Learning Associations between Features and Clusters: An Interpretable Deep Clustering Method
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Irradiation examination shows that gas bubble swelling kinetics is much faster after irradiation-induced recrystallization than that prior recrystallization in UMo fuels. It implies that gas bubbles in coarse grains and small recrystallized grains have different growth behavior. In this work, a phase-field model of gas bubble evolution integrating microstructure dependent cluster dynamics has been developed, for the first time, to study the gas bubble swelling behavior in the recrystallization zone of UMo fuels. Generation, diffusion, reaction, sink, emission and clustering of vacancies and interstitials are described by the cluster dynamics model while a phase-field model is used to describe the evolution of non-equilibrium gas bubbles including nucleation and growth. With the coupled model, the effect of defect generation rate, clustering rate, interstitial emission and sink rates on grain boundaries on the gas bubble evolution are systematically simulated. A set of model parameters (defect generation rate, clustering rate, interstitial emission and sink rates) is determined by comparing measured and simulated gas bubble swelling kinetics. The results demonstrate that interstitial clustering is one of the important physical mechanisms which results in a fast gas bubble swelling kinetics in the recrystallization zone. The developed model can also be extended to study the associated growth of defect and second phase precipitates often observed in irradiated materials.
We apply a friends-of-friends (FoF) algorithm to identify galaxy clusters and we use the catalog to explore the evolutionary synergy between brightest cluster galaxies (BCGs) and their host clusters. We base the cluster catalog on the dense HectoMAP redshift survey (2000 redshifts deg -2 ). The HectoMAP FoF catalog includes 346 clusters with 10 or more spectroscopic members within the range 0.05 < z < 0.55 and with a median z = 0.29. We list these clusters and their members. We also include central velocity dispersions (σ*, BCG ) for the FoF cluster BCGs, a distinctive feature of the HectoMAP FoF catalog. HectoMAP clusters with higher galaxy number density (80 systems) are all genuine clusters with a strong concentration and a prominent BCG in Subaru/Hyper Suprime-Cam images. The phase-space diagrams show the expected elongation along the line of sight. Lower-density systems include some low reliability systems. We establish a connection between BCGs and their host clusters by demonstrating that σ*, BCG /σ cl decreases as a function of cluster velocity dispersion (σ cl ), in contrast, numerical simulations predict a constant σ*, BCG /σ cl . Sets of clusters at two different redshifts show that BCG evolution in massive systems is slow over the redshift range z < 0.4. The data strongly suggest that minor mergers may play an important role in BCG evolution in clusters with σ cl ≳ 300 km s -1 . For lower mass systems (σ cl < 300 km s -1 ), major mergers may play a significant role. The coordinated evolution of BCGs and their host clusters provides an interesting test of simulations in high-density regions of the universe.
The increasing occurrence of extreme weather events is challenging power grid operation. For extreme weather events, the system operator is responsible for estimating the power outages and scheduling the restoration resources. This paper proposes an outage evaluation framework to identify the possible unserved load profiles, vulnerable areas, and mobile energy adequacy. The outputs of an outage prediction model tool are used to generate numerous faulted line scenarios. Next, each scenario's nodal unserved load profile is obtained by solving a three-phase restoration model that considers repair crews and mobile energy resources (MERs). Then, a novel scenario clustering strategy is developed to cluster the unserved load profiles into multiple representative profiles which the system operator can focus on. Finally, case studies on a distribution system evaluate the damage caused by an extreme weather event and verify the effectiveness of the proposed scenario clustering strategy.
We present a Bayesian population modeling method to analyze the abundance of galaxy clusters identified by the South Pole Telescope (SPT) with a simultaneous mass calibration using weak gravitational lensing data from the Dark Energy Survey (DES) and the Hubble Space Telescope (HST). We discuss and validate the modeling choices with a particular focus on a robust, weak-lensing-based mass calibration using DES data. For the DES Year 3 data, we report a systematic uncertainty in weak-lensing mass calibration that increases from 1% at z = 0.25 to 10% at z = 0.95 , to which we add 2% in quadrature to account for uncertainties in the impact of baryonic effects. We implement an analysis pipeline that joins the cluster abundance likelihood with a multiobservable likelihood for the Sunyaev-Zel’dovich effect, optical richness, and weak-lensing measurements for each individual cluster. We validate that our analysis pipeline can recover unbiased cosmological constraints by analyzing mocks that closely resemble the cluster sample extracted from the SPT-SZ, SPTpol ECS, and SPTpol 500d surveys and the DES Year 3 and HST-39 weak-lensing datasets. This work represents a crucial prerequisite for the subsequent cosmological analysis of the real dataset.
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We present the first joint analysis of cluster abundances and auto or cross-correlations of three cosmic tracer fields: galaxy density, weak gravitational lensing shear, and cluster density split by optical richness. From a joint analysis (4×2pt+N) of cluster abundances, three cluster cross-correlations, and the auto correlations of the galaxy density measured from the first year data of the Dark Energy Survey, we obtain Ωm=0.305-0.038+0.055 and σ8=0.783-0.054+0.064. This result is consistent with constraints from the DES-Y1 galaxy clustering and weak lensing two-point correlation functions for the flat νΛCDM model. Consequently, we combine cluster abundances and all two-point correlations from across all three cosmic tracer fields (6×2pt+N) and find improved constraints on cosmological parameters as well as on the cluster observable-mass scaling relation. This analysis is an important advance in both optical cluster cosmology and multiprobe analyses of upcoming wide imaging surveys.
The first Spectrum-Roentgen-Gamma (SRG) eROSITA public release contains 12 247 clusters and groups from its first 6 months of operation. We used the offset between the brightest cluster galaxy (BCG) and the X-ray peak ( D BCG − X ) to classify the cluster dynamical state of 3946 galaxy clusters and groups. We aim to investigate the evolution of the merger and relaxed cluster distributions with redshift and mass, and the distributions’ impact on the BCG. We used the X-ray peak from the eROSITA survey and the BCG position from the LS DR10 optical data, which includes the DECam eROSITA Survey optical data, to measure the D BCG − X offset. We modelled the distribution of D BCG − X , in units of R 500 , as the sum of two Rayleigh distributions representing the cluster’s relaxed and disturbed populations, and explored their evolution with redshift and mass. To explore the impact of the cluster’s dynamical state on the BCG luminosity, we separated the main sample according to the dynamical state. We defined clusters as relaxed if D BCG − X < 0.25R500, disturbed if D BCG − X > 0.5R500, and ‘diverse’ if 0.25R500 < D BCG − X < 0.5R500. We find no evolution of the merging fraction with redshift or mass. The width of the relaxed distribution increases with redshift, while the width of the two Rayleigh distributions decreases with mass. The analysis reveals that BCGs in relaxed clusters are brighter than BCGs in both the disturbed and diverse cluster populations. The most significant differences are found for high-mass clusters at higher redshifts. The results suggest that BCGs in low-mass clusters are less centrally bound than those in high-mass systems, irrespective of the dynamical state. Over time, BCGs in relaxed clusters progressively align with the potential centre. This alignment correlates with their luminosity growth relative to BCGs in dynamically disturbed clusters, underscoring the critical role of the cluster’s dynamical state in regulating BCG evolution.
X-ray absorption near edge structure (XANES) spectroscopy is widely used for operando catalyst characterization. We show that, for highly fluxional supported nanoclusters, the customary extraction of the oxidation state of the metal from the XANES data by fitting to the bulk standards is highly questionable. The XANES signatures as well as the apparent oxidation state for such clusters arise from a complex combination of many factors, and not only from the chemical composition in reaction conditions (e.g., oxygen content in oxidizing atmosphere). The thermally accessible isomerization and population of several structurally distinct cluster forms, cluster-support interaction, and intrinsic size effects all impact the metal oxidation state and XANES signal. We demonstrate this on copper oxide clusters with different compositions, Cu4Ox(x = 2-5) and Cu5Oy (y = 3, 5), deposited on amorphous alumina and ultrananocrystalline diamond, for which we computed the XANES spectra and compare the results to the experiment. We show in addition that fitting the experimental spectrum to calculated spectra of supported clusters can, in contrast, provide good agreement and insight into the spectrum-composition-structure relation. Experimental XANES interpreted using the proposed fitting scheme shows the partial reduction of Cu oxide clusters at rising temperatures, and pinpoints the specific stoichiometries that dominate in the ensemble of cluster states as the temperature changes.
We use photometry from the DECam Legacy Survey to detect candidate tidal tails extending ~5° on either side of the Palomar 13 globular cluster. The tails are aligned with the proper motion of Palomar 13 and are consistent with its old, metal-poor stellar population. We identify three RR Lyrae stars (RRLs) that are plausibly associated with the tails, in addition to four previously known in the cluster. From these RRLs, we find that the mean distance to the cluster and tails is 23.6 ± 0.2 kpc and estimate the total (initial) luminosity of the cluster to be , consistent with previous claims that its initial luminosity was higher than its current luminosity. Combined with previously determined proper motion and radial velocity measurements of the cluster, we find that Palomar 13 is on a highly eccentric orbit (e ~ 0.8) with a pericenter of ~9 kpc and an apocenter of ~69 kpc, and a recent pericentric passage of the cluster ~75 Myr ago. We note a prominent linear structure in the interstellar dust map that runs parallel to the candidate tidal features, but conclude that reddening due to dust is unlikely to account for the structure that we observe. If confirmed, the Palomar 13 stellar stream would be one of very few streams with a known progenitor system, making it uniquely powerful for studying the disruption of globular clusters, the formation of the stellar halo, and the distribution of matter within our Galaxy.
Abstract We show the improvement to cosmological constraints from galaxy cluster surveys with the addition of cosmic microwave background (CMB)-cluster lensing data. We explore the cosmological implications of adding mass information from the 3.1 σ detection of gravitational lensing of the CMB by galaxy clusters to the Sunyaev–Zel’dovich (SZ) selected galaxy cluster sample from the 2500 deg 2 SPT-SZ survey and targeted optical and X-ray follow-up data. In the ΛCDM model, the combination of the cluster sample with the Planck power spectrum measurements prefers σ 8 Ω m / 0.3 0.5 = 0.831 ± 0.020 . Adding the cluster data reduces the uncertainty on this quantity by a factor of 1.4, which is unchanged whether the 3.1 σ CMB-cluster lensing measurement is included or not. We then forecast the impact of CMB-cluster lensing measurements with future cluster catalogs. Adding CMB-cluster lensing measurements to the SZ cluster catalog of the ongoing SPT-3G survey is expected to improve the expected constraint on the dark energy equation of state w by a factor of 1.3 to σ ( w ) = 0.19. We find the largest improvements from CMB-cluster lensing measurements to be for σ 8 , where adding CMB-cluster lensing data to the cluster number counts reduces the expected uncertainty on σ 8 by respective factors of 2.4 and 3.6 for SPT-3G and CMB-S4.
Mass-selected cluster deposition and scanning tunneling microscopy (STM) were used to investigate the surface structure and thermal stability of Ti 3 O y (y = 5, 6) clusters on a Cu(111) surface. STM imaging shows that the substoichiometric Ti 3 O 5 clusters aggregate into large dendritic assemblies at step edges, while the stoichiometric Ti 3 O 6 clusters are highly dispersed as single or small groupings of clusters. Cluster deposition also results in extensive reconstruction of the Cu(111) surface. The Ti 3 O 5 /Cu(111) surface exhibits one Cu-layer deep pits that are ringed by cluster assemblies that nucleate and grow at the perimeter step edges. By comparison, the Ti 3 O 6 /Cu(111) surface consists of irregular step edges and small one Cu-layer islands that are decorated with clusters. The restructuring of the Cu(111) surface is attributed to strong Cu-cluster interactions that release Cu adatoms from the step edges. This mechanism is supported by density functional theory (DFT) calculations, which predict that the Cu adatom attachment to the clusters is energetically favorable. Annealing the surfaces at elevated temperatures (400-700 K) results in higher densities of irregular steps, pits and isolated Cu islands as well as increased cluster aggregation. In conclusion, this work highlights adatom-cluster interactions as another manifestation of strong cluster-support interactions that can significantly alter the nature of the oxide-metal interface.
Triphenylphosphine (PPh3)-ligated gold clusters offer promising potential applications due to their relative ease of synthesis and usefulness in forming advanced cluster architectures. While previous studies reported cationic PPh3-ligated gold clusters with core sizes of Au1 - Au4, Au6 - Au11, and Au¬13 - Au14, there has not been definitive identification by mass spectrometry of larger clusters in the Au12 - Au25¬ range. Herein, we survey a polydisperse solution of cationic PPh3-ligated gold clusters using high mass-resolution (M/?M = 60,000) electrospray ionization mass spectrometry (ESI-MS). To improve the sensitivity and mass resolution of larger clusters for unambiguous identification, we increased the number of scan averages and reduced the range of mass collection windows to 200 m/z, thereby mitigating potential mass and ion abundance bias resulting from smaller “building block” gold clusters and other solution components present in higher abundance. In addition to the previously reported clusters, we identified several new species including Au5(PPh3)5+, Au12(PPh3)9HCl2+, Au15(PPh3)9Cl2+, Au16(PPh3)10Cl22+, Au17(PPh3)113+, Au18(PPh3)102+, Au19(PPh3)10Cl2+, Au20(PPh3)12H33+, Au21(PPh3)10Cl2+, and Au22(PPh3)10Cl22+, indicating that a full range of clusters between Au1 - Au22 may be observed in a single polydisperse solution. Considering all of the observed clusters, our findings provide evidence that the “magic number” icosahedral Au13 may be the transition point in cluster growth between smaller clusters, exhibiting a 1:1 gold-to-ligand ratio, and larger clusters, wherein subsequent gold atoms are added to the core without an equal number of accompanying ligands. Our method demonstrates that reducing the range of m/z collection windows and increasing the number of scan averages can improve instrument sensitivity for cationic gold clusters and enable a more complete survey of polydisperse solutions, thereby providing new insights to guide and validate the results of other characterization methods and theoretical calculations. This work was supported by the US Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. MH acknowledges support from the DOE Science Undergraduate Laboratory Internship (SULI) program. HH acknowledges support from the DOE Office of Workforce Development for Teachers and Scientist (WDTS) under the Visiting Faculty Program (VFP). This work was performed using EMSL, a national scientific user facility sponsored by the DOE's Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory (PNNL). PNNL is a multiprogram national laboratory operated for DOE by Battelle.
ABSTRACT We present a method of combining cluster abundances and large-scale two-point correlations, namely galaxy clustering, galaxy–cluster cross-correlations, cluster autocorrelations, and cluster lensing. This data vector yields comparable cosmological constraints to traditional analyses that rely on small-scale cluster lensing for mass calibration. We use cosmological survey simulations designed to resemble the Dark Energy Survey Year 1 (DES-Y1) data to validate the analytical covariance matrix and the parameter inferences. The posterior distribution from the analysis of simulations is statistically consistent with the absence of systematic biases detectable at the precision of the DES-Y1 experiment. We compare the χ2 values in simulations to their expectation and find no significant difference. The robustness of our results against a variety of systematic effects is verified using a simulated likelihood analysis of DES-Y1-like data vectors. This work presents the first-ever end-to-end validation of a cluster abundance cosmological analysis on galaxy catalogue level simulations.
The clustering of galaxy clusters links the spatial nonuniformity of dark matter halos to the growth of the primordial spectrum of perturbations. The amplitude of the clustering signal is widely used to estimate the halo mass of astrophysical objects. The advent of cluster mass calibrations enables using clustering in cosmological studies. Aims. We analyze the autocorrelation function of a large contiguous sample of galaxy clusters, the Constrain Dark Energy with X-ray (CODEX) sample, in which we take particular care of cluster definition. These clusters were X-ray selected using the ROentgen SATellite All-Sky Survey and then identified as galaxy clusters using the code redMaPPer run on the photometry of the Sloan Digital Sky Survey. We develop methods for precisely accounting for the sample selection effects on the clustering and demonstrate their robustness using numerical simulations. Methods. Using the clean CODEX sample, which was obtained by applying a redshift-dependent richness selection, we computed the two-point autocorrelation function of galaxy clusters in the 0.1 < z < 0.3 and 0.3 < z < 0.5 redshift bins. We compared the bias in the measured correlation function with values obtained in numerical simulations using a similar cluster mass range. Results. By fitting a power law, we measured a correlation length r 0 = 18.7 ± 1.1 and slope γ = 1.98 ± 0.14 for the correlation function in the full redshift range. By fixing the other cosmological parameters to their nine-year Wilkinson Microwave Anisotropy Probe values, we reproduced the observed shape of the correlation function under the following cosmological conditions: Ω m0 = $0.22_{-0.03}^{+0.04}$ and S 8 = σ 8 (Ω m0 /0.3)0.5 = $0.85_{-0.08}^{+0.10}$ with estimated additional systematic errors of σ Ω m0 = 0.02 and σS 8 = 0.20. We illustrate the complementarity of clustering constraints by combining them with CODEX cosmological constraints based on the X-ray luminosity function, deriving Ωm = 0.25 ± 0.01 and σ 8 = $0.81_{-0.02}^{+0.01}$ with an estimated additional systematic error of σ Ω m0 = 0.07 and σ σ8 = 0.04. The mass calibration and statistical quality of the mass tracers are the dominant source of uncertainty.
The orientation of triaxial galaxy clusters with respect to the line-of-sight is expected to be one of the prime sources of scatter and potential bias in optical observables (e.g., richness and weak-lensing signal) of galaxy clusters. In this work, we use the observed shape of the central Brightest Cluster Galaxy (BCG) as proxy for the orientation along the line-of-sight for clusters selected via the Sunyaev-Zel'dovich (SZ) effect from the South Pole Telescope (SPT) and Atacama Cosmology Telescope (ACT) surveys, matched to optically selected clusters from the Dark Energy Survey Year 3 (DES). We construct two samples of clusters that are designed to be identical in SZ mass estimate and redshift but with the roundest vs. the most elliptical BCGs, which we expect to correspond to BCGs (and clusters) with major axes aligned along the line-of-sight vs. in the plane of the sky, respectively. We find that the optical richness of round-BCG clusters is $\sim 10$% larger than that of elliptical-BCG clusters, in agreement with the expectation from projection effects and presenting the first such detection in data. The density profiles, however, are not in agreement with the expectation from projection effects: the 1-halo term (below $6~h^{-1}\rm{Mpc}$) of both the weak-lensing and galaxy density profiles are the same for the subsamples, contrary to previous studies based on X-ray selected clusters. In the 2-halo regime (above $6~h^{-1}\rm{Mpc}$), we find a significant excess of the elliptical-BCG cluster profiles compared to the round-BCG cluster profiles, which is the opposite of the expectation from numerical simulations. We hypothesize that the intrinsic shape of the BCG reflects not just the orientation angle, but also intrinsic properties of the cluster which can affect both the SZ signal and the amplitude of the 2-halo term.
ABSTRACT We study the properties of the Sydney University Molonglo Sky Survey (SUMSS) 843 MHz radio active galactic nuclei (AGNs) population in galaxy clusters from two large catalogues created using the Dark Energy Survey (DES): ∼11 800 optically selected RM-Y3 and ∼1000 X-ray selected MARD-Y3 clusters. We show that cluster radio loud AGNs are highly concentrated around cluster centres to $z$ ∼ 1. We measure the halo occupation number for cluster radio AGNs above a threshold luminosity, finding that the number of radio AGNs per cluster increases with cluster halo mass as N ∝ M1.2 ± 0.1 (N ∝ M0.68 ± 0.34) for the RM-Y3 (MARD-Y3) sample. Together, these results indicate that radio mode feedback is favoured in more massive galaxy clusters. Using optical counterparts for these sources, we demonstrate weak redshift evolution in the host broad-band colours and the radio luminosity at fixed host galaxy stellar mass. We use the redshift evolution in radio luminosity to break the degeneracy between density and luminosity evolution scenarios in the redshift trend of the radio AGNs luminosity function (LF). The LF exhibits a redshift trend of the form (1 + $z$)γ in density and luminosity, respectively, of γD = 3.0 ± 0.4 and γP = 0.21 ± 0.15 in the RM-Y3 sample, and γD = 2.6 ± 0.7 and γP = 0.31 ± 0.15 in MARD-Y3. We discuss the physical drivers of radio mode feedback in cluster AGNs, and we use the cluster radio galaxy LF to estimate the average radio-mode feedback energy as a function of cluster mass and redshift and compare it to the core (<0.1R500) X-ray radiative losses for clusters at $z$ < 1.
ABSTRACT Distances to the k-nearest-neighbor (kNN) data points from volume-filling query points are a sensitive probe of spatial clustering. Here, we present the first application of kNN summary statistics to observational clustering measurement, using the 1000 richest redMaPPer clusters (0.1 ≤ z ≤ 0.3) from the SDSS DR8 catalog. A clustering signal is defined as a difference in the cumulative distribution functions (CDFs) of kNN distances from fixed query points to the observed clusters versus a set of unclustered random points. We find that the k = 1, 2-NN CDFs of redMaPPer deviate significantly from the randoms’ across scales of 35 to 155 Mpc, which is a robust signature of clustering. In addition to kNN, we also measure the two-point correlation function for the same set of redMaPPer clusters versus random points, which shows a noisier and less significant clustering signal within the same radial scales. Quantitatively, the χ2 distribution for both the kNN-CDFs and the two-point correlation function measured on the randoms peak at χ2 ∼ 50 (null hypothesis), whereas the kNN-CDFs (χ2 ∼ 300, p = 1.54 × 10−36) pick up a much more significant clustering signal than the two-point function (χ2 ∼ 100, p = 1.16 × 10−6) when measured on redMaPPer. Finally, the measured 3NN and 4NN CDFs deviate from the predicted k = 3, 4-NN CDFs assuming an ideal Gaussian field, indicating a non-Gaussian clustering signal for redMaPPer clusters, although its origin might not be cosmological due to observational systematics. Therefore, kNN serves as a more sensitive probe of clustering complementary to the two point correlation function, providing a novel approach for constraining cosmology and galaxy–halo connection.