Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “cluster finding”

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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Cloud regimes over the Amazon Basin: perspectives from the GoAmazon2014/5 campaign

Abstract. Radiosonde observations collected during the GoAmazon2014/5 campaign are analyzed to identify the primary thermodynamic regimes accompanying different modes of convection over the Amazon. This analysis identifies five thermodynamic regimes that are consistent with traditional Amazon calendar definitions of seasonal shifts, which include one wet, one transitional, and three dry season regimes based on a k-means cluster analysis. A multisensor ground-based approach is used to project associated bulk cloud and precipitation properties onto these regimes. This is done to assess the propensity for each regime to be associated with different characteristic cloud frequency, cloud types, and precipitation properties. Additional emphasis is given to those regimes that promote deep convective precipitation and organized convective systems. Overall, we find reduced cloud cover and precipitation rates to be associated with the three dry regimes and those with the highest convective inhibition. While approximately 15 % of the dataset is designated as organized convection, these events are predominantly contained within the transitional regime.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Critical magnetic Reynolds number of the turbulent dynamo in collisionless plasmas

The intracluster medium of galaxy clusters is an extremely hot and diffuse, nearly collisionless plasma, which hosts dynamically important magnetic fields of ~μG strength. Seed magnetic fields of much weaker strength of astrophysical or primordial origin can be present in the intracluster medium. In collisional plasmas, which can be approximated in the magnetohydrodynamical (MHD) limit, the turbulent dynamo mechanism can amplify weak seed fields to strong dynamical levels efficiently by converting turbulent kinetic energy into magnetic energy. However, the viability of this mechanism in weakly collisional or completely collisionless plasma is much less understood. In this study, we explore the properties of the collisionless turbulent dynamo using three-dimensional hybrid-kinetic particle-in-cell simulations. We explore the properties of the collisionless turbulent dynamo in the kinematic regime for different values of the magnetic Reynolds number, Rm, initial magnetic-to-kinetic energy ratio, (E mag /E kin ) i , and initial Larmor ratio, (r Larmor /L box ) i , i.e. the ratio of the Larmor radius to the size of the turbulent system. We find that in the ‘un-magnetized’ regime, (r Larmor /L box ) i > 1, the critical magnetic Reynolds number for the dynamo action Rm crit ≈ 107 ± 3. In the ‘magnetized’ regime, (r Larmor /L box ) i ≲ 1, we find a marginally higher Rm crit = 124 ± 8. We find that the growth rate of the magnetic energy does not depend on the strength of the seed magnetic field when the initial magnetization is fixed. We also study the distribution and evolution of the pressure anisotropy in the collisionless plasma and compare our results with the MHD turbulent dynamo.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Hydrophobic Metal–Organic Frameworks Enable Superior High-Pressure Ammonia Storage through Geometric Design

Hydrophobic metal–organic frameworks (MOFs) are typically overlooked for ammonia storage due to weak host–guest interactions. Here, we demonstrate that four structurally analogous aluminum-based MOFs exhibit a counterintuitive behavior whereby framework geometry, rather than ligand hydrophilicity, determines high-pressure NH 3 adsorption performance. The hydrophobic CAU-23 achieved an exceptional capacity matching hydrophilic analogs despite its poor low-pressure uptake. This pressure-dependent enhancement stems from the unique 4-cis-4-trans geometry of CAU-23 compared to the purely cis arrangement of MIL-160 and KMF-1 and the alternating cis-trans configuration of MOF-303. Critically, CAU-23 retained 95% capacity over three high-pressure cycles, whereas hydrophilic MOFs suffered 39–46% irreversible losses due to strong NH 3 -framework interactions that compromise structural integrity. Grand canonical Monte Carlo simulations reveal that high pressure enables NH 3 clustering through intermolecular hydrogen bonding, bypassing the need for strong host–guest interactions. High-pressure powder X-ray diffraction measurements confirm the exceptional mechanical resilience of CAU-23, showing complete structural recovery upon decompression despite exhibiting the highest pressure sensitivity among the studied MOFs. An extended analog, HE-CAU-23, validates this design principle with further enhanced capacity. Furthermore, these findings reveal a paradigm shift toward hydrophobic MOFs with optimized geometry for high-performance and regenerable gas storage applications.

MOFs↗
DOE OSTI2022

Optical depth to reionization from perturbative 21 cm clustering

The optical depth τ is the least well determined parameter in the standard model of cosmology, and one whose precise value is important for both understanding reionization and for inferring fundamental physics from cosmological measurements. Here, we forecast how well future epoch of reionization experiments could constraint τ using a symmetries-based bias expansion that highlights the special role played by anisotropies in the power spectrum on large scales. Given a parametric model for the ionization evolution inspired by the physical behavior of more detailed reionization simulations, we find that future 21 cm experiments could place tight constraints on the timing and duration of reionization and hence constraints on τ that are competitive with proposed, space-based CMB missions provided they can measure k ≈ 0.1 h Mpc -1 with a clean foreground wedge across redshifts spanning the most active periods of reionization, corresponding to ionization fractions 0.2 ≲ x ≲ 0.8. Significantly improving upon existing CMB-based measurements with next-generation 21 cm surveys would require substantially longer observations (~ 5 years) than standard $\mathscr{O}$(1000 hour) integration times. Precise measurements of smaller scales will not improve constraints on τ until a better understanding of the astrophysics of reionization is achieved. In the presence of noise and foregrounds even future 21 cm experiments will struggle to constrain τ if the ionization evolution deviates significantly from simple parametric forms.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Microstructure study of U–35 wt.% Zr alloy after quick annealing at 650 °C

Uranium-35wt.%zirconium (U-35wt.%Zr) alloy was annealed for 1 hour and 24 hours at 650 ºC and characterized to understand the early stage microstructure evolution. Dendritic microstructure with fine (~300 nm in length) α-U precipitates clustered between dendrite branches were observed in the 1-hour annealed sample. After 24-hour annealing 650 ºC, the α-U precipitates coarsened, and the dendritic microstructure disappeared due to microstructure homogenization. Furthermore, microchemical homogenization observed with Energy-Dispersive X-ray Spectroscopy analysis suggests that α-U precipitates are approaching thermodynamic equilibrium in the 24-hour annealed sample. The findings from this study have potential impacts on the manufacturing and computer modeling of metallic nuclear fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Brought to Light. I. Quantification of Disk Substructure in Dwarf Early-type Galaxies

Dwarf early-type galaxies (ETGs) display a rich diversity in their photometric, structural, and dynamical properties. In this work, we address their structural complexity by studying with deep imaging a sample of nine dwarf ETGs from the Virgo galaxy cluster, characterized by having faint disk features such as bars and spiral arms, that lie mostly hidden within the bright diffuse light of the galaxies. We present a new, robust method that aims to identify and extract the disk substructure embedded in these dwarf ETGs. The method consists in an iterative procedure that gradually separates a galaxy image into two components: the bright, dominant, diffuse component, and the much fainter, underlying disk component. By applying it to the dwarf ETG sample, we quantify their disk substructure and find that its relative contribution to the total galaxy light ranges between 2.2% and 6.4% within two effective radii. We test the reliability of the method, and prove that it is accurate in recovering the disk substructure we introduce in mock galaxy images, even at low disk-to-total light fractions of a few percent. As a potential application of the method, we perform a Fourier analysis on the extracted disk substructures and measure the orientation, length, and strength of the bars, as well as the pitch angle and strength of the spiral arms. We also briefly discuss a scenario based on the numerical simulations presented in our companion paper, Brought to Light II: Smith et al., in which we investigate the origins of the substructure in such dwarf systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

X-Ray Performance of Critical-angle Transmission Grating Prototypes for the Arcus Mission

Arcus is a proposed Explorer Class soft X-ray grating spectrometer. It aims to explore cosmic feedback by mapping hot gases within and between galaxies and galaxy clusters and characterizing jets and winds from supermassive black holes and to investigate the dynamics of protoplanetary disks and stellar accretion. Arcus features 12 m focal-length grazing-incidence silicon pore optics (SPO) developed for the Athena mission. Critical-angle transmission (CAT) gratings efficiently disperse high diffraction orders onto CCDs. We report new and improved X-ray performance results for Arcus-like CAT gratings, including a record resolving power for two coaligned CAT gratings. Multiple Arcus prototype grating facets were illuminated by an SPO at the PANTER facility. The facets consist of 32 × 32.5 mm 2 patterned silicon membranes, bonded to metal frames. The bonding angle is adjusted according to the measured average tilt angle of the grating bars in the membrane. Two simultaneously illuminated facets show a minor broadening of the Al-K α doublet in the 18th and 21st orders with the best-fit record effective resolving power of ${R}_{G}\approx {1.3}_{-0.5}^{+\infty }\times {10}^{4}$ (3σ), about three to four times the Arcus requirement. We measured the diffraction efficiency of quasi-fully illuminated gratings at O-K wavelengths in orders 4–7 in an Arcus-like configuration and compare results with synchrotron spot measurements. After corrections for geometrical effects and bremsstrahlung continuum, we find agreement between full and spot illumination at the two different facilities, as well as with the models used for Arcus effective area predictions. We find that these flight-like gratings meet the diffraction efficiency and greatly exceed the resolving power Arcus requires.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Shape-driven, emergent behavior in active particle mixtures

Abstract Active particle systems can vary greatly from one-component systems of spheres to mixtures of particle shapes at different composition ratios. We investigate computationally the combined effect of anisotropy and stoichiometry on the collective behavior of two-dimensional active colloidal mixtures of polygons. We uncover three emergent phenomena not yet reported in active Brownian particle systems. First, we find that mixtures containing hexagons exhibit micro-phase separation with large grains of hexagonal symmetry. We quantify a measurable, implicit ‘steric attraction’ between the active particles as a result of shape anisotropy and activity. This calculation provides further evidence that implicit interactions in active systems, even without explicit attraction, can lead to an effective preferential attraction between particles. Next, we report stable fluid clusters in mixtures containing one triangle or square component. We attribute the fluidization of the dense cluster to the interplay of cluster destabilizing particles, which introduce grain boundaries and slip planes into the system, causing solid-like clusters to break up into fluid clusters. Third, we show that fluid clusters can coexist with solid clusters within a sparse gas of particles in a steady state of three coexisting phases. Our results highlight the potential for a wide variety of behavior to be accessible to active matter systems and establish a route to control active colloidal systems through simple parameter designs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

Assembly bias and local Primordial non-Gaussianity from DESI DR1 quasars

The analysis of the large-scale clustering of quasars (QSO) observed by the Dark Energy Spectroscopic Instrument (DESI) represents a promising avenue for constraining local Primordial non-Gaussianity (PNG), parameterized by f NL . The signal to be constrained is the scale-dependent bias induced in the 2-point clustering of the considered tracer sample. The resulting constraints on f NL , however, are fully degenerate with the local PNG bias parameter b ϕ , dependent on the assembly bias parameter p. Using IllustrisTNG hydrodynamical simulations, we select a QSO sample reflecting the selection criteria and properties of DESI QSOs, and provide a robust prior for p, and thus for b ϕ , building on the findings of Fondi et al. 2024. We find a distribution with mean p̅ ≃ 1.4 with weak redshift dependence, stable to selection noise and consistent with the expected recent merger history typical of quasar-hosting halos. By comparing with the CAMELS simulations we demonstrate that this prior is robust to astrophysical assumptions and cosmic variance. Finally, applying this prior to the DESI DR1 dataset, we derive updated constraints on local PNG, obtaining f NL = -3.3±9.2.

cosmological parameters from LSS↗
DOE OSTI2021

Optimal dimensionality selection for independent component analysis of transcriptomic data

Independent component analysis is an unsupervised machine learning algorithm that separates a set of mixed signals into a set of statistically independent source signals. Applied to high-quality gene expression datasets, independent component analysis effectively reveals both the source signals of the transcriptome as co-regulated gene sets, and the activity levels of the underlying regulators across diverse experimental conditions. Two major variables that affect the final gene sets are the diversity of the expression profiles contained in the underlying data, and the user-defined number of independent components, or dimensionality, to compute. Availability of high-quality transcriptomic datasets has grown exponentially as high-throughput technologies have advanced; however, optimal dimensionality selection remains an open question. We computed independent components across a range of dimensionalities for four gene expression datasets with varying dimensions (both in terms of number of genes and number of samples). We computed the correlation between independent components across different dimensionalities to understand how the overall structure evolves as the number of user-defined components increases. We then measured how well the resulting gene clusters reflected known regulatory mechanisms, and developed a set of metrics to assess the accuracy of the decomposition at a given dimension. We found that over-decomposition results in many independent components dominated by a single gene, whereas under-decomposition results in independent components that poorly capture the known regulatory structure. From these results, we developed a new method, called OptICA, for finding the optimal dimensionality that controls for both over- and under-decomposition. Specifically, OptICA selects the highest dimension that produces a low number of components that are dominated by a single gene. We show that OptICA outperforms two previously proposed methods for selecting the number of independent components across four transcriptomic databases of varying sizes. OptICA avoids both over-decomposition and under-decomposition of transcriptomic datasets resulting in the best representation of the organism’s underlying transcriptional regulatory network.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Containers on Switches: A Cluster School Experience

Network switches, such as those from Arista and Mellanox, often have underutilized computational resources in the form of built-in processors and memory. By leveraging these untapped resources, we can optimize functionality and efficiency of computational cluster networks. Our research focuses on deploying containers directly onto these switches to execute various auxiliary tasks ranging from metric logging to system-wide management via post-boot configuration. By doing so, we can significantly enchance the capabilities of the cluster without the need for additional dedicated hardware. Our research involved five distinct scenarios where switch utilization could have a profound impact on HPC Clusters: run cloud-init services via link-local connection; configuring a Telegraf container to export metrics; deploying a caching proxy; creating a reconfigurable IPv6 DHCP/DNS provider for VLAN; and implementing a client detection with Magellan discovery. These scenarios were containerized with podman and docker, and tested both physically on the switch virtually on a QEMU VM both running SONiC OS. Testing and findings indicate that network switches can indeed be used for these scenarios. They offer a wide range of possibilities beyond these applications. They run as expected as containers on the switches, and although there were some minor issues, work-arounds were implemented. Overall, this is a positive result that can be further explored with more scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Search for Lensing Signatures in the Gravitational-Wave Observations from the First Half of LIGO–Virgo’s Third Observing Run

Here, we search for signatures of gravitational lensing in the gravitational-wave signals from compact binary coalescences detected by Advanced Laser Interferometer Gravitational-wave Observatory (LIGO) and Advanced Virgo during O3a, the first half of their third observing run. We study: (1) the expected rate of lensing at current detector sensitivity and the implications of a non-observation of strong lensing or a stochastic gravitational-wave background on the merger-rate density at high redshift; (2) how the interpretation of individual high-mass events would change if they were found to be lensed; (3) the possibility of multiple images due to strong lensing by galaxies or galaxy clusters; and (4) possible wave-optics effects due to point-mass microlenses. Several pairs of signals in the multiple-image analysis show similar parameters and, in this sense, are nominally consistent with the strong lensing hypothesis. However, taking into account population priors, selection effects, and the prior odds against lensing, these events do not provide sufficient evidence for lensing. Overall, we find no compelling evidence for lensing in the observed gravitational-wave signals from any of these analyses.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Emergence of quasiparticles in a doped Mott insulator

How a Mott insulator develops into a weakly coupled metal upon doping is a central question to understanding various emergent correlated phenomena. To analyze this evolution and its connection to the high- T c cuprates, we study the single-particle spectrum for the doped Hubbard model using cluster perturbation theory on superclusters. Starting from extremely low doping, we identify a heavily renormalized quasiparticle dispersion that immediately develops across the Fermi level, and a weakening polaronic side band at higher binding energy. The quasiparticle spectral weight roughly grows at twice the rate of doping in the low doping regime, but this rate is halved at optimal doping. In the heavily doped regime, we find both strong electron-hole asymmetry and a persistent presence of Mott spectral features. Finally, we discuss the applicability of the single-band Hubbard model to describe the evolution of nodal spectra measured by angle-resolved photoemission spectroscopy (ARPES) on the single-layer cuprate La 2– x Sr x CuO 4 (0 ≤ x ≤ 0.15). This work benchmarks the predictive power of the Hubbard model for electronic properties of high- T c cuprates.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Ground and excited state properties of ThB − and ThB: a theoretical study

In the present work, we studied a series of electronic and spin–orbit states of ThB − and ThB using high-level multireference and coupled-cluster theories. We report the potential energy curves (PECs), equilibrium electron configurations, spectroscopic constants, energetics, and spin–orbit coupling effects of 17 and 19 electronic states of ThB − and ThB, respectively. The ground state of ThB − is a single-reference 1 3 Π with a 1σ 2 2σ 2 3σ 1 1π 3 electron configuration. Detachment of an electron from the doubly occupied 1π orbital of ThB − (1 3 Π) produces the single-reference ground electronic state of ThB (1 4 Σ − ). The ground spin–orbit states of ThB − and of ThB are 1 3 Π + 0 and 1 4 Σ − 3/2 , respectively. The vertical electron detachment energy (VDE) of ThB − and the adiabatic electron attachment energy (AEA) of ThB at our largest CBS-C-CCSD(T)+δT(Q)+δSO (complete basis set effect, spin–orbit effect, and triple and perturbative quadruple electron correlation effect added coupled-cluster theory with single, double, and perturbative triple excitations) level are 1.473 eV and 1.459, respectively. The reaction of Th( 3 F) + B( 2 P o ) produces the ground state of ThB with a bond energy of 2.843 eV. Finally, we estimated a heat of formation, Δ H 0 f (298 K), of 891.01 kJ mol −1 for the ThB molecule. The high-level findings of this work are expected to aid and motivate future experimental spectroscopic investigations of ThB and ThB − species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Adaptive pruning-based optimization of parameterized quantum circuits

Abstract Variational hybrid quantum–classical algorithms are powerful tools to maximize the use of noisy intermediate-scale quantum devices. While past studies have developed powerful and expressive ansatze, their near-term applications have been limited by the difficulty of optimizing in the vast parameter space. In this work, we propose a heuristic optimization strategy for such ansatze used in variational quantum algorithms, which we call ‘parameter-efficient circuit training (PECT)’. Instead of optimizing all of the ansatz parameters at once, PECT launches a sequence of variational algorithms, in which each iteration of the algorithm activates and optimizes a subset of the total parameter set. To update the parameter subset between iterations, we adapt the Dynamic Sparse Reparameterization scheme which was originally proposed for training deep convolutional neural networks. We demonstrate PECT for the Variational Quantum Eigensolver, in which we benchmark unitary coupled-cluster ansatze including UCCSD and k -UpCCGSD, as well as the Low-Depth Circuit Ansatz (LDCA), to estimate ground state energies of molecular systems. We additionally use a layerwise variant of PECT to optimize a hardware-efficient circuit for the Sycamore processor to estimate the ground state energy densities of the one-dimensional Fermi-Hubbard model. From our numerical data, we find that PECT can enable optimizations of certain ansatze that were previously difficult to converge and more generally can improve the performance of variational algorithms by reducing the optimization runtime and/or the depth of circuits that encode the solution candidate(s).

Physics↗
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↗
DOE OSTI2020

X-ray properties of the X-CLASS-redMaPPer galaxy cluster sample: the luminosity–temperature relation

ABSTRACT This article presents the results of a spectroscopic analysis of the X-CLASS-redMaPPer (XC1-RM) galaxy cluster sample. X-CLASS is a serendipitous search for clusters in X-ray wavebands based on the XMM–Newton archive, whereas redMaPPer is an optical cluster catalogue derived from the Sloan Digital Sky Survey (SDSS). The present sample comprises 92 X-ray extended sources identified in optical images within 1 arcmin separation. The area covered by the cluster sample is ∼ 27 deg2. The clusters span a wide redshift range (0.05 < z < 0.6) and 88 clusters benefit from spectrosopically confirmed redshifts using data from SDSS Data Release 14. We present an automated pipeline to derive the X-ray properties of the clusters in three distinct apertures: R500 (at fixed mass overdensity), Rfit (at fixed signal-to-noise ratio) and ${R}_{300\, {\rm kpc}}$ (fixed physical radius). The sample extends over wide temperature and luminosity ranges: from 1–10 keV and from 6 × 1042 to 11 × 1044 erg s−1, respectively. We investigate the luminosity–temperature (L–T) relation of the XC1-RM sample and find a slope equal to 3.03 ± 0.26. It is steeper than predicted by self-similar assumptions, in agreement with independent studies. A simplified approach is developed to estimate the amount and impact of selection biases that might be affecting our recoveredL–Tparameters. The result of this simulation process suggests that the measuredL–Trelation is biased to a steeper slope and higher normalization.

Molham, Mona↗
DOE OSTI2026

DECADE+ DES Y3 Weak Lensing Mass Map: A 13,000 deg $\^{} 2$ View of Cosmic Structure from 270 Million Galaxies

We present the largest galaxy weak lensing mass map of the late-time Universe, reconstructed from 270 million galaxies in the DECADE and DES Year 3 datasets, covering 13,000 square degrees. We validate the map through systematic tests against observational conditions (depth, seeing, etc.), finding the map is statistically consistent with no contamination. The large area covered by the mass map makes it a well-suited tool for cosmological analyses, cross-correlation studies and the identification of large-scale structure features. We demonstrate its potential by detecting cosmic filaments directly from the mass map for the first time and validating them through their association with galaxy clusters selected using the Sunyaev-Zeldovich effect from Planck and ACT DR6.

Gatti, M.↗