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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.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Optimization of a Non-traditional Unsupervised Classification Approach for Land Cover Analysis

The conditions under which a hybrid of clustering and canonical analysis for image classification produce optimum results were analyzed. The approach involves generation of classes by clustering for input to canonical analysis. The importance of the number of clusters input and the effect of other parameters of the clustering algorithm (ISOCLS) were examined. The approach derives its final result by clustering the canonically transformed data. Therefore the importance of number of clusters requested in this final stage was also examined. The effect of these variables were studied in terms of the average separability (as measured by transformed divergence) of the final clusters, the transformation matrices resulting from different numbers of input classes, and the accuracy of the final classifications. The research was performed with LANDSAT MSS data over the Hazleton/Berwick Pennsylvania area. Final classifications were compared pixel by pixel with an existing geographic information system to provide an indication of their accuracy.

Boyd, R. K.↗
DOE OSTI2025

Optical galaxy cluster mock catalogs with realistic projection effects: Validations with the SDSS clusters

Galaxy clusters identified in optical imaging surveys suffer from projection effects: Physically unassociated galaxies along a cluster’s line of sight can be counted as its members and boost the observed richness (the number of cluster members). To model the impact of projection on cluster cosmology analyses, we apply a halo occupation distribution model to 𝑁-body simulations to simulate the red galaxies contributing to cluster members, and we use the number of galaxies in a cylinder along the line of sight (counts in cylinders) to model the impact of projection on cluster richness. We compare three projection models: uniform, quadratic, and Gaussian, and we convert between them by matching their effective cylinder volumes. We validate our mock catalogs using SDSS redMaPPer clusters’ data vectors, including counts vs richness, stacked lensing signal, spectroscopic redshift distribution of member galaxies, and richness remeasured on a redshift grid. We find the former two are insensitive to the projection model, while the latter two favor a quadratic projection model with a width of ≈180 ℎ −1 Mpc (equivalent to the volume of a uniform model with a width of 100 ℎ −1 Mpc and a Gaussian model with a width of 110 ℎ −1 Mpc, or a Gaussian redshift error of 0.04). Furthermore, our framework provides an efficient and flexible way to model optical cluster data vectors, paving the way for a simulation-based joint analysis for clusters, galaxies, and shear.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1985

Applications of Some Artificial Intelligence Methods to Satellite Soundings

Hard clustering of temperature profiles and regression temperature retrievals were used to refine the method using the probabilities of membership of each pattern vector in each of the clusters derived with discriminant analysis. In hard clustering the maximum probability is taken and the corresponding cluster as the correct cluster are considered discarding the rest of the probabilities. In fuzzy partitioned clustering these probabilities are kept and the final regression retrieval is a weighted regression retrieval of several clusters. This method was used in the clustering of brightness temperatures where the purpose was to predict tropopause height. A further refinement is the division of temperature profiles into three major regions for classification purposes. The results are summarized in the tables total r.m.s. errors are displayed. An approach based on fuzzy logic which is intimately related to artificial intelligence methods is recommended.

Munteanu, M. J.↗
NASA NTRS2004

Clustering with Missing Values: No Imputation Required

Clustering algorithms can identify groups in large data sets, such as star catalogs and hyperspectral images. In general, clustering methods cannot analyze items that have missing data values. Common solutions either fill in the missing values (imputation) or ignore the missing data (marginalization). Imputed values are treated as just as reliable as the truly observed data, but they are only as good as the assumptions used to create them. In contrast, we present a method for encoding partially observed features as a set of supplemental soft constraints and introduce the KSC algorithm, which incorporates constraints into the clustering process. In experiments on artificial data and data from the Sloan Digital Sky Survey, we show that soft constraints are an effective way to enable clustering with missing values.

constraints↗
DOE OSTI2025

Exploring Continuous Seismic Data at an Industry Facility Using Unsupervised Machine Learning

Seismic data recorded at industrial sites contain valuable information on anthropogenic activities. With advances in machine learning and computing power, new opportunities have emerged to explore the seismic wavefield in these complex environments. We applied two unsupervised machine learning algorithms to analyze continuous seismic data collected from an industrial facility in Texas, United States. The Uniform Manifold Approximation and Projection for Dimension Reduction algorithm was used to reduce the dimensionality of the data and generate 2D embeddings. Then, the Hierarchical Density-Based Spatial Clustering of Applications with Noise method was employed to automatically group these embeddings into distinct signal clusters. Our analysis of over 1400 hr (around 59 days) of continuous seismic data revealed five and seven signal clusters at two separate stations. At both stations, we identified clusters associated with background noise and vehicle traffic, with the latter’s temporal patterns aligning closely with the facility’s work schedule. Furthermore, the algorithms detected signal clusters from unknown sources and underline the ability of unsupervised machine learning for uncovering previously unrecognized patterns. Our analysis demonstrates the effectiveness of unsupervised approaches in examining continuous seismic data without requiring prior knowledge or pre-existing labels.

58 GEOSCIENCES↗
NASA NTRS2000

The Distance and Mass of the Galaxy Cluster Abell 1995 Derived From Sunyaev-Zel'dovich Effect and X-Ray Measurements

We present multi-wavelength observations of the Abell 1995 galaxy cluster. From analysis of x-ray spectroscopy and imaging data we derive the electron temperature, cluster core radius, and central electron number density. Using optical spectroscopy of 15 cluster members, we derive an accurate cluster redshift and velocity dispersion. Finally, the interferometric imaging of the SZE toward Abell 1995 at 28.5 GHz provides a measure of the integrated pressure through the cluster.

Patel, Sandeep K.↗
NASA NTRSDate not supplied

Differential Responses to Mechanostimulation in Embryonic Stem Cells Versus the Embryoid Body Model of Development Assessed at Single Cell RNA-Seq Resolution

Mechanicalforces generated by gravity have shaped life on Earth and impact gene expression and morphogenesis during early development. In contrast disuse canreduce normal mechanical loading, resulting in altered cell and tissue function. Although loading in adult mammals is known to promote increased cell proliferation and differentiation, little is known about how cells respondto this stimulusduring early development. In this study we sought to understand, with single cell RNA-sequencing resolution, how a 60-minute pulse of 50xg hypergravity-generated 5kPa hydrostatic pressure, influences transcriptomic regulation of developmental processes in the Embryoid Body (EB) model. Our study included both day-9 EBs and progenitor mouse embryonic stem cells (ESCs) with or without the hydrostatic pressurepulse. Single cell tSNE mapping shows limited transcriptome shifts in response to thispulse in either ESCs or EBs; this pulse,however, induces greater positional shifts in EB mapping compared to ESCs, indicating the influence of mechanotransduction is more pronounced in later states of cell commitment within the developmental program.We assessed ESCs and EBs for differentially expressed (DE) genes with hydrostatic pressurepulse and found approximately 1/3 DE genes were shared. However, gene ontology (GO) pathway analysis show that EBs have choreographed responses associated with upregulation ofpathways formulticellular development, mechanical signal transduction, and DNA damage repair. Cluster transcriptome analysis of the EBs showsmechanostimulationpromotes maintenance of transitory cell phenotypes in early development,including EB cluster co-expression of markers for progenitor, post-implant epiblast and primitive endoderm phenotypes versus expression exclusivity in the non-pulsed clusters. Pseudotime analysisidentified three branching cell types susceptible tohydrostatic pressureinduction of cell fate decisions. In summary, this study provides novel evidence that ESC maintenance and EB development can be regulated by mechanostimulation,and that stem cells committed to a differentiation program are more sensitive to force-induced changes to their transcriptome.

Cassandra Juran↗
DOE OSTI2026

Dark Energy Survey Year 3 results: Simulation-based 𝑤CDM inference from weak lensing and galaxy clustering maps with deep learning: Analysis design

Data-driven approaches using deep learning are emerging as powerful techniques to extract non-Gaussian information from cosmological large-scale structure. Here, this work presents the first simulation-based inference (SBI) pipeline that combines weak lensing and galaxy clustering maps in a realistic Dark Energy Survey Year 3 (DES Y3) configuration and serves as preparation for a forthcoming analysis of the survey data. We develop a scalable forward model based on the CosmoGridV1 suite of N-body simulations to generate over one million self-consistent mock realizations of DES Y3 at the map level. Leveraging this large dataset, we train deep graph convolutional neural networks on the full survey footprint in spherical geometry to learn low-dimensional features that approximately maximize mutual information with target parameters. These learned compressions enable neural density estimation of the implicit likelihood via normalizing flows in a ten-dimensional parameter space spanning cosmological 𝑤CDM, intrinsic alignment, and linear galaxy bias parameters, while marginalizing over baryonic, photometric redshift, and shear bias nuisances. To ensure robustness, we extensively validate our inference pipeline using synthetic observations derived from both systematic contaminations in our forward model and independent Buzzard galaxy catalogs. Our forecasts yield significant improvements in cosmological parameter constraints, achieving 2−3× higher figures of merit in the 𝛺 𝑚 − 𝑆 8 plane relative to our implementation of baseline two-point statistics and effectively breaking parameter degeneracies through probe combination. These results demonstrate the potential of SBI analyses powered by deep learning for upcoming Stage-IV wide-field imaging surveys.

Thomsen, A. [Zurich, ETH] (ORCID:0000000203099021)↗
DOE OSTI2024

SPT clusters with DES and HST weak lensing. II. Cosmological constraints from the abundance of massive halos

We present cosmological constraints from the abundance of galaxy clusters selected via the thermal Sunyaev-Zel’dovich (SZ) effect in South Pole Telescope (SPT) data with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). The cluster sample is constructed from the combined SPT-SZ, SPTpol ECS, and SPTpol 500d surveys, and comprises 1,005 confirmed clusters in the redshift range 0.25–1.78 over a total sky area of 5200 deg 2 . We use DES Year 3 weak-lensing data for 688 clusters with redshifts 𝑧 < 0.95 and HST weak-lensing data for 39 clusters with 0.6 < 𝑧 < 1.7. The weak-lensing measurements enable robust mass measurements of sample clusters and allow us to empirically constrain the SZ observable-mass relation without having to make strong assumptions about, e.g., the hydrodynamical state of the clusters. For a flat Λ⁢ CDM cosmology, and marginalizing over the sum of massive neutrinos, we measure Ω m = 0.286 ± 0.032, 𝜎 8 = 0.817 ± 0.026, and the parameter combination 𝜎 8 ⁢(Ω m /0.3) 0.25 = 0.805 ± 0.016. Our measurement of 𝑆 8 ≡ 𝜎 8 ⁢$\sqrt{Ω_{m}/0.3}$ = 0.795 ± 0.029 and the constraint from Planck CMB anisotropies (2018 TT, TE, EE+lowE) differ by 1.1⁢𝜎. In combination with that Planck dataset, we place a 95% upper limit on the sum of neutrino masses ∑𝑚 𝜈 < 0.18 eV. When additionally allowing the dark energy equation of state parameter 𝑤 to vary, we obtain 𝑤 = −1.45 ± 0.31 from our cluster-based analysis. In combination with Planck data, we measure 𝑤 =−1.3⁢4$^{+0.22}_{−0.15}$, or a 2.2⁢𝜎 difference with a cosmological constant. We use the cluster abundance to measure 𝜎8 in five redshift bins between 0.25 and 1.8, and we find the results to be consistent with structure growth as predicted by the Λ⁢ CDM model fit to Planck primary CMB data.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2011

Correlations in the (Sub)Mil1imeter Background from ACT x BLAST

We present measurements of the auto- and cross-frequency correlation power spectra of the cosmic (sub)millimeter background at: 250, 350, and 500 microns (1200, 860, and 600 GHz) from observations made with the Balloon-borne Large Aperture Submillimeter Telescope, BLAST; and at 1380 and 2030 microns (218 and 148 GHz) from observations made with the Atacama Cosmology Telescope, ACT. The overlapping observations cover 8.6 deg(sup 2) in an area relatively free of Galactic dust near the south ecliptic pole (SEP). The ACT bands are sensitive to radiation from the CMB, the Sunyaev-Zel'dovich (SZ) effect from galaxy clusters, and to emission by radio and dusty star-forming galaxies (DSFGs), while the dominant contribution to the BLAST bands is from DSFGs. We confirm and extend the BLAST analysis of clustering with an independent pipeline, and also detect correlations between the ACT and BLAST maps at over 25(sigma) significance, which we interpret as a detection of the DSFGs in the ACT maps. In addition to a Poisson component in the cross-frequency power spectra, we detect a clustered signal at 4(sigma), and using a model for the DSFG evolution and number counts, we successfully fit all our spectra with a linear clustering model and a bias that depends only on red shift and not on scale. Finally, the data are compared to, and generally agree with, phenomenological models for the DSFG population. This study represents a first of its kind, and demonstrates the constraining power of the cross-frequency correlation technique to constrain models for the DSFGs. Similar analyses with more data will impose tight constraints 011 future models.

Hajian, Amir↗
NASA NTRS1993

Infrared laser spectroscopy of jet-cooled carbon clusters - The bending dynamics of linear C9

We report improved measurements for the nu6 antisymmetric stretch fundamental and observation of the (nu6 + nu15) - nu15 and (nu6 + 2nu15) - 2nu15 hot bands of the linear C9 carbon cluster by direct absorption diode laser spectroscopy of a supersonic carbon cluster beam. Analysis of these bands characterizes C9 as a semirigid molecule with a bending potential similar to that of C5 and further evidences the alternation in degree of rigidity of linear carbon clusters with the g-u symmetry of the HOMO.

Van Orden, A.↗
NASA NTRS1996

Another collision for the Coma cluster

The wavelet transform analysis of the Rosat position sensitive proportional counter (PSPC) images of the Coma cluster are presented. The analysis shows, on small scales, a substructure dominated by two extended sources surrounding the two bright clusters NGC 4874 and NGC 4889. On scales of about 2 arcmin to 3 arcmin, the analysis reveals a tail of X-ray emission originating near the cluster center, curving to the south and east for approximately 25 arcmin and ending near the galaxy NGC 4911. The results are interpreted in terms of a merger of a group, having a core mass of approximately 10(exp 13) solar mass, with the main body of the Coma cluster.

Vikhlinin, A.↗
DOE OSTI2026

Search for Long-Lived Particles with Muon Detector Shower Signature in the CMS Run-3 data

Many beyond standard model theories predict the existence of long-lived particles (LLPs). These LLPs can have sizable lifetimes and decay several meters from their production vertex. In this poster/talk, we present the analysis strategy for searching for LLPs using the Compact Muon Solenoid (CMS) Experiment. The proton-proton collision data used in this analysis were collected from 2022 to 2024 at a center-of-mass energy of 13.6 TeV, corresponding to an integrated luminosity of 170 fb^-1. The LLP decays are reconstructed as a high-multiplicity cluster of detector hits in the cathode strip chambers (CSC) of the muon system endcap. This signature is referred to as the Muon Detector Showers (MDS). This search requires events to contain at least one MDS cluster. The analysis focuses on LLP hadronic decays and LLP masses up to a few tens of GeV. We present the signal properties in MonteCarlo simulation, event selection, background modeling, and evaluation of the expected sensitivity. The results are interpreted under the Twin Higgs model benchmark.

Agyemang-Duah, Andrews [Grambling State U.]↗
NASA NTRS1994

1919+479: Big WAT in a poor cluster

New x-ray, optical, and redshift data are presented for the cluster of galaxies associated with the giant, 1 Mpc diameter, wide-angle tailed (WAT) radio galaxy 1919+479. The ROSAT Position-Sensitive Proportional Counter (PSPC) pointed observation shows an x-ray peak on the WAT and elongated diffuse emission tracing the galaxy distribution. In addition, an asymmetric extension of emission exists between the tails of the WAT. The fitting of a Raymond-Smith thermal model to the x-ray spectra suggests an approximately = 2 keV temperature intracluster medium (ICM). The cooling time and irregular morphology rule out a cluster-wide cooling flow. The x-ray luminosity and temperature are consistent with the velocity dispersion, 480 km/s, estimated from 31 galaxy velocities. However, this velocity distribution is significantly non-Gaussian, which along with the x-ray morphology, suggests incomplete virialization in the cluster. Substructure analysis does not reveal significant clumping in the velocities/positions; but, the spatial distribution of galaxies is very elongated. Also, the cD galaxy producing the WAT does not have a significant radial peculiar velocity with respect to the cluster centroid. These characteristics are consistent with a merger scenario in which a subcluster has crossed the cluster core in the plane of the sky and has dispersed. We compare this cluster with the post-merger cluster Abell 2634 (Pinkney et al., 1993), containing the prototype WAT, and with a recent N-Body/Hydro simulation of merging clusters. The similarities indicate that the cluster 1919+479 may be the poor extreme of a class of clusters in which the bulk motion in the ICM, caused by a subcluster merger, in shaping the central WAT.

Pinkney, Jason↗
DOE OSTI2025

Reducing model error using optimized galaxy selection: weak lensing cluster mass estimation

Galaxy clusters are one of the most powerful probes to study extensions of General Relativity and the Standard Cosmological Model. Upcoming surveys like the Vera Rubin Observatory’s Legacy Survey of Space and Time are expected to revolutionise the field, by enabling the analysis of cluster samples of unprecedented size and quality. To reach this era of high-precision cluster cosmology, the mitigation of sources of systematic error is crucial. A particularly important challenge is bias in cluster mass measurements induced by the mismodelling of photometric redshift estimates of source galaxies. This work proposes a method to optimise the source sample selection in cluster weak lensing analyses drawn from wide-field survey lensing catalogs to reduce the bias on reconstructed cluster masses. We use a combinatorial optimisation scheme and methods from variational inference to select galaxies in latent space to produce a probabilistic galaxy source sample catalog for highly accurate cluster mass estimation. We show that our method reduces the critical surface mass density Σ crit relative modelling bias on the 60-70% level, while maintaining up to 90% of galaxies. We highlight that our methodology has applications beyond cluster mass estimation as an approach to jointly combine galaxy selection and model inference under sources of systematics.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1982

X-ray illumination of globular cluster puzzles

Globular clusters are thought to be among the oldest objects in the Galaxy, and provide, in this connection, important clues for determining the age and process of formation of the Galaxy. The present investigation is concerned with puzzles relating to the X-ray emission of globular clusters, taking into account questions regarding the location of X-ray emitting clusters (XEGC) unusually near the galactic plane and/or galactic center. An adopted model is discussed for the nature, formation, and lifetime of X-ray sources in globular clusters. An analysis of the available data is conducted in connection with a search for correlations between binary formation time scales, central relaxation times, galactic locations, and X-ray emission. The positive correlation found between distance from galactic center and two-body binary formation time for globular clusters, explanations for this correlation, and the hypothesis that X-ray sources in globular clusters require binary star systems provide a possible explanation of the considered puzzles.

Lightman, A. P.↗
DOE OSTI2025

The XMM Cluster Survey: automating the estimation of hydrostatic mass for large samples of galaxy clusters – I. Methodology, validation, and application to the SDSSRM-XCS sample

ABSTRACT We describe features of the X-ray: Generate and Analyse (xga) open-source software package that have been developed to facilitate automated hydrostatic mass ($M_{\rm hydro}$) measurements from XMM X-ray observations of clusters of galaxies. This includes describing how xga measures global, and radial, X-ray properties of galaxy clusters. We then demonstrate the reliability of xga by comparing simple X-ray properties, namely the X-ray temperature and gas mass, with published values presented by the XMM Cluster Survey (XCS), the Ultimate XMM eXtragaLactic survey project (XXL), and the Local Cluster Substructure Survey (LoCuSS). xga measured values for temperature are, on average, within 1 per cent of the values reported in the literature for each sample. xga gas masses for XXL clusters are shown to be ${\sim }$10 per cent lower than previous measurements (though the difference is only significant at the $\sim 1.8\sigma$ level), LoCuSS $R_{2500}$ and $R_{500}$ gas mass re-measurements are 3 per cent and 7 per cent lower, respectively (representing 1.5$\sigma$ and 3.5$\sigma$ differences). Like-for-like comparisons of hydrostatic mass are made to LoCuSS results, which show that our measurements are $10{\pm }3~{{\rm per\ cent}}$ ($19{\pm }7~{{\rm per\ cent}}$) higher for $R_{2500}$ ($R_{500}$). The comparison between $R_{500}$ masses shows significant scatter. Finally, we present new $M_{\rm hydro}$ measurements for 104 clusters from the Sloan Digital Sky Survey (SDSS) DR8 redMaPPer XCS sample (SDSSRM-XCS). Our SDSSRM-XCS hydrostatic mass measurements are in good agreement with multiple literature estimates, and represent one of the largest samples of consistently measured hydrostatic masses. We have demonstrated that xga is a powerful tool for X-ray analysis of clusters; it will render complex-to-measure X-ray properties accessible to non-specialists.

Turner, D. J. (ORCID:0000000196581396)↗
NASA NTRS2004

Microbial Characterization During the Early Habitation of the International Space Station

An evaluation of the microbiota from air, water, and surface samples provided a baseline of microbial characterization onboard the International Space Station (ISS) to gain insight into bacterial and fungal contamination during the initial stages of construction and habitation. Using 16S genetic sequencing and rep-PCR, 63 bacterial strains were isolated for identification and fingerprinted for microbial tracking. Of the bacterial strains that were isolated and fingerprinted, 19 displayed similarity to each other. The use of these molecular tools allowed for the identification of bacteria not previously identified using automated biochemical analysis and provided a clear indication of the source of several ISS contaminants. Strains of Bradyrhizobium and Sphingomonas unable to be identified using sequencing were identified by comparison of rep-PCR DNA fingerprints. Distinct DNA fingerprints for several strains of Methylobacterium provided a clear indication of the source of an ISS water supply contaminant. Fungal and bacterial data acquired during monitoring do not suggest there is a current microbial hazard to the spacecraft, nor does any trend indicate a potential health risk. Previous spacecraft environmental analysis indicated that microbial contamination will increase with time and will require continued surveillance. Copyright 2004 Springer-Verlag.

Fungi/genetics↗