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DOE OSTI2022

Insights on sources and formation mechanisms of liquid-bearing clouds over MOSAiC examined from a Lagrangian framework

Understanding Arctic stratiform liquid-bearing cloud life cycles and properly representing these life cycles in models is crucial for evaluations of cloud feedbacks as well as the faithfulness of climate projections for this rapidly warming region. Examination of cloud life cycles typically requires analyses of cloud evolution and origins on short time scales, on the order of hours to several days. Measurements from the recent Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition provide a unique view of the current state of the central Arctic over an annual cycle. Here, we use the MOSAiC radiosonde measurements to detect liquid-bearing cloud layers over full atmospheric columns and to examine the cloud-generating air masses’ properties. We perform 5-day (120 h) back-trajectory calculations for every detected cloud and cluster them using a unique set of variables extracted from these trajectories informed by ERA5 reanalysis data. This clustering method enables us to separate between the air mass source regions such as ice-covered Arctic and midlatitude open water. We find that moisture intrusions into the central Arctic typically result in multilayer liquid-bearing cloud structures and that more than half of multilayer profiles include overlying liquid-bearing clouds originating in different types of air masses. Finally, we conclude that Arctic cloud formation via prolonged radiative cooling of elevated stable subsaturated air masses circulating over the Arctic can occur frequently (up to 20% of detected clouds in the sounding data set) and may lead to a significant impact of ensuing clouds on the surface energy budget, including net surface warming in some cases.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1989

Blue compact dwarf galaxies in the Virgo Cluster - H I and IRAS data and upper limits on proto-dwarf galaxies

Correlations between various properties of blue compact dwarf (BCD) galaxies in the Virgo Cluster were studied. It was found that, at constant mass, BCD galaxies are comparable to non-BCD irregulars in both blue luminosity and H I flux. About one-third of the BCDs were detected by IRAS at 60 or 100 microns, mostly at intensities just above the threshold sensitivity.

Hoffman, G. Lyle↗

NASA NTRS2003

Gyrophase-bunched Electrons: Cluster Observations and Simulations

The interaction of the solar wind with the Earth's bow shock is responsible for a number of phenomena both upstream and downstream. One of the least understood and studied of these is the generation of gyrophase-bunched electrons. We will describe initial work searching for and analyzing such events in (Plasma Electron And Current Experiment (PEACE) data from CLUSTER. Plasma simulations will complement the data analysis. Recent analyses suggest that gyrophase-bunched electrons are present rather frequently in the upstream region, due either to energization in the reflection off the shock front or, more likely, to phase trapping in locally produced whistler wave fields.

Gurgiolo, C.↗

NASA NTRS2013

Onboard Algorithms for Data Prioritization and Summarization of Aerial Imagery

Many current and future NASA missions are capable of collecting enormous amounts of data, of which only a small portion can be transmitted to Earth. Communications are limited due to distance, visibility constraints, and competing mission downlinks. Long missions and high-resolution, multispectral imaging devices easily produce data exceeding the available bandwidth. To address this situation computationally efficient algorithms were developed for analyzing science imagery onboard the spacecraft. These algorithms autonomously cluster the data into classes of similar imagery, enabling selective downlink of representatives of each class, and a map classifying the terrain imaged rather than the full dataset, reducing the volume of the downlinked data. A range of approaches was examined, including k-means clustering using image features based on color, texture, temporal, and spatial arrangement

Chien, Steve A.↗

DOE OSTI2017

STAR FORMATION AND SUPERCLUSTER ENVIRONMENT OF 107 NEARBY GALAXY CLUSTERS

We analyze the relationship between star formation (SF), substructure, and supercluster environment in a sample of 107 nearby galaxy clusters using data from the Sloan Digital Sky Survey. Previous works have investigated the relationships between SF and cluster substructure, and cluster substructure and supercluster environment, but definitive conclusions relating all three of these variables has remained elusive. We find an inverse relationship between cluster SF fraction ( f {sub SF}) and supercluster environment density, calculated using the Galaxy luminosity density field at a smoothing length of 8 h {sup −1} Mpc (D8). The slope of f {sub SF} versus D8 is −0.008 ± 0.002. The f {sub SF} of clusters located in low-density large-scale environments, 0.244 ± 0.011, is higher than for clusters located in high-density supercluster cores, 0.202 ± 0.014. We also divide superclusters, according to their morphology, into filament- and spider-type systems. The inverse relationship between cluster f {sub SF} and large-scale density is dominated by filament- rather than spider-type superclusters. In high-density cores of superclusters, we find a higher f {sub SF} in spider-type superclusters, 0.229 ± 0.016, than in filament-type superclusters, 0.166 ± 0.019. Using principal component analysis, we confirm these results and the direct correlation between cluster substructure and SF. These results indicate that cluster SF is affected by both the dynamical age of the cluster (younger systems exhibit higher amounts of SF); the large-scale density of the supercluster environment (high-density core regions exhibit lower amounts of SF); and supercluster morphology (spider-type superclusters exhibit higher amounts of SF at high densities).

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

Detecting Gravitational Lensing of the Cosmic Microwave Background by Galaxy Clusters

Clusters of galaxies gravitationally lens the Cosmic Microwave Background (CMB) leading to a distinct signal in the CMB on arcminute scales. Measurement of the cluster lensing effect offers the exciting possibility of constraining the masses of galaxy clusters using CMB data alone. Improved constraints on cluster masses are in turn essential to the use of clusters as cosmological probes: uncertainties in cluster masses are currently the dominant systematic affecting cluster abundance constraints on cosmology. To date, however, the CMB cluster lensing signal remains undetected because of its small magnitude and angular size. In this thesis, we develop a maximum likelihood approach to extracting the signal from CMB temperature data. We validate the technique by applying it to mock data designed to replicate as closely as possible real data from the South Pole Telescope’s (SPT) Sunyaev-Zel’dovich (SZ) survey: the effects of the SPT beam, transfer function, instrumental noise and cluster selection are incorporated. We consider the effects of foreground emission on the analysis and show that uncertainty in amount of foreground lensing results in a small systematic error on the lensing constraints. Additionally, we show that if unaccounted for, the SZ effect leads to unacceptably large biases on the lensing constraints and develop an approach for removing SZ contamination. The results of the mock analysis presented here suggest that a 4σ first detection of the cluster lensing effect can be achieved with current SPT-SZ data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Self-consistent clustering analysis: an efficient multiscale scheme for inelastic heterogeneous materials

A predictive computational theory is shown for modeling complex, hierarchical materials ranging from metal alloys to polymer nanocomposites. The theory can capture complex mechanisms such as plasticity and failure that span across multiple length scales. This general multiscale material modeling theory relies on sound principles of mathematics and mechanics, and a cutting-edge reduced order modeling method named self-consistent clustering analysis (SCA) [Zeliang Liu, M.A. Bessa, Wing Kam Liu, “Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials,” Comput. Methods Appl. Mech. Engrg. 306 (2016) 319–341]. SCA reduces by several orders of magnitude the computational cost of micromechanical and concurrent multiscale simulations, while retaining the microstructure information. This remarkable increase in efficiency is achieved with a data-driven clustering method. Computationally expensive operations are performed in the so-called offline stage, where degrees of freedom (DOFs) are agglomerated into clusters. The interaction tensor of these clusters is computed. In the online or predictive stage, the Lippmann-Schwinger integral equation is solved cluster-wise using a self-consistent scheme to ensure solution accuracy and avoid path dependence. To construct a concurrent multiscale model, this scheme is applied at each material point in a macroscale structure, replacing a conventional constitutive model with the average response computed from the microscale model using just the SCA online stage. A regularized damage theory is incorporated in the microscale that avoids the mesh and RVE size dependence that commonly plagues microscale damage calculations. The SCA method is illustrated with two cases: a carbon fiber reinforced polymer (CFRP) structure with the concurrent multiscale model and an application to fatigue prediction for additively manufactured metals. For the CFRP problem, a speed up estimated to be about 43,000 is achieved by using the SCA method, as opposed to FE2, enabling the solution of an otherwise computationally intractable problem. The second example uses a crystal plasticity constitutive law and computes the fatigue potency of extrinsic microscale features such as voids. This shows that local stress and strain are capture sufficiently well by SCA. This model has been incorporated in a process-structure-properties prediction framework for process design in additive manufacturing.

Liu, Z.↗

NASA NTRS1999

Unsupervised classification of Space Acceleration Measurement System (SAMS) data using ART2-A

The Space Acceleration Measurement System (SAMS) has been developed by NASA to monitor the microgravity acceleration environment aboard the space shuttle. The amount of data collected by a SAMS unit during a shuttle mission is in the several gigabytes range. Adaptive Resonance Theory 2-A (ART2-A), an unsupervised neural network, has been used to cluster these data and to develop cause and effect relationships among disturbances and the acceleration environment. Using input patterns formed on the basis of power spectral densities (psd), data collected from two missions, STS-050 and STS-057, have been clustered.

STS-57 Shuttle Project↗

DOE OSTI2020

Tomographic galaxy clustering with the Subaru Hyper Suprime-Cam first year public data release

We analyze the clustering of galaxies in the first public data release of the HSC Subaru Strategic Program. Despite the relatively small footprints of the observed fields, the data are an excellent proxy for the deep photometric datasets that will be acquired by LSST, and are therefore an ideal test bed for the analysis methods being implemented by the LSST DESC. We select a magnitude limited sample with i<24.5 and analyze it in four redshift bins covering 0.15≲z≲1.5. We carry out a Fourier-space analysis of the two-point clustering of this sample, including all auto- and cross-correlations. We demonstrate the use of map-level deprojection methods to account for fluctuations in the galaxy number density caused by observational systematics. Through an HOD analysis, we place constraints on the characteristic halo masses of this sample, finding a good fit up to scales k max = 1Mpc –1 , including both auto- and cross-correlations. Our results show monotonically decreasing average halo masses, which can be interpreted in terms of the drop-out of red galaxies at high redshifts for a flux-limited sample. In terms of photometric redshift systematics, we show that additional care is needed in order to marginalize over uncertainties in the redshift distribution in galaxy clustering, and that these uncertainties can be constrained by including cross-correlations. We are able to make a ~3σ detection of lensing magnification in the HSC data. Our results are stable to variations in σ 8 and Ω c and we find constraints that agree well with measurements from Planck and low-redshift probes. Lastly, we use our pipeline to study the clustering of galaxies as a function of limiting flux, and provide a simple fitting function for the linear galaxy bias for magnitude limited samples as a function of limiting magnitude and redshift.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Tomographic Galaxy Clustering with the Subaru Hyper Suprime-Cam First Year Public Data Release

We analyze the clustering of galaxies in the first public data release of the HSC Subaru Strategic Program. Despite the relatively small footprints of the observed fields, the data are an excellent proxy for the deep photometric datasets that will be acquired by LSST, and are therefore an ideal test bed for the analysis methods being implemented by the LSST DESC. We select a magnitude limited sample with $i<24.5$ and analyze it in four redshift bins covering $0.15\lesssim z \lesssim1.5$. We carry out a Fourier-space analysis of the two-point clustering of this sample, including all auto- and cross-correlations. We demonstrate the use of map-level deprojection methods to account for fluctuations in the galaxy number density caused by observational systematics. Through an HOD analysis, we place constraints on the characteristic halo masses of this sample, finding a good fit up to scales $k_{\rm max}=1\,{\rm Mpc}^{-1}$, including both auto- and cross-correlations. Our results show monotonically decreasing average halo masses, which can be interpreted in terms of the drop-out of red galaxies at high redshifts for a flux-limited sample. In terms of photometric redshift systematics, we show that additional care is needed in order to marginalize over uncertainties in the redshift distribution in galaxy clustering, and that these uncertainties can be constrained by including cross-correlations. We are able to make a $\sim3\sigma$ detection of lensing magnification in the HSC data. Our results are stable to variations in $\sigma_8$ and $\Omega_c$ and we find constraints that agree well with measurements from Planck and low-redshift probes. Finally, we use our pipeline to study the clustering of galaxies as a function of limiting flux, and provide a simple fitting function for the linear galaxy bias for magnitude limited samples as a function of limiting magnitude and redshift. [abridged]

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2014

The XXL survey. V. Detection of the Sunyaev-Zel'dovich effect of the redshift 1.9 galaxy cluster XLSSU J021744.1–034536 with CARMA

We report the detection of the Sunyaev-Zel'dovich (SZ) effect of galaxy cluster XLSSU J021744.1–034536, using 30 GHz Combined Array for Research in Millimeter-wave Astronomy (CARMA) data. This cluster was discovered via its extended X-ray emission in the XMM- Newton Large Scale Structure survey, the precursor to the XXL survey. It has a photometrically determined redshift z=1.91{sub −0.21}{sup +0.19}, making it among the most distant clusters known, and nominally the most distant for which the SZ effect has been measured. The spherically integrated Comptonization is Y {sub 500} = (3.0 ± 0.4) × 10{sup –12}, a measurement that is relatively insensitive to assumptions regarding the size and redshift of the cluster, as well as the background cosmology. Using a variety of locally calibrated cluster scaling relations extrapolated to z ∼ 2, we estimate a mass M {sub 500} ∼ (1-2) × 10{sup 14} M {sub ☉} from the X-ray flux and SZ signal. The measured properties of this cluster are in good agreement with the extrapolation of an X-ray luminosity-SZ effect scaling relation calibrated from clusters discovered by the South Pole Telescope at higher masses and lower redshifts. The full XXL-CARMA sample will provide a more complete, multi-wavelength census of distant clusters in order to robustly extend the calibration of cluster scaling relations to these high redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2010

Impact of Magnetic Draping, Convection, and Field Line Tying on Magnetopause Reconnection Under Northward IMF

We simulate a northward IMF cusp reconnection event at the magnetopause using the OpenGGCM resistive MHD code. The ACE input data, solar wind parameters, and dipole tilt belong to a 2002 reconnection event observed by IMAGE and Cluster. Based on a fully three-dimensional skeleton separators, nulls, and parallel electric fields, we show magnetic draping, convection, ionospheric field line tying play a role in producing a series of locally reconnecting nulls with flux ropes. The flux ropes in the cusp along the global separator line of symmetry. In 2D projection, the flux ropes the appearance of a tearing mode with a series of 'x's' and 'o's' but bearing a kind of 'guide field' that exists only within the magnetopause. The reconnecting field lines in the string of ropes involve IMF and both open and closed Earth magnetic field lines. The observed magnetic geometry reproduces the findings of a superposed epoch impact parameter study derived from the Cluster magnetometer data for the same event. The observed geometry has repercussions for spacecraft observations of cusp reconnection and for the imposed boundary conditions reconnection simulations.

Wendel, Deirdre E.↗

DOE OSTI2015

Using NVMe Gen3 PCIe SSD Cards in High-density Servers for High-performance Big Data Transfer Over Multiple Network Channels

This Technical Note describes how the Zettar team came up with a data transfer cluster design that convincingly proved the feasibility of using high-density servers for high-performance Big Data transfers. It then outlines the tests, operations, and observations that address a potential over-heating concern regarding the use of Non-Volatile Memory Host Controller Interface Specification (NVMHCI aka NVM Express or NVMe) Gen 3 PCIe SSD cards in high-density servers. Finally, it points out the possibility of developing a new generation of high-performance Science DMZ data transfer system for the data-intensive research community and commercial enterprises.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

TH-E-BRF-08: Subpopulations of Similarly-Responding Lesions in Metastatic Prostate Cancer

Purpose: In patients with multiple lesions, resistance to cancer treatments and subsequent disease recurrence may be due to heterogeneity of response across lesions. This study aims to identify subpopulations of similarly-responding metastatic prostate cancer lesions in bone using quantitative PET metrics. Methods: Seven metastatic prostate cancer patients treated with AR-directed therapy received pre-treatment and mid-treatment [F-18]NaF PET/CT scans. Images were registered using an articulated CT registration algorithm and transformations were applied to PET segmentations. Midtreatment response was calculated on PET-based texture features. Hierarchical agglomerative clustering was used to form groups of similarly-responding lesions, with the number of natural clusters (K) determined by the inconsistency coefficient. Lesion clustering was performed within each patient, and for the pooled population. The cophenetic coefficient (C) quantified how well the data was clustered. The Jaccard Index (JI) assessed similarity of cluster assignments from patient clustering and from population clustering. Results: 188 lesions in seven patients were identified for analysis (between 6 to 53 lesions per patient). Lesion response was defined as percent change relative to pre-treatment for 23 uncorrelated PET-based feature identifiers. . High response heterogeneity was found across all lesions (i.e. range ΔSUVmax =−95.98% to 775.00%). For intra-patient clustering, K ranged from 1–20. Population-based clustering resulted in 75 clusters, of 1-6 lesions each. Intra-patient clustering resulted in higher quality clusters than population clustering (mean C=0.95, range=0.89 to 1.00). For all patients, cluster assignments from population clustering showed good agreement to intra-patient clustering (mean JI=0.87, range=0.68 to 1.00). Conclusion: Subpopulations of similarly-responding lesions were identified in patients with multiple metastatic lesions. Good agreement was found between population- and patient-level clustering, indicating that PET-based response features may be used to quantify disease heterogeneity in advanced metastatic disease. This method for categorizing lesion response could help in identifying lesions with similar phenotypic- or genetic-based resistances to therapy. Research Supported by the Prostate Cancer Foundation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Charliecloud

Charliecloud is a set of scripts to let users run a virtual cluster of virtual machines (VMs) on a desktop or supercomputer. Key functions include: 1. Creating (typically by installing an operating system from vendor media) and updating VM images; 2. Running a single VM; 3. Running multiple VMs in a virtual cluster. The virtual machines can talk to one another over the network and (in some cases) the outside world. This is accomplished by calling external programs such as QEMU and the Virtual Distributed Ethernet (VDE) suite. The goal is to let users have a virtual cluster containing nodes where they have privileged access, while isolating that privilege within the virtual cluster so it cannot affect the physical compute resources. Host configuration enforces security; this is not included in Charliecloud, though security guidelines are included in its documentation and Charliecloud is designed to facilitate such configuration. Charliecloud manages passing information from host computers into and out of the virtual machines, such as parameters of the virtual cluster, input data specified by the user, output data from virtual compute jobs, VM console display, and network connections (e.g., SSH or X11). Parameters for the virtual cluster (number of VMs, RAM and disk per VM, etc.) are specified by the user or gathered from the environment (e.g., SLURM environment variables). Example job scripts are included. These include computation examples (such as a "hello world" MPI job) as well as performance tests. They also include a security test script to verify that the virtual cluster is appropriately sandboxed. Tests include: 1. Pinging hosts inside and outside the virtual cluster to explore connectivity; 2. Port scans (again inside and outside) to see what services are available; 3. Sniffing tests to see what traffic is visible to running VMs; 4. IP address spoofing to test network functionality in this case; 5. File access tests to make sure host access permissions are enforced. This test script is not a comprehensive scanner and does not test for specific vulnerabilities. Importantly, no information about physical hosts or network topology is included in this script (or any of Charliecloud); while part of a sensible test, such information is specified by the user when the test is run. That is, one cannot learn anything about the LANL network or computing infrastructure by examining Charliecloud code.

Priedhorsky, Reid↗

DOE OSTI2015

Charliecloud

Priedhorsky, Reid↗

DOE OSTI2021

Galaxy clustering in harmonic space from the dark energy survey year 1 data: compatibility with real-space results

ABSTRACT We perform an analysis in harmonic space of the Dark Energy Survey Year 1 Data (DES-Y1) galaxy clustering photometric data using products obtained for the real-space analysis. We test our pipeline with a suite of lognormal simulations, which are used to validate scale cuts in harmonic space as well as to provide a covariance matrix that takes into account the DES-Y1 mask. We then apply this pipeline to DES-Y1 data taking into account survey property maps derived for the real-space analysis. We compare with real-space DES-Y1 results obtained from a similar pipeline. We show that the harmonic space analysis we develop yields results that are compatible with the real-space analysis for the bias parameters. This verification paves the way to performing a harmonic space analysis for the upcoming DES-Y3 data.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Clustered BSRs: Evidence for gas hydrate-bearing turbidite complexes in folded regions, example from the Perdido Fold Belt, northern Gulf of Mexico

We detail previously undocumented but extensive gas hydrate accumulations in the mouth of Perdido Canyon in the northern Gulf of Mexico. The accumulations are located within central parts of structural domes (four-way closures) and are characterized by stacked, high-amplitude bottom simulating reflections (BSRs) that we call clustered BSRs. Seismic data from Perdido Canyon show two clustered BSRs associated with turbidite sequences within two dome folds formed from tectonic folding and salt diapir rise. The northwestern (NW) and southeastern (SE) clustered BSRs have aerial extents of ~25 km2 and 50 km2, respectively. Well log data confirm gas hydrate occurs above the NW clustered BSR, within a 225 m-thick consistently high-resistivity interval that we interpret as gas hydrate in near-vertical fractures and turbidite sands. The SE dome is only drilled at the edge of the BSR; nevertheless, the well log data indicate that a 30 m-thick gas hydrate accumulation is present. Gas chromatographic logs in both domes suggest a gradual transition from predominantly microbial gas below the BSR (500–1000 m below seafloor (mbsf)) to thermogenic gas at 1000–2000 mbsf. Based on the well log data and seismic stratigraphic analysis, we find gas hydrate is concentrated in fractures in marine mud, as well as in the pores of submarine fan turbidities, where saturations reach as high as 75%. An estimate of the total gas hydrate-bound gas volume at standard temperature and pressure is between 0.04 and 0.17 trillion cubic meters (TCM) assuming average hydrate saturation of 5-20% in a ~45 m thick turbidite sand unit above the Perdido Canyon BSR area. Measured BSR extent and gas volume estimates indicate that the NW and SE reservoirs are among the largest gas hydrate occurrences known in the Gulf of Mexico.

58 GEOSCIENCES↗