentally friendly compared to a design obtained from the clustering algorithm method with 2 depots. In the former, the distance from fields to depots totals 801,031,476 miles, while in the latter, it adds up to 1,037,606,072 miles, which represents about 30% more distance covered for feedstock transportation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2005

Decentralized Formation Flying Control in a Multiple-Team Hierarchy

This paper presents the prototype of a system that addresses these objectives-a decentralized guidance and control system that is distributed across spacecraft using a multiple-team framework. The objective is to divide large clusters into teams of manageable size, so that the communication and computational demands driven by N decentralized units are related to the number of satellites in a team rather than the entire cluster. The system is designed to provide a high-level of autonomy, to support clusters with large numbers of satellites, to enable the number of spacecraft in the cluster to change post-launch, and to provide for on-orbit software modification. The distributed guidance and control system will be implemented in an object-oriented style using MANTA (Messaging Architecture for Networking and Threaded Applications). In this architecture, tasks may be remotely added, removed or replaced post-launch to increase mission flexibility and robustness. This built-in adaptability will allow software modifications to be made on-orbit in a robust manner. The prototype system, which is implemented in MATLAB, emulates the object-oriented and message-passing features of the MANTA software. In this paper, the multiple-team organization of the cluster is described, and the modular software architecture is presented. The relative dynamics in eccentric reference orbits is reviewed, and families of periodic, relative trajectories are identified, expressed as sets of static geometric parameters. The guidance law design is presented, and an example reconfiguration scenario is used to illustrate the distributed process of assigning geometric goals to the cluster. Next, a decentralized maneuver planning approach is presented that utilizes linear-programming methods to enact reconfiguration and coarse formation keeping maneuvers. Finally, a method for performing online collision avoidance is discussed, and an example is provided to gauge its performance.

Mueller, Joseph .↗
NASA NTRS2007

NASA Tech Briefs, December 2007

Topics include: Ka-Band TWT High-Efficiency Power Combiner for High-Rate Data Transmission; Reusable, Extensible High-Level Data-Distribution Concept; Processing Satellite Imagery To Detect Waste Tire Piles; Monitoring by Use of Clusters of Sensor-Data Vectors; Circuit and Method for Communication Over DC Power Line; Switched Band-Pass Filters for Adaptive Transceivers; Noncoherent DTTLs for Symbol Synchronization; High-Voltage Power Supply With Fast Rise and Fall Times; Waveguide Calibrator for Multi-Element Probe Calibration; Four-Way Ka-Band Power Combiner; Loss-of-Control-Inhibitor Systems for Aircraft; Improved Underwater Excitation-Emission Matrix Fluorometer; Metrology Camera System Using Two-Color Interferometry; Design and Fabrication of High-Efficiency CMOS/CCD Imagers; Foam Core Shielding for Spacecraft CHEM-Based Self-Deploying Planetary Storage Tanks Sequestration of Single-Walled Carbon Nanotubes in a Polymer PPC750 Performance Monitor Application-Program-Installer Builder Using Visual Odometry to Estimate Position and Attitude Design and Data Management System Simple, Script-Based Science Processing Archive Automated Rocket Propulsion Test Management Online Remote Sensing Interface Fusing Image Data for Calculating Position of an Object Implementation of a Point Algorithm for Real-Time Convex Optimization Handling Input and Output for COAMPS Modeling and Grid Generation of Iced Airfoils Automated Identification of Nucleotide Sequences Balloon Design Software Rocket Science 101 Interactive Educational Program Creep Forming of Carbon-Reinforced Ceramic-Matrix Composites Dog-Bone Horns for Piezoelectric Ultrasonic/Sonic Actuators Benchtop Detection of Proteins Recombinant Collagenlike Proteins Remote Sensing of Parasitic Nematodes in Plants Direct Coupling From WGM Resonator Disks to Photodetectors Using Digital Radiography To Image Liquid Nitrogen in Voids Multiple-Parameter, Low-False-Alarm Fire-Detection Systems Mosaic-Detector-Based Fluorescence Spectral Imager Plasmoid Thruster for High Specific-Impulse Propulsion Analysis Method for Quantifying Vehicle Design Goals Improved Tracking of Targets by Cameras on a Mars Rover Sample Caching Subsystem Multistage Passive Cooler for Spaceborne Instruments GVIPS Models and Software Stowable Energy-Absorbing Rocker-Bogie Suspensions

Source record↗
DOE OSTI2025

Suppressing the sample variance of DESI-like galaxy clustering with fast simulations

Ongoing and upcoming galaxy redshift surveys, such as the Dark Energy Spectroscopic Instrument (DESI) survey, will observe vast regions of sky and a wide range of redshifts. In order to model the observations and address various systematic uncertainties, N-body simulations are routinely adopted, however, the number of large simulations with sufficiently high mass resolution is usually limited by available computing time. Therefore, achieving a simulation volume with the effective statistical errors significantly smaller than those of the observations becomes prohibitively expensive. In this study, we apply the Convergence Acceleration by Regression and Pooling (CARPool) method to mitigate the sample variance of the DESI-like galaxy clustering in the AbacusSummit simulations, with the assistance of the quasi-N-body simulations FastPM. Based on the halo occupation distribution (HOD) models, we construct different FastPM galaxy catalogs, including the luminous red galaxies (LRGs), emission line galaxies (ELGs), and quasars, with their number densities and two-point clustering statistics well matched to those of AbacusSummit. We also employ the same initial conditions between AbacusSummit and FastPM to achieve high cross-correlation, as it is useful in effectively suppressing the variance. Our method of reducing noise in clustering is equivalent to performing a simulation with volume larger by a factor of 5 and 4 for LRGs and ELGs, respectively. We also mitigate the standard deviation of the LRG bispectrum with the triangular configurations k 2 = 2k 1 = 0.2 h Mpc -1 by a factor of 1.6. With smaller sample variance on galaxy clustering, we are able to constrain the baryon acoustic oscillations (BAO) scale parameters to higher precision. The CARPool method will be beneficial to better constrain the theoretical systematics of BAO, redshift space distortions (RSD) and primordial non-Gaussianity (NG).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Exploiting non-linear scales in galaxy–galaxy lensing and galaxy clustering: A forecast for the dark energy survey

ABSTRACT The combination of galaxy–galaxy lensing (GGL) and galaxy clustering is a powerful probe of low-redshift matter clustering, especially if it is extended to the non-linear regime. To this end, we use an N-body and halo occupation distribution (HOD) emulator method to model the redMaGiC sample of colour-selected passive galaxies in the Dark Energy Survey (DES), adding parameters that describe central galaxy incompleteness, galaxy assembly bias, and a scale-independent multiplicative lensing bias Alens. We use this emulator to forecast cosmological constraints attainable from the GGL surface density profile ΔΣ(rp) and the projected galaxy correlation function wp, gg(rp) in the final (Year 6) DES data set over scales $r_p=0.3\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$. For a $3{{\ \rm per\ cent}}$ prior on Alens we forecast precisions of $1.9{{\ \rm per\ cent}}$, $2.0{{\ \rm per\ cent}}$, and $1.9{{\ \rm per\ cent}}$ on Ωm, σ8, and $S_8 \equiv \sigma _8\Omega _m^{0.5}$, marginalized over all halo occupation distribution (HOD) parameters as well as Alens. Adding scales $r_p=0.3\!-\!3.0\, h^{-1} \, \mathrm{Mpc}$ improves the S8 precision by a factor of ∼1.6 relative to a large scale ($3.0\!-\!30.0\, h^{-1} \, \mathrm{Mpc}$) analysis, equivalent to increasing the survey area by a factor of ∼2.6. Sharpening the Alens prior to $1{{\ \rm per\ cent}}$ further improves the S8 precision to $1.1{{\ \rm per\ cent}}$, and it amplifies the gain from including non-linear scales. Our emulator achieves per cent-level accuracy similar to the projected DES statistical uncertainties, demonstrating the feasibility of a fully non-linear analysis. Obtaining precise parameter constraints from multiple galaxy types and from measurements that span linear and non-linear clustering offers many opportunities for internal cross-checks, which can diagnose systematics and demonstrate the robustness of cosmological results.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Phase identification using co‐association matrix ensemble clustering

Calibrating distribution system models to aid in the accuracy of simulations such as hosting capacity analysis is increasingly important in the pursuit of the goal of integrating more distributed energy resources. The recent availability of smart meter data is enabling the use of machine learning tools to automatically achieve model calibration tasks. This research focuses on applying machine learning to the phase identification task, using a co‐association matrix‐based, ensemble spectral clustering approach. The proposed method leverages voltage time series from smart meters and does not require existing or accurate phase labels. This work demonstrates the success of the proposed method on both synthetic and real data, surpassing the accuracy of other phase identification research.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Synthesis of Free-Standing Pd-Ni-P Metallic Glass Nanoparticles with Durable Medium-Range Ordered Structure for Enhanced Electrocatalytic Properties

Topologically disordered metallic glass nanoparticles (MGNPs) with highly active and tailorable surface chemistries have immense potential for functional uses. The synthesis of free-standing MGNPs is crucial and intensively pursued because their activity strongly depends on their exposed surfaces. Herein, a novel laser-evaporated inert-gas condensation method is designed and successfully developed for synthesizing free-standing MGNPs without substrates or capping agents, which is implemented via pulse laser-induced atomic vapor deposition under an inert helium atmosphere. In this way, the metallic atoms vaporized from the targets collide with helium atoms and then condense into short-range-order (SRO) clusters, which mutually assemble to form the MGNPs. Using this method, free-standing Pd 40 Ni 40 P 20 MGNPs with a spherical morphology are synthesized, which demonstrates satisfactory electrocatalytic activity and durability in oxygen reduction reactions. Moreover, local structure investigations using synchrotron pair distribution function techniques reveal the transformation of SRO cluster connection motifs of the MGNPs from face-sharing to edge-sharing modes during cyclic voltammetry cycles, which enhances the electrochemical stability by blocking crystallization. Further, this approach provides a general strategy for preparing free-standing MGNPs with high surface activities, which may have widespread functional applications

36 MATERIALS SCIENCE↗
NASA NTRS2001

Characterizing the Small Scale Structure in Clusters of Galaxies

We studied galaxy clusters Abell 119, Abell 754, and Abell 1750, using data from the ASCA and ROSAT satellites. In addition, we completed the paper "Merging Binary Clusters". In this paper we study three prominent bi-modal X-ray clusters: A3528, A1750 and A3395. Since the sub-clusters in these systems have projected separations of 0.93, 1.00 and 0.67 Mpc respectively, we examine their X-ray and optical observations to investigate the dynamics and possible merging of these sub-clusters. Using data taken with ROSAT and ASCA, we analyze the temperature and surface brightness distributions. We also analyze the velocity distributions of the three clusters using new measurements supplemented with previously published data. We examined both the overall cluster properties as well as the two sub-cluster elements in each. These results were then applied to the determination of the overall cluster masses, that demonstrate excellent consistency between the various methods used. While the characteristic parameters of the sub-clusters are typical of isolated objects, our temperature results for the regions between the two sub-clusters clearly confirm the presence of merger activity that is suggested by the surface brightness distributions. These three clusters represent a progression of equal-sized sub-cluster mergers, starting from initial contact to immediately before first core passage.

Forman, William R.↗
DOE OSTI2020

Cross-correlation of Planck CMB lensing with DESI-like LRGs

ABSTRACT Cross-correlations between the lensing of the cosmic microwave background (CMB) and other tracers of large-scale structure provide a unique way to reconstruct the growth of dark matter, break degeneracies between cosmology and galaxy physics, and test theories of modified gravity. We detect a cross-correlation between Dark Energy Spectroscopic Instrument (DESI)-like luminous red galaxies (LRGs) selected from DECam Legacy Survey imaging and CMB lensing maps reconstructed with the Planck satellite at a significance of S/N = 27.2 over scales ℓmin = 30, ℓmax = 1000. To correct for magnification bias, we determine the slope of the LRG cumulative magnitude function at the faint limit as s = 0.999 ± 0.015, and find corresponding corrections of the order of a few per cent for $C^{\kappa g}_{\ell }, C^{gg}_{\ell }$ across the scales of interest. We fit the large-scale galaxy bias at the effective redshift of the cross-correlation zeff ≈ 0.68 using two different bias evolution agnostic models: a HaloFit times linear bias model where the bias evolution is folded into the clustering-based estimation of the redshift kernel, and a Lagrangian perturbation theory model of the clustering evaluated at zeff. We also determine the error on the bias from uncertainty in the redshift distribution; within this error, the two methods show excellent agreement with each other and with DESI survey expectations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

The prediction of tropopause height from clusters of brightness temperatures and its application in the stratified regression temperature retrievals using microwave and infrared satellite measurements

A total of 1575 radiosondes and the corresponding simulated brightness temperatures were used in an effort to derive a temperature retrieval based on the clusters of brightness temperatures. The 8 simulated channels, namely, 3 MSU and 5 IR of the TIROS-N satellite are used by the GLAS temperature retrieval method. The 3 MSU and 5 IR brightness temperatures were clustered into 17 cluster groups and a regression for the prediction of the tropopause height in mb was generated. The overall r.m.s. for the tropopause prediction is excellent, namely, around 16 mb for the summer and 23 mb for the winter. The correct cluster of brightness temperatures can be identified 98% of the time by the method of discriminatory classification if it is approximately a normal distribution or, in general, by the method of the nearest neighbor.

Munteanu, M. J.↗
NASA NTRS2002

Hubble Space Telescope Imaging of the Circumnuclear Environments of the CfA Seyfert Galaxies: Nuclear Spirals and Fueling

We present archival Hubble Space Telescope (HST) images of the nuclear regions of 43 of the 46 Seyfert galaxies found in the volume limited,spectroscopically complete CfA Redshift Survey sample. Using an improved method of image contrast enhancement, we created detailed high-quality " structure maps " that allow us to study the distributions of dust, star clusters, and emission-line gas in the circumnuclear regions (100-1000 pc scales) and in the associated host galaxy. Essentially all of these Seyfert galaxies have circumnuclear dust structures with morphologies ranging from grand-design two-armed spirals to chaotic dusty disks. In most Seyfert galaxies there is a clear physical connection between the nuclear dust spirals on hundreds of parsec scales and large-scale bars and spiral arms in the host galaxies proper. These connections are particularly striking in the interacting and barred galaxies. Such structures are predicted by numerical simulations of gas flows in barred and interacting galaxies and may be related to the fueling of active galactic nuclei by matter inflow from the host galaxy disks. We see no significant differences in the circumnuclear dust morphologies of Seyfert 1s and 2s, and very few Seyfert 2 nuclei are obscured by large-scale dust structures in the host galaxies. If Sevfert 2s are obscured Sevfert Is, then the obscuration must occur on smaller scales than those probed by HST.

Pogge, Richard W.↗
NASA NTRS1993

An improved reconstruction method for cosmological density fields

This paper proposes some improvements to existing reconstruction methods for recovering the initial linear density and velocity fields of the universe from the present large-scale density distribution. We derive the Eulerian continuity equation in the Zel'dovich approximation and show that, by applying this equation, we can trace the evolution of the gravitational potential of the universe more exactly than is possible with previous approaches based on the Zel'dovich-Bernoulli equation. The improved reconstruction method is tested using N-body simulations. When the Zel'dovich-Bernoulli equation describes the formation of filaments, then the Zel'dovich continuity equation also follows the clustering of clumps inside the filaments. Our reconstruction method recovers the true initial gravitational potential with an rms error about 3 times smaller than previous methods. We examine the recovery of the initial distribution of Fourier components and find the scale at which the recovered phases are scrambled with respect their true initial values. Integrating the Zel'dovich continuity equation back in time, we can improve the spatial resolution of the reconstruction by a factor of about 2.

Gramann, Mirt↗