A Flash Clustering Algorithm for North Alabama Lightning Mapping Array Data
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flash↗
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Results for “data clustering”
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An Automatic Learning Framework for Smart Residential Communities
Predictability has been foundational to matching supply and demand in the day-to-day operation of the electric power system. Demand predictability is eroding because of the increased use of renewable energy resources and more sophisticated loads, such as electric vehicles and smart appliances. In this paper, an automatic software framework is described which can be used for load forecasting in smart communities. A time-varying clustering-based Markov chain approach is used to predict the energy consumption of residential buildings in a smart community. The training data is based on 1-minute meter data of occupied homes over one month. The data points are first clustered based on the energy consumption and the time of the day. Then, the original data is converted using the Centroids of the clusters. A time-varying Markov chain is subsequently trained to model the energy consumption behavior of residents for each home using the transformed data. The trained model is shown to successfully predict load in 5-minute intervals over a 24 hours period.
Zandi, Helia↗
Reduction Potentials of [FeFe]-Hydrogenase Accessory Iron–Sulfur Clusters Provide Insights into the Energetics of Proton Reduction Catalysis
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solar (fuels), biofuels (including algae and bioma↗
dCache: Inter-disciplinary storage system
The dCache project provides open-source software deployed internationally to satisfy ever more demanding storage requirements. Its multifaceted approach provides an integrated way of supporting different use-cases with the same storage, from high throughput data ingest, data sharing over wide area networks, efficient access from HPC clusters and long term data persistence on a tertiary storage. Though it was originally developed for the HEP experiments, today it is used by various scientific communities, including astrophysics, biomed, life science, which have their specific requirements. In this paper we describe some of the new requirements as well as demonstrate how dCache developers are addressing them.
Mkrtchyan, Tigran↗
Using Statistical Multivariable Models to Understand the Relationship Between Interplanetary Coronal Mass Ejecta and Magnetic Flux Ropes
In-situ measurements of interplanetary coronal mass ejections (ICMEs) display a wide range of properties. A distinct subset, "magnetic clouds" (MCs), are readily identifiable by a smooth rotation in an enhanced magnetic field, together with an unusually low solar wind proton temperature. In this study, we analyze Ulysses spacecraft measurements to systematically investigate five possible explanations for why some ICMEs are observed to be MCs and others are not: i) An observational selection effect; that is, all ICMEs do in fact contain MCs, but the trajectory of the spacecraft through the ICME determines whether the MC is actually encountered; ii) interactions of an erupting flux rope (PR) with itself or between neighboring FRs, which produce complex structures in which the coherent magnetic structure has been destroyed; iii) an evolutionary process, such as relaxation to a low plasma-beta state that leads to the formation of an MC; iv) the existence of two (or more) intrinsic initiation mechanisms, some of which produce MCs and some that do not; or v) MCs are just an easily identifiable limit in an otherwise corntinuous spectrum of structures. We apply quantitative statistical models to assess these ideas. In particular, we use the Akaike information criterion (AIC) to rank the candidate models and a Gaussian mixture model (GMM) to uncover any intrinsic clustering of the data. Using a logistic regression, we find that plasma-beta, CME width, and the ratio O(sup 7) / O(sup 6) are the most significant predictor variables for the presence of an MC. Moreover, the propensity for an event to be identified as an MC decreases with heliocentric distance. These results tend to refute ideas ii) and iii). GMM clustering analysis further identifies three distinct groups of ICMEs; two of which match (at the 86% level) with events independently identified as MCs, and a third that matches with non-MCs (68 % overlap), Thus, idea v) is not supported. Choosing between ideas i) and iv) is more challenging, since they may effectively be indistinguishable from one another by a single in-situ spacecraft. We offer some suggestions on how future studies may address this.
Riley, P.↗
Hypergraph Random Walks, Laplacians, and Clustering
We propose a flexible framework for clustering hypergraph-structured data based on recently proposed random walks utilizing edge-dependent vertex weights. When incorporating edge-dependent vertex weights (EDVW), a weight is associated with each vertex-hyperedge pair, yielding a weighted incidence matrix of the hypergraph. Such weightings have been utilized in term-document representations of text data sets. We explain how random walks with EDVW serve to construct different hypergraph Laplacian matrices, and then develop a suite of clustering methods that use these incidence matrices and Laplacians for hypergraph clustering. Using 20Newsgroup, U.S. patent, Reuters' Corpus Volume 1, and genetics data sets, we compare the performance of these clustering algorithms experimentally against a variety of existing hypergraph clustering methods. We show that the proposed methods produce higher-quality clusters.
hypergraphs, clustering, laplacian, random walk, M↗
Dark Energy Survey Year 3 Results: Cosmological Constraints from Cluster Abundances, Weak Lensing, and Galaxy Clustering
Galaxy clusters provide a unique probe of the late-time cosmic structure and serve as a powerful independent test of the $\Lambda$CDM model. This work presents the first set of cosmological constraints derived with ~16,000 optically selected redMaPPer clusters across nearly 5,000 $\rm{deg}^2$ using DES Year 3 data sets. Our analysis leverages a consistent modeling framework for galaxy cluster cosmology and DES-Y3 joint analyses of galaxy clustering and weak lensing (3x2pt), ensuring direct comparability with the DES-Y3 3x2pt analysis. We obtain constraints of $S_8 = 0.864 \pm 0.035$ and $\Omega_{\rm{m}} = 0.265^{+0.019}_{-0.031}$ from the cluster-based data vector. We find that cluster constraints and 3x2pt constraints are consistent under the $\Lambda$CDM model with a Posterior Predictive Distribution (PPD) value of $0.53$. The consistency between clusters and 3x2pt provides a stringent test of $\Lambda$CDM across different mass and spatial scales. Jointly analyzing clusters with 3x2pt further improves cosmological constraints, yielding $S_8 = 0.811^{+0.022}_{-0.020}$ and $\Omega_{\rm{m}} = 0.294^{+0.022}_{-0.033}$, a $24\%$ improvement in the $\Omega_{\rm{m}}-S_8$ figure-of-merit over 3x2pt alone. Moreover, we find no significant deviation from the Planck CMB constraints with a probability to exceed (PTE) value of $0.6$, significantly reducing previous $S_8$ tension claims. Finally, combining DES 3x2pt, DES clusters, and Planck CMB places an upper limit on the sum of neutrino masses of $\sum m_\nu < 0.26$ eV at 95% confidence under the $\Lambda$CDM model. These results establish optically selected clusters as a key cosmological probe and pave the way for cluster-based analyses in upcoming Stage-IV surveys such as LSST, Euclid, and Roman.
79 ASTRONOMY AND ASTROPHYSICS↗
The distance to the Large Magellanic Cloud - Constraints from Cepheids in Large Magellanic Cloud star clusters
We have used recent observational data for the Cepheids in the rich, young LMC clusters NGC 1866 and NGC 2031 to constrain the cluster distances with the mass-equivalency (ME) method. The basis of this approach is to fix the cluster distances by requiring the Cepheid evolutionary and pulsational masses to be equal. Using evolutionary models incorporating a mild amount of core and envelope overshooting along with recent pulsational models, we derive distance moduli of 18.51 +/- 0.21 and 18.32 +/- 0.20 for NGC 1866 and NGC 2031, respectively. The quoted errors are dominated by the uncertainties in the heavy element abundances of the clusters (assumed to be 0.3 dex for both clusters), with a smaller contribution due to the apparently intrinsic spread in the masses of the Cepheids in each cluster. For the ME method, we find that Delta(m-M)(0)/Delta sub Z(1) = 0.69, where Z(1) = log (Z/0.016). This result implies that the cluster distances can be determined to better than +/- 5 percent if the cluster abundances can be measured to better than about +/- 0.15 dex.
Bertelli, Gianpaolo↗
Clusterdv: a simple density-based clustering method that is robust, general and automatic
Abstract Motivation How to partition a dataset into a set of distinct clusters is a ubiquitous and challenging problem. The fact that data vary widely in features such as cluster shape, cluster number, density distribution, background noise, outliers and degree of overlap, makes it difficult to find a single algorithm that can be broadly applied. One recent method, clusterdp, based on search of density peaks, can be applied successfully to cluster many kinds of data, but it is not fully automatic, and fails on some simple data distributions. Results We propose an alternative approach, clusterdv, which estimates density dips between points, and allows robust determination of cluster number and distribution across a wide range of data, without any manual parameter adjustment. We show that this method is able to solve a range of synthetic and experimental datasets, where the underlying structure is known, and identifies consistent and meaningful clusters in new behavioral data. Availability and implementation The clusterdv is implemented in Matlab. Its source code, together with example datasets are available on: https://github.com/jcbmarques/clusterdv. Supplementary information Supplementary data are available at Bioinformatics online.
Marques, João C.↗
Gas-Phase Stability of Large Lanthanide:Ligand Clusters Evaluated Using Collision-Induced Dissociation
Introduction In the reprocessing of f-elements present in used nuclear fuels, a variety of diglycolamides (DGA’s) are used as extractants for actinide partitioning. In particular, the Actinide-Lanthanide Separation (ALSEP) process typically utilizes either the N,N,N’,N’-tetraoctyl diglycolamide (TODGA) or N,N,N',N'-tetra-2-ethylhexyl diglycolamide (T2EHDGA) extractant ligands following the partitioning of uranium and plutonium from used nuclear fuel. To better understand fundamental interactions in these processes, covalent bonding of several f-elements with diglycolamides, primarily TODGA, is investigated in the gas phase using nanospray ionization and a quadrupole time-of-flight mass spectrometer. Further, analysis of the identity and relative strength of the cluster is enabled by MS2 isolation and collision induced dissociation. Methods Metal ion cluster analysis was completed using a Bruker (Billerica, MA, USA) mircOTOF-Q II quadrupole time-of-flight mass spectrometer with a CaptiveSpray nanospray ion source. Detection was accomplished using positive ionization mode. Metal: ligand solutions were assembled as 30 µM europium nitrate, samarium nitrate, cerium nitrate, or holmium nitrate and 3 µM DGA in acetonitrile or a 50:50 mixture of acetonitrile: isopropanol. Preliminary data The samarium cluster experiments yielded clusters with a samarium:TODGA ratio of up to 1:7 able to be isolated and evidence of greater ratios present in the mass spectrum. This is surprising, as metal clusters are not expected to have a coordination space able to accommodate this many TODGA ligands, due to its size and tridenticity. Collisional activation of [Sm(TODGA)3]3+ suggested loss of a TODGA radical cation, in addition to ligand fragmentation. In contrast, activation of clusters with higher Sm:TODGA ratios resulted in loss of entire ligands, with no evidence of fragmentation. A lower collision energy was required to remove ligands as the number of bound TODGAs increased, suggesting that in larger clusters, ligands are more delicately complexed to the metal. In addition, several clusters were observed with the composition [Sm(NO3)x(TODGA)n x]+3 x. With a single nitrate ion, clusters with up to six TODGAs were able to be isolated. In a similar pattern to the samarium clusters containing only TODGA, less collision energy was required to eliminate one or more TODGAs with increasing size. Clusters with composition [Sm(NO3)(TODGA)n-1]2+ appeared in lower abundance and were more collisionally stable than [Sm(TODGA)n]3+ clusters. With two nitrate ions, only clusters with a single TODGA were able to be isolated. Analogous europium experiments resulted in similar clusters. Ratios of up to 1:7 Eu:TODGA and clusters with one nitrate and up to five TODGAs were isolated. In clusters with two nitrate ions, only one or two TODGAs were observed to be bound. Similar to samarium, MS2 experiments with the Eu clusters suggested that larger clusters required less collision energy to eliminate TODGA. Europium clusters with the composition [Eu(NO3)(TODGA)n-1]2+ were observed in greater abundance and with greater stability than the equivalent cluster with the composition [Eu(TODGA)n]3+. Novel Aspect These are the first reported Ln:TODGA clusters, allowing us to begin to investigate intrinsic complexation of lanthanides with process-relevant ligands.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Cosmology from large-scale galaxy clustering and galaxy–galaxy lensing with Dark Energy Survey Science Verification data
We present cosmological constraints from the Dark Energy Survey (DES) using a combined analysis of angular clustering of red galaxies and their cross-correlation with weak gravitational lensing of background galaxies. We use a 139 square degree contiguous patch of DES data from the Science Verification (SV) period of observations. Using large scale measurements, we constrain the matter density of the Universe as $\Omega_m = 0.31 \pm 0.09$ and the clustering amplitude of the matter power spectrum as $\sigma_8 = 0.74 +\pm 0.13$ after marginalizing over seven nuisance parameters and three additional cosmological parameters. This translates into $S_8$ = $\sigma_8(\Omega_m/0.3)^{0.16} = 0.74 \pm 0.12$ for our fiducial lens redshift bin at 0.35 < z < 0.5, while $S_8 = 0.78 \pm 0.09$ using two bins over the range 0.2 < z < 0.5. We study the robustness of the results under changes in the data vectors, modelling and systematics treatment, including photometric redshift and shear calibration uncertainties, and find consistency in the derived cosmological parameters. We show that our results are consistent with previous cosmological analyses from DES and other data sets and conclude with a joint analysis of DES angular clustering and galaxy-galaxy lensing with Planck CMB data, Baryon Accoustic Oscillations and Supernova type Ia measurements.
79 ASTRONOMY AND ASTROPHYSICS↗
ON THE INTERMEDIATE-REDSHIFT CENTRAL STELLAR MASS-HALO MASS RELATION, AND IMPLICATIONS FOR THE EVOLUTION OF THE MOST MASSIVE GALAXIES SINCE z ∼ 1
The stellar mass-halo mass relation is a key constraint in all semi-analytic, numerical, and semi-empirical models of galaxy formation and evolution. However, its exact shape and redshift dependence remain under debate. Several recent works support a relation in the local universe steeper than previously thought. Based on comparisons with a variety of data on massive central galaxies, we show that this steepening holds up to z ∼ 1 for stellar masses M {sub star} ≳ 2 × 10{sup 11} M {sub ☉}. Specifically, we find significant evidence for a high-mass end slope of β ≳ 0.35-0.70 instead of the usual β ≲ 0.20-0.30 reported by a number of previous results. When including the independent constraints from the recent Baryon Oscillation Spectroscopic Survey clustering measurements, the data, independent of any systematic errors in stellar masses, tend to favor a model with a very small scatter (≲ 0.15 dex) in stellar mass at fixed halo mass, in the redshift range z < 0.8 and for M {sub star} > 3 × 10{sup 11} M {sub ☉}, suggesting a close connection between massive galaxies and host halos even at relatively recent epochs. We discuss the implications of our results with respect to the evolution of the most massive galaxies since z ∼ 1.
79 ASTRONOMY AND ASTROPHYSICS↗
High Speed Networking and Large-scale Simulation in Geodynamics
Large-scale numerical simulation has been one of the most important approaches for understanding global geodynamical processes. In this approach, peta-scale floating point operations (pflops) are often required to carry out a single physically-meaningful numerical experiment. For example, to model convective flow in the Earth's core and generation of the geomagnetic field (geodynamo), simulation for one magnetic free-decay time (approximately 15000 years) with a modest resolution of 150 in three spatial dimensions would require approximately 0.2 pflops. If such a numerical model is used to predict geomagnetic secular variation over decades and longer, with e.g. an ensemble Kalman filter assimilation approach, approximately 30 (and perhaps more) independent simulations of similar scales would be needed for one data assimilation analysis. Obviously, such a simulation would require an enormous computing resource that exceeds the capacity of a single facility currently available at our disposal. One solution is to utilize a very fast network (e.g. 10Gb optical networks) and available middleware (e.g. Globus Toolkit) to allocate available but often heterogeneous resources for such large-scale computing efforts. At NASA GSFC, we are experimenting with such an approach by networking several clusters for geomagnetic data assimilation research. We shall present our initial testing results in the meeting.
Kuang, Weijia↗
Unsupervised anomaly clustering via offset alignment in multivariate grid sensing data
Modern industries increasingly rely on multi-sensor technologies to acquire complex, high-dimensional data streams, enabling advanced monitoring and control systems. One critical application is online anomaly detection in electrical smart grids, where multivariate and multimodal sensing technologies play a vital role. However, detecting anomalies in such time-series data is challenging due to their inherent temporal dependencies and stochastic behavior. Traditional approaches based on supervised and semi-supervised learning methods depend on labeled datasets, which are often unavailable in real-world scenarios. While unsupervised methods have emerged as promising alternatives, these methods are highly susceptible to noise and outliers commonly present in sensing applications. Furthermore, deep learning-based anomaly detection methods, despite their performance, are often criticized for their black-box nature, limiting their applicability in safety-critical and online environments where interpretability and explainability are paramount. In this work, we propose an unsupervised anomaly clustering method leveraging a cyclic alignment-based offset detection algorithm for multivariate time-series signals. The proposed method is applied to multivariate data collected from vibrational, voltage, and magnetic field sensors deployed in a local grid substation. Our results demonstrate the robustness of the algorithm in accurately clustering various anomalies/events across different sensing modalities. Additionally, we compare the effectiveness of the proposed approach against a simple pattern-based anomaly detection method, which performs well for univariate data but fails to generalize to multivariate and multimodal time-series data.
Mukherjee, Subrata [ORNL] (ORCID:0000000309930338)↗
Metal abundance in the Praesepe and Hyades clusters
Calcium K-line photometry is reported for 27 A-type stars in the Praesepe cluster, and the data obtained are compared with previous K-line observations of Hyades stars. It is found that calcium and other metals are generally overabundant in Praesepe relative to field stars and that there is a considerable scatter in metal-abundance indices. Comparison with the Hyades results indicates that the Praesepe stars are as metal-enriched as the Hyades stars. These results are taken as evidence favoring Eggen's (1960) proposal that the Hyades and Praesepe clusters should be regarded as a single group having, on the average, about a factor-of-two higher metal abundance than solar-neighborhood field stars as well as a high internal dispersion in metal-line strengths. The questions of where and how the Praesepe-Hyades stars acquired their high average metal abundances, K-line strengths, and associated dispersions are briefly considered.
Henry, R. C.↗
Characterizing the Small Scale Structure in Clusters of Galaxies
We studied galaxy clusters Abell 119, Abell 754, and Abell 1750, using data from the ASCA and ROSAT satellites. In addition, we completed the paper "Merging Binary Clusters". In this paper we study three prominent bi-modal X-ray clusters: A3528, A1750 and A3395. Since the sub-clusters in these systems have projected separations of 0.93, 1.00 and 0.67 Mpc respectively, we examine their X-ray and optical observations to investigate the dynamics and possible merging of these sub-clusters. Using data taken with ROSAT and ASCA, we analyze the temperature and surface brightness distributions. We also analyze the velocity distributions of the three clusters using new measurements supplemented with previously published data. We examined both the overall cluster properties as well as the two sub-cluster elements in each. These results were then applied to the determination of the overall cluster masses, that demonstrate excellent consistency between the various methods used. While the characteristic parameters of the sub-clusters are typical of isolated objects, our temperature results for the regions between the two sub-clusters clearly confirm the presence of merger activity that is suggested by the surface brightness distributions. These three clusters represent a progression of equal-sized sub-cluster mergers, starting from initial contact to immediately before first core passage.
Forman, William R.↗
Significance of operator variation and the angle of illumination in lineament analysis on synoptic images
The significance of operator variation and the angle of illumination in acquired imagery is analyzed for lineament analysis. Five operators analyzed a LANDSAT image and four photographs of a plastic relief map illuminated at a low angle from varying directions of the Prescott, Arizona region. Significant differences were found in both number and length of the lineaments recognized by the different investigators for the images. The actual coincidence of lineaments recognized by the investigators for the same image is exceptionally low. Even the directional data on lineament orientation is significantly different from operator to operator and from image to image. Cluster analysis of the orientation data displays a clustering by operators rather than by images. It is recommended that extreme caution be taken before attempting to compare different investigators' results in lineament analysis.
Siegal, B. S.↗
Gravitational waves and galaxies cross-correlations: a forecast on GW biases for future detectors
ABSTRACT Gravitational waves (GWs) have rapidly become important cosmological probes since their first detection in 2015. As the number of detected events continues to rise, upcoming instruments like Einstein Telescope (ET) and Cosmic Explorer (CE) will observe millions of compact binary mergers. These detections, coupled with galaxy surveys by instruments such as the Dark Spectroscopic Energy Instrument (DESI), Euclid, and the Vera Rubin Observatory, will provide unique information on the large-scale structure of the universe by cross-correlating GWs with the distribution of galaxies hosting them. In this paper, we focus on how cross-correlations constrain the clustering bias of GWs emitted by the coalescence of binary black holes (BBHs). This parameter links BBHs to the underlying dark matter distribution, hence informing us how they populate galaxies. Using a multitracer approach, we forecast the precision of these measurements under different survey combinations. Our results indicate that current GW detectors will have limited precision, with measurement errors as high as $\displaystyle \sim 50~{{\ \rm per\ cent}}$. However, third-generation detectors like ET, when cross-correlated with Legacy Survey of Space and Time (LSST) data, can improve clustering bias measurements to within 2.5 per cent. Furthermore, we demonstrate that these cross-correlations can enable a per cent-level measurement of the magnification lensing effect on GWs. Despite this, there is a degeneracy between magnification and evolution biases, which hinders the precision of both. This degeneracy is most effectively addressed by assuming knowledge of one bias or targeting an optimal redshift range of $\displaystyle 1 \lt z \lt 2.5$. Our analysis opens new avenues for studying the distribution of BBHs and testing the nature of gravity through large-scale structure.
Zazzera, Stefano (ORCID:0000000158979221)↗