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DOE OSTI2025

Ab initio study of strain-driven vacancy clustering in aluminum

Here, we present a first-principles investigation of strain-driven vacancy clustering in aluminum. Specifically, we perform Kohn-Sham density functional theory calculations to study the influence of hydrostatic strains on clustering in tri-, quad-, and heptavacancies. We find that compressive strains are a key driving force for vacancy aggregation, particularly for collapse of clusters on the (111) plane, consistent with prior experimental observations of vacancy clusters on this plane. Notably, we find that the heptavacancy on the (111) plane collapses to form a prismatic dislocation loop for hydrostatic compressive strains exceeding 5%, highlighting the critical role of such strains in prismatic dislocation loop nucleation in aluminum.

Physics - Condensed matter physics↗

DOE OSTI2022

X-ray nano-imaging of defects in thin film catalysts via cluster analysis

Functional properties of transition-metal oxides strongly depend on crystallographic defects; crystallographic lattice deviations can affect ionic diffusion and adsorbate binding energies. Scanning x-ray nanodiffraction enables imaging of local structural distortions across an extended spatial region of thin samples. Yet, localized lattice distortions remain challenging to detect and localize using nanodiffraction, due to their weak diffuse scattering. Here, in this study, we apply an unsupervised machine learning clustering algorithm to isolate the low-intensity diffuse scattering in as-grown and alkaline-treated thin epitaxially strained SrIrO 3 films. We pinpoint the defect locations, find additional strain variation in the morphology of electrochemically cycled SrIrO 3 , and interpret the defect type by analyzing the diffraction profile through clustering. Our findings demonstrate the use of a machine learning clustering algorithm for identifying and characterizing hard-to-find crystallographic defects in thin films of electrocatalysts and highlight the potential to study electrochemical reactions at defect sites in operando experiments.

42 ENGINEERING↗

DOE OSTI2020

Using modularity to segment binary code

We consider the problem of recovering program structure from compiled binary code. We first extract the call graph and layout of functions in memory from the compiled code and represent this information in a graphical format. We then employ Louvain's modularity algorithm to identify clusters of functions that are considered to be related. We find that the quality and properties of clusters extracted by our technique are greatly impacted by the relative importance we assign to the call graph and the ordering of functions in memory.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

DESI Data Release 2 ELGs: Property-dependent subsamples, imaging systematics, and clustering

Using emission-line galaxies (ELGs) from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2, we evaluate a property-dependent correction to imaging systematics. We derive systematic weights following the same linear regression method used for other DESI tracers, but do so separately on ELG subsamples to provide a physically-informed alternative to the fiducial, neural-network-based approach. In doing so, we show that the deeper imaging in the Dark Energy Survey (DES) footprint leads to a higher overall number density but a lack of targets with extreme $g-r$ and $r-z$ colors. ELGs in the DES region also show a distinct redshift distribution when subsampled by position in the $g-r$ vs. $r-z$ plane. To address these effects, we implement a separate treatment of the DES footprint within the DESI catalog production pipeline, which is generally well-motivated and, in some cases, imperative for accurate clustering measurements. With DES treated separately, we find that property-dependent systematic weights further mitigate spurious clustering signal in $\sim$10% of subsamples, while the fiducial scheme remains optimal for the full sample.

Hagen, T. [Utah U.]↗

DOE OSTI2022

Cluster cosmology with anisotropic boosts: validation of a novel forward modelling analysis and application on SDSS redMaPPer clusters

We present a novel analysis for cluster cosmology that fully forward models the abundances, weak lensing, and the clustering of galaxy clusters. Our analysis notably includes an empirical model for the anisotropic boosts impacting the lensing and clustering signals of optical clusters. These boosts arise from a preferential selection of clusters surrounded by anisotropic large-scale structure, a consequence of the limited discrimination between line-of-sight interlopers and true cluster members offered by photometric surveys. We validate our analysis via a blind cosmology challenge on mocks, and find that we can obtain tight and unbiased cosmological constraints without informative priors or external calibrations on any of our model parameters. We then apply our analysis on the SDSS redMaPPer clusters, and find results favoring low Ωm and high σ8, combining to yield the lensing strength constraint $S_8 = 0.715_{-0.021}^{+0.024}$. We investigate potential drivers behind these results through a series of post-unblinding tests, noting that our results are consistent with existing cluster cosmology constraints but clearly inconsistent with other CMB/LSS based cosmology results. From these tests, we find hints that a suppression in the cluster lensing signal may be driving our results.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Nuclear short-range correlations and the zero-energy eigenstates of the Schrödinger equation

Here, we present a systematic analysis of the nuclear two- and three-body short-range correlations and their relations to the zero-energy eigenstates of the Schrödinger equation. To this end we analyze the doublet and triplet coupled-cluster amplitudes in the high momentum limit, and show that they obey universal equations independent of the number of nucleons and their state. Furthermore, we find that these coupled-cluster amplitudes coincide with the zero-energy Bloch-Horowitz operator. These results illuminate the relations between the nuclear many-body theory and the generalized contact formalism, introduced to describe the nuclear two-body short range correlations, and they might also be helpful for general coupled-cluster computations as the asymptotic part of the amplitudes is given and shown to be universal.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2025

XRISM Reveals Low Nonthermal Pressure in the Core of the Hot, Relaxed Galaxy Cluster A2029

We present XRISM Resolve observations of the core of the hot, relaxed galaxy cluster Abell 2029 (A2029). We find that the line-of-sight bulk velocity of the intracluster medium (ICM) within the central 180 kpc is at rest with respect to the brightest cluster galaxy, with a 3σ upper limit of ∣vbulk∣ < 100 km s−1. We robustly measure the field-integrated ICM velocity dispersion to be σv = 169 ± 10 km s−1, obtaining similar results for both single-temperature and two-temperature plasma models to account for the cluster cool core. This result, if ascribed to isotropic turbulence, implies a subsonic ICM with Mach number M 3D ≈ 0.22 and a nonthermal pressure fraction of 2.6 ± 0.3%. The turbulent velocity is similar to what was measured in the core of the Perseus cluster by Hitomi, but here in a more massive cluster with an ICM temperature of 7 keV, the limit on the nonthermal pressure fraction is even more stringent. Our result is consistent with expectations from simulations of relaxed clusters, but it is on the low end of the predicted distribution, indicating that A2029 is an exceptionally relaxed cluster with no significant impacts from either a recent minor merger or active galactic nucleus activity.

Audard, Marc (ORCID:000000034721034X)↗

DOE OSTI2020

Brightest cluster galaxies: the centre can(not?) hold

ABSTRACT We explore the persistence of the alignment of brightest cluster galaxies (BCGs) with their local environment. We find that a significant fraction of BCGs do not coincide with the centroid of the X-ray gas distribution and/or show peculiar velocities (they are not at rest with respect to the cluster mean). Despite this, we find that BCGs are generally aligned with the cluster mass distribution even when they have significant offsets from the X-ray centre and significant peculiar velocities. The large offsets are not consistent with simple theoretical models. To account for these observations BCGs must undergo mergers preferentially along their major axis, the main infall direction. Such BCGs may be oscillating within the cluster potential after having been displaced by mergers or collisions, or the dark matter halo itself may not yet be relaxed.

De Propris, Roberto↗

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 OSTI2020

Beyond Limber: efficient computation of angular power spectra for galaxy clustering and weak lensing

Angular two-point statistics of large-scale structure observables are important cosmological probes. To reach the high accuracy required by the statistical precision of future surveys, some of these statistics may need to be computed without the commonly employed Limber approximation; the exact computation however requires integration over Bessel functions, and a brute-force evaluation is slow to converge. Here, we present a new method based on our generalized FFTLog algorithm for the efficient computation of angular power spectra beyond the Limber approximation. The new method significantly simplifies the calculation and improves the numerical speed and stability. It is easily extended to handle integrals involving derivatives of Bessel functions, making it equally applicable to numerically more challenging cases such as contributions from redshift-space distortions and Doppler effects. We implement our method for galaxy clustering and galaxy-galaxy lensing power spectra. We find that using the Limber approximation for galaxy clustering in future analyses like LSST Year 1 and DES Year 6 may cause significant biases in cosmological parameters, indicating that going beyond the Limber approximation is necessary for these analyses.

weak gravitational lensing↗

NASA NTRS1990

A CLIPS expert system for clinical flow cytometry data analysis

An expert system is being developed using CLIPS to assist clinicians in the analysis of multivariate flow cytometry data from cancer patients. Cluster analysis is used to find subpopulations representing various cell types in multiple datasets each consisting of four to five measurements on each of 5000 cells. CLIPS facts are derived from results of the clustering. CLIPS rules are based on the expertise of Drs. Stewart, Duque, and Braylan. The rules incorporate certainty factors based on case histories.

Salzman, G. C.↗

DOE OSTI2022

The alignment between brightest cluster galaxies and host clusters

The alignment between the brightest cluster galaxies (BCGs) and host clusters can reveal the mystery of the formation and evolution of galaxy clusters. We measure cluster orientations in optical based on the projected distribution of member galaxies and in X-ray by fitting the morphology of intracluster medium (ICM). Cluster orientations determined in the two wavelengths are generally consistent. The orientation alignment between BCGs and host clusters is confirmed and more significant than in previous works. We find that BCGs are more aligned with cluster orientations measured in X-ray than those from optical data. Clusters with a brighter BCG generally show a stronger alignment. We argue that the detected redshift evolution of the alignment is probably caused by observational bias rather than intrinsic evolution. The alignment is not related to the ellipticity of BCGs, and the richness, ellipticity, and dynamical state of host clusters. As a result, the strong alignment between BCGs and the morphology of ICMs may be the consequence of the co-evolution between the central massive galaxy and host clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1994

Hubble Space Telescope imaging of the central star forming region in NGC 1140 (exp 1)

We present broadband images taken with the Hubble Space Telescope's Planetary Camera of the central supergiant H II region in the amorphous galaxy NGC 1140. These images allow observations to a resolution of about 13 pc at the galaxy, and they reveal that its central 1/2 kpc contains 6-7 blue, luminous, compact super star clusters, many of which would be comparable in luminosity to globular clusters at the same age. A blue arc-shaped structure near the center may be a grouping of less luminous, R136/NGC 2070-sized clusters or a sheet of OB stars. Additional somewhat less luminous and redder clusters are also found farther out from the center. If these clusters are older, they too could have had luminosities comparable to those of the central six clusters at a comparable age. Thus, we find that NGC 1140 is remarkable in the number of extreme clusters that it has formed recently in a relatively small area of the galaxy. Since NGC 1140 exhibits global characteristics that are consistent with a recent merger, these clusters are likely to be a product of that event. This galaxy adds to the number of cases where rapid star formation has evidently produced super star clusters.

Hunter, Deidre A.↗

DOE OSTI2025

Galaxy-multiplet clustering from DESI DR2

We present an efficient estimator for higher-order galaxy clustering using small groups of nearby galaxies, or multiplets. Using the Luminous Red Galaxy (LRG) sample from the Dark Energy Spectroscopic Instrument (DESI) Data Release 2, we identify galaxy multiplets as discrete objects and measure their cross-correlations with the general galaxy field. Our results show that the multiplets exhibit stronger clustering bias as they trace more massive dark matter halos than individual galaxies. When comparing the observed clustering statistics with the mock catalogs generated from the N-body simulation AbacusSummit, we find that the mocks underpredict multiplet clustering despite reproducing the galaxy two-point auto-correlation reasonably well. This discrepancy indicates that the standard Halo Occupation Distribution (HOD) model is insufficient to describe the properties of galaxy multiplets, revealing the greater constraining power of this higher-order statistic on galaxy-halo connection and the possibility that multiplets are specific to additional assembly bias. We demonstrate that incorporating secondary biases into the HOD model improves agreement with the observed multiplet statistics, specifically by allowing galaxies to preferentially occupy halos in denser environments. Our results highlight the potential of utilizing multiplet clustering, beyond traditional two-point correlation measurements, to break degeneracies in models describing the galaxy-dark matter connection.

cosmology↗

DOE OSTI2021

A Knowledge Network-Based Approach to Facilitate Annotation of Clinical Pathway Component Clusters

Mining electronic health records (EHRs) to identify contextually related clinical concept clusters that tend to co-occur temporarily and consistently could improve data-driven clinical pathway (CP) construction. However, the automatic extraction of contextually related clinical concept clusters contains a vast amount of irrelevant information. Hence, this paper proposes a knowledge network-enabled literature-based discovery (LBD) approach to remove noise from clusters. The authors used published literature to filter spurious concepts from the clusters and used data from the US Department of Veterans Affairs’s major depressive disorder (MDD) cohort of Operation Enduring Freedom/Operation Iraqi Freedom (OEF/OIF) for their experimentation. The approach was applied to 2,967 clusters extracted from the MDD OEF/OIF database. The experimental results demonstrate that the proposed approach can filter 94% of the irrelevant information. Moreover, the authors applied various network mining algorithms to analyze the clusters and demonstrated that LBD, along with network mining techniques, is a useful method for finding accurate contextually related clinical concept clusters. This could help domain researchers perform advanced analytics in CPs.

Hasan, S M Shamimul↗

NASA NTRS1994

The nuclear regions of NGC 3311 and NGC 7768 imaged with the Hubble Space Telescope Planetary Camera

We present high-resolution, V band images of the central regions of the brightest cluster ellipticals NGC 3311 and NGC 7768 taken with the Planetary Camera of the Hubble Space Telescope. The nuclei of both galaxies are found to be obscured by dust, though the morphology of the dust is quite different in the two cases. The dust cloud which obscures the central 3 arcsec of NGC 3311 is complex and irregular, while the central region of NGC 7768 contains a disk of material similar in appearance and scale to that recently observed in HST images of NGC 4261. The bright, relatively blue source detected in ground-based studies of NGC 3311 is marginally resolved and is likely to be a site of ongoing star formation. We examine the distribution of globular clusters in the central regions of NGC 3311. The gradient in the surface density profile of the cluster system is significantly shallower than that found by previous investigators at larger radii. We find a core radius for the cluster distribution of 12 plus or minus 3 kpc, which is even larger than the core radius of the globular cluster system surrounding M87. It is also an order of magnitude larger than the upper limit on the core radius of NGC 3311's stellar light and suggests that the central field-star population and the globular cluster system are dynamically distinct. We briefly discuss possible sources for the cold/warm interstellar material in early-type galaxies. While the issue has not been resolved, models which involve galactic wind failure appear to be mo st naturally consistent with the observations.

Grillmair, Carl J.↗

DOE OSTI2021

Unsupervised learning for identifying events in active target experiments

This article presents novel applications of unsupervised machine learning methods to the problem of event separation in an active target detector, the Active-Target Time Projection Chamber (AT-TPC). The overarching goal is to group similar events in the early stages of the data analysis, thereby improving efficiency by limiting the computationally expensive processing of unnecessary events. The application of unsupervised clustering algorithms to the analysis of two-dimensional projections of particle tracks from a resonant proton scattering experiment on 46 Ar is introduced. We explore the performance of autoencoder neural networks and a pre-trained VGG16 Simonyan and Zisserman (2015) convolutional neural network. We study clustering performance on both data from a simulated 46 Ar experiment, and real events from the AT-TPC detector. We find that a -means algorithm applied to simulated data in the VGG16 latent space forms almost perfect clusters. Additionally, the VGG16+-means approach finds high purity clusters of proton events for real experimental data. Here, we also explore the application of clustering the latent space of autoencoder neural networks for event separation. While these networks show strong performance, they suffer from high variability in their results.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Highly dispersed Pt atoms and clusters on hydroxylated indium tin oxide: a view from first-principles calculations

Supported single-atom and small cluster catalysts have become highly popular in heterogeneous catalysis. These catalysts can maximize the metal atom utilization while still showing superior catalytic performance. One of the main challenges in producing these small cluster catalysts is their low binding strength with the support, which causes these small clusters to sinter into larger nanoparticles. We have used first-principles simulations to study small Pt n ( n : 1,2,3) clusters on indium oxide, tin doped indium oxide, and hydroxylated tin doped indium oxide. We report that the Pt n cluster is stabilized in the presence of tin and that this is especially the case for Pt single atoms on the hydroxylated indium tin oxide support, which are anchored to the support via the hydroxyl group. On this support, the Pt single atoms become more stable than Pt 2 and Pt 3 clusters, hence decreasing sintering. These findings provide a promising way to design single-atom catalysts on electrically conducting supports for electrocatalytic applications and to better understand how functional groups on supports can increase the adhesion of cluster catalysts.

36 MATERIALS SCIENCE↗