Feature Selection Clustering and Prototype Placement for Turbulence Data Sets.
Abstract not provided.
Barone, Matthew F.↗
SEARCH · Engineering Papers
Results for “clustering statistics”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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Clustering and Cliques in Preferential Attachment Random Graphs with Edge Insertion
In this paper, we investigate the global clustering coefficient (a.k.a transitivity) and clique number of graphs generated by a preferential attachment random graph model with an additional feature of allowing edge connections between existing vertices. Specifically, at each time step t, either a new vertex is added with probability f(t), or an edge is added between two existing vertices with probability 1 – f(t). We establish concentration inequalities for the global clustering and clique number of the resulting graphs under the assumption that f(t) is a regularly varying function at infinity with index of regular variation –$\gamma$, where $\gamma$ $\in$ [0, 1). Finally, we also demonstrate an inverse relation between these two statistics: the clique number is essentially the reciprocal of the global clustering coefficient.
97 MATHEMATICS AND COMPUTING↗
Revisiting the Definition of Rapid Intensification of Tropical Cyclones by Clustering the Initial Intensity and Inner‐Core Size
Abstract Rapid intensification (RI) of tropical cyclones (TCs) provides a great challenge in operational forecasting and contributes significantly to the development of major TCs. RI is commonly defined as an increase in the maximum sustained surface wind speed of at least a certain threshold within 24 hr. The most widely used threshold is 30 kt (15.4 m/s), which was determined statistically. Here we propose a new definition for RI by objectively clustering TCs using the intensification rate, initial intensity, and radius of the maximum wind speed (RMW). A group of 770 samples is separated at a threshold of 45 kt (23.2 m/s). The threshold is 40 kt (20.6 m/s) for the western North Atlantic, where TC size measurements are more reliable. Monte Carlo experiments demonstrate that the proposed threshold is robust even considering the uncertainty in RMW of as high as 30 km. We show that, when a TC undergoes RI, its maximum wind speed is approximately 60 ± 15 kt (30.9 ± 7.7 m/s) and the RMW is 45 ± 20 km. The new threshold outperforms the conventional threshold of 30 kt/24 hr in describing the bimodal distribution of lifetime maximum intensity and explaining the annual count of Category 5 TCs. This new definition provides a more physically based threshold and describes a more reliable representation of extreme events. Although more comparisons are needed for operational application, it is likely to be desirable for case‐based process studies and could provide a more valuable metric for TC intensification classification and research.
Li, Yi↗
An analytic hybrid halo + perturbation theory model for small-scale correlators: baryons, halos, and galaxies
In this work, we update Halo Zeldovich Perturbation Theory (HZPT, [1]), an analytic model for the two-point statistics of dark matter, to describe halo and galaxy clustering, and galaxy-matter cross-correlation on nonlinear scales. The model correcting Zeldovich has an analytic Fourier transform, and therefore is valid in both configuration space and Fourier space. The model is accurate at the 2%-level or less for P_mm (k< 1 h/Mpc), P_hm (k< 1 h/Mpc), P_hh (k< 2 h/Mpc), P gm (k< 1 h/Mpc), P gg (k< 1 h/Mpc), ξ mm (r> 1 Mpc/h), ξ hm (r> 2 Mpc/h), ξ hh (r> 2 Mpc/h), ξ gm (r> 1 Mpc/h), ξ gg (r> 2 Mpc/h), for LRG-like mock galaxies. We show that the HZPT model for matter correlators can account for the effects of a wide range of baryonic feedback models and provide two extended dark matter models which are of 1% (3%) accuracy for k < 10 (8) h/Mpc. We explicitly model the non-perturbative features of halo exclusion for the halo-halo and galaxy-galaxy correlators, as well as the presence of satellites for galaxy-matter and galaxy-galaxy correlation functions. We perform density estimation using N-body simulations and a wide range of HOD galaxy mocks to obtain correlations of model parameters with the cosmological parameters Ω m and σ 8 . HZPT can provide a fast, interpretable, and analytic model for combined-probe analyses of redshift surveys using scales well into the non-linear regime.
79 ASTRONOMY AND ASTROPHYSICS↗
Cluster spin glass correlations and dynamics in Zn 0.5 Mn 0.5 Te
Here, we present a combined magnetometry, muon spin-relaxation (𝜇SR), and neutron-scattering study of the insulating spin glass Zn 0.5 Mn 0.5 Te, for which magnetic Mn 2+ and nonmagnetic Zn 2+ ions are randomly distributed on a face-centered cubic lattice. The magnetometry and 𝜇SR results confirm a spin freezing transition around 𝑇 𝑓 ≈ 23 K, with the spin-fluctuation rate decreasing gradually and somewhat inhomogeneously through the sample volume as the temperature decreases toward 𝑇 𝑓 . Characteristic spin-correlation times well above 𝑇 𝑓 are on the order of 10 −10 s, much slower than typically observed in canonical spin glasses but in line with expectations for a cluster spin glass. Using magnetic pair distribution function (mPDF) analysis and reverse Monte Carlo (RMC) modeling of the magnetic diffuse neutron-scattering data, we show that the spin-glass ground state consists of clusters of spins exhibiting short-range-ordered type-III antiferromagnetic correlations with a locally ordered moment of 3.1(1)𝜇 B between nearest-neighbor spins. The type-III correlations decay exponentially as a function of spin separation distance with a correlation length of approximately 5 Å. The diffuse magnetic scattering and corresponding mPDF show no significant changes across 𝑇 𝑓 , indicating that the dynamically fluctuating short-range spin correlations in the paramagnetic state retain the same basic type-III configuration that characterizes the spin-glass state; the only change apparent from the neutron-scattering data is a gradual reduction of the correlation length and locally ordered moment with increasing temperature. Taken together, these results paint a unique and detailed picture of the local magnetic structure and dynamics in Zn 0.5 Mn 0.5 Te and provide strong evidence that this material is best described as a cluster spin glass. In addition, this work showcases a statistical method for extracting diffuse scattering signals from neutron powder diffraction data, which we developed to facilitate the mPDF and RMC analysis of the neutron data. This method has the potential to be broadly useful for neutron powder diffraction experiments on a variety of materials with short-range atomic or magnetic order.
magnetism↗
Geospatial analysis of preterm and small-for-gestational age births in Washington D.C.
Background: This study is based on the recognition that adverse pregnancy outcomes significantly affect maternal and infant health, leading to increased morbidity and mortality. These outcomes are shaped by a complex interplay of individual-level factors—like maternal age and education—and community-level influences, including socio-economic status and access to healthcare. Understanding these determinants is crucial for developing effective public health strategies, especially for marginalized populations, by identifying high-risk areas and informing targeted interventions that address both individual and structural barriers. Methods: We utilized geospatial analysis to explore the association between individual- and community-level factors and adverse pregnancy outcomes, specifically preterm birth (PTB) and small-for-gestational-age (SGA) birthweight in Washington, D.C. We used Empirical Bayes smoothing methods to calculate rates of adverse birth outcomes from 2010 to 2018 at the U.S. Census tract–level. Spatial scan statistics were used to investigate if adverse birth outcomes clustered in specific areas. ANOVA tests were conducted for individual- and community-level factors within identified clusters. Results: Spatial analysis identified significant high-risk clusters for PTB and SGA infants primarily in southeastern Washington, D.C., particularly in Wards 7 and 8. Individuals residing within these clusters experienced a 47% increased risk of PTB (RR = 1.467) and a 56% increased risk of SGA (RR = 1.560) compared to those outside clusters. Space–time analysis revealed temporal variation, with PTB clusters persisting from 2011 to 2014 and SGA clusters extending through 2017. Compared to low-risk clusters, high-risk clusters had younger birthing individuals (mean age ~26.5 vs. ~33 years), lower maternal college degree attainment (~20% vs. ~80%), higher rates of late or no prenatal care (~16% vs. 11%), and increased prevalence of smoking and hypertension (all P < 0.001). Community-level indicators showed lower median household incomes ($\$40,000$ vs. ~$\$105,000$), greater poverty (~16% vs. ~7% below $\$10,000$/year), higher public assistance use (~32% vs. ~5%), and reduced healthcare access (greater distances to emergency and specialty care) in high-risk areas (all P < 0.001). Neighborhood deprivation indices were significantly elevated, commutes were longer, and population density was lower in these clusters. These findings highlight that adverse birth outcomes cluster in neighborhoods with pronounced socioeconomic and health disparities. Conclusion: High-risk birth clusters highlight intertwined factors: individual, socio-economic, and geographic. Addressing these requires comprehensive interventions focusing on social and structural determinants of health.
Birth outcomes↗
FORESTR: Finding, Organizing, Representing, Explaining, Summarizing, and Thinning Random forests
Random forests have become popular models used for data driven predictions. As a result, random forests are currently used or being considered for high-consequence mission applications in national security, such as the prediction of yield from optical signals and malware detection. While random forests may provide accurate predictions, the complexity of the algorithm causes a lack of interpretability. Random forests are an ensemble of regression or decision trees. Individual regression and decision trees are interpretable, but ensembles are inherently difficult to interpret due to the compilation of many models. We aim to increase the interpretability of random forests by finding patterns in the ensemble of trees that can be used to “thin” (or remove) trees. As a starting point, in this report, we develop a new distance metric for quantifying the similarity between trees based on their topologies (i.e., shapes). We base the metric on a novel distance metric for graphs that is a proper mathematical distance, is invariant to transformations, has registration between graphs, and computes topological evolutions between graphs. We use the tree distance metric to compute tree statistics such as a “mean tree” and to identify clusters of trees. We apply the developed methodology to a toy dataset and a mission relevant product inspection dataset to demonstrate how the metric can provide insight into random forests. Furthermore, we discuss the limitations of the approach and ideas for future research into how the metric could be used as a thinning tool to develop less complex models.
97 MATHEMATICS AND COMPUTING↗
Validation of the Scientific Program for the Dark Energy Spectroscopic Instrument
The Dark Energy Spectroscopic Instrument (DESI) was designed to conduct a survey covering 14,000 deg$^{2}$ over 5 yr to constrain the cosmic expansion history through precise measurements of baryon acoustic oscillations (BAO). The scientific program for DESI was evaluated during a 5 month survey validation (SV) campaign before beginning full operations. This program produced deep spectra of tens of thousands of objects from each of the stellar Milky Way Survey (MWS), Bright Galaxy Survey (BGS), luminous red galaxy (LRG), emission line galaxy (ELG), and quasar target classes. These SV spectra were used to optimize redshift distributions, characterize exposure times, determine calibration procedures, and assess observational overheads for the 5 yr program. In this paper, we present the final target selection algorithms, redshift distributions, and projected cosmology constraints resulting from those studies. We also present a One-Percent Survey conducted at the conclusion of SV covering 140 deg$^{2}$ using the final target selection algorithms with exposures of a depth typical of the main survey. The SV indicates that DESI will be able to complete the full 14,000 deg$^{2}$ program with spectroscopically confirmed targets from the MWS, BGS, LRG, ELG, and quasar programs with total sample sizes of 7.2, 13.8, 7.46, 15.7, and 2.87 million, respectively. These samples will allow exploration of the Milky Way halo, clustering on all scales, and BAO measurements with a statistical precision of 0.28% over the redshift interval z < 1.1, 0.39% over the redshift interval 1.1 < z < 1.9, and 0.46% over the redshift interval 1.9 < z < 3.5.
79 ASTRONOMY AND ASTROPHYSICS↗
Limits of Detection for EXAFS Characterization of Heterogeneous Single-Atom Catalysts
Single-atom catalysts (SACs), consisting of individual metal atoms dispersed on a support, attract attention due to their unique reactivity, efficient use of precious metals, and precise chemical tunability. Characterization of the metal species is crucial to substantiate structure–function relationships. Authors often use—and referees often require—X-ray absorption spectroscopy (XAS) data to prove the absence of clustered metal (or metal oxide) structures after pre-treatment and under in situ or operando conditions. However, there has been no critical assessment of the limitations of XAS in substantiating such conclusive statements, which is particularly important given the potential outsized influence of minority catalyst structures in dictating catalytic activity. Here, in this article, we quantitatively assess the detection limits of XAS to identify metal (or metal oxide) clusters in samples containing predominantly single atoms by modeling the extended X-ray absorption fine structure (EXAFS) of mixtures of structures. We identified that a significant fraction of clusters can coexist with SAC active sites (e.g., ~10% metallic Pt or ~40% oxidized Pt clusters in Pt/CeO 2 SACs), while eluding detection via EXAFS with any statistical significance. To generalize these conclusions, a descriptor-based screening of bulk metal oxides using a continuous Cauchy wavelet transform was proposed that suggests certain materials for which differentiating atomically dispersed metal species and metal oxide clusters would be infeasible by EXAFS (e.g., ReO x ). Based on this analysis, we suggest best practices for the study of SACs using EXAFS and provide recommendations to ensure that conclusions do not outpace the evidence used to support them. In this rapidly expanding research area, rigorous characterization will lead to greater understanding of the behavior of SACs and ultimately improved catalytic materials.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Precipitation best-estimate event statistics (c1-level)
Best estimates of precipitation from ARM instruments derived through clustering and other computational techniques.
54 ENVIRONMENTAL SCIENCES↗
The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: cosmological implications from multitracer BAO analysis with galaxies and voids
We construct cosmic void catalogues with the dive void finder upon SDSS BOSS DR12 and eBOSS DR16 galaxy samples with BAO reconstruction, and perform a joint BAO analysis using different types of galaxies and the corresponding voids. The BAO peak is evident for the galaxy–galaxy, galaxy–void, and void–void correlation functions of all data sets, including the ones cross-correlating LRG and ELG samples. Two multitracer BAO fitting schemes are tested, one combining the galaxy and void correlation functions with a weight applied to voids, and the other using a single BAO dilation parameter for all clustering measurements. Both methods produce consistent results with mock catalogues, and on average ~10 per cent improvements of the BAO statistical uncertainties are observed for all samples, compared to the results from galaxies alone. By combining the clustering of galaxies and voids, the uncertainties of BAO measurements from the SDSS data are reduced by 5–15 per cent, yielding 0.9 per cent, 0.8 per cent, 1.1 per cent, 2.3 per cent, and 2.9 per cent constraints on the distance $D_{_{\rm V}}(z)$, at effective redshifts 0.38, 0.51, 0.70, 0.77, and 0.85, respectively. When combined with BAO measurements from SDSS MGS, QSO, and Lyα samples, as well as the BBN results, we obtain $H_0 = 67.58 \pm 0.91\, {\rm km}\, {\rm s}^{-1}\, {\rm Mpc}^{-1}$, Ω m = 0.290 ± 0.015, and $\Omega _\Lambda h^2 = 0.3241 \pm 0.0079$ in the flat-ΛCDM framework, where the 1σ uncertainties are around 6 per cent, 6 per cent, and 17 per cent smaller respectively, compared to constraints from the corresponding anisotropic BAO measurements without voids and LRG–ELG cross-correlations.
79 ASTRONOMY AND ASTROPHYSICS↗
Exploring the stellar populations of backsplash galaxies
Backsplash galaxies are those that traverse and overshoot cluster cores as they fall into these structures. They are affected by environment, and should stand out in contrast to the infalling population. We target galaxies in the vicinity of clusters (R≳R 200 ) and select a sample in projected phase space (PPS), from the compilation of Sampaio et al. based on SDSS data. We present a statistical analysis, comparing two regions in PPS, with the same projected distance to the cluster but different velocity. The analysis relies on the presence of variations in the stellar population content of backsplash galaxies. We find a lower limit in the fractional contribution of ∼5 per cent with respect to the general sample of infalling galaxies at similar group-centric distance when using single line strength analysis, or ∼15-30 per cent when adopting bivariate distributions. The stellar populations show a subtle but significant difference towards older ages, and a higher fraction of quiescent galaxies. We also compare this set with a general field sample, where a substantially larger difference in galaxy properties is found, with the field sample being consistently younger, metal poorer and with a lower fraction of quiescent galaxies. Noting that our ‘cluster’ sample is located outside of the virial radius, we expect this difference to be caused by pre-processing of the infalling galaxies in the overall higher density regions.
79 ASTRONOMY AND ASTROPHYSICS↗
Investigating the large-scale environment of wide-angle tailed radio galaxies in the local Universe
We present a statistical analysis of the large-scale (up to two Mpc) environment of a homogeneous and complete sample, both in radio and optical selection, of wide-angle tailed radio galaxies (WATs) in the local Universe (i.e., with redshifts z ≲ 0.15). The analysis is carried out using the parameters obtained from cosmological neighbors within two Mpc of the target source. Results regarding the large-scale environments of the WATs are then compared with those of Fanaroff–Riley type I (FR Is) and type II (FR IIs) radio galaxies listed in two other homogeneous and complete catalogs and selected with the same criterion adopted for the WATs catalog. We obtain indication that at low redshift, WATs inhabit environments with a larger number of galaxies than those of FR Is and FR IIs. In the explored redshift range, the physical size of the galaxy group or cluster in which the WATs reside appears to be almost constant with respect to FR Is and FR IIs, being around one Mpc. From the distribution of the concentration parameter, defined as the ratio between the number of cosmological neighbors lying within 500 kpc and within one Mpc, we conclude that WATs tend to inhabit the central region of the group or cluster in which they reside, in agreement with the general paradigm that WATs are the brightest cluster or group galaxy.
79 ASTRONOMY AND ASTROPHYSICS↗
Nonequilibrium information entropy approach to ternary fission of actinides
Ternary fission of actinides probes the state of the nucleus at scission. Light clusters are produced in space and time very close to the scission point. Within the nonequilibrium statistical operator method, a generalized Gibbs distribution is constructed from the information given by the observed yields of isotopes. Using this relevant statistical operator, yields are calculated taking excited states and continuum correlations into account, in accordance with the virial expansion of the equation of state. Furthermore, clusters with mass number A≤10 are well described using the nonequilibrium generalizations of temperature and chemical potentials. Improving the virial expansion, in-medium effects may become of importance in determining the contribution of weakly bound states and continuum correlations to the intrinsic partition function. Yields of larger clusters, which fail to reach this quasiequilibrium form of the relevant distribution, are described by nucleation kinetics, and a saddle-to-scission relaxation time of about 7000 fm/c is inferred. Light-charged particle emission, described by reaction kinetics and virial expansions, may therefore be regarded as a very important tool to probe the nonequilibrium time evolution of actinide nuclei during fission.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
A MeerKAT-meets-LOFAR study of Abell 1413: a moderately disturbed non-cool-core cluster hosting a ~500 kpc ‘mini’-halo
Many relaxed cool-core clusters host diffuse radio emission on scales of hundreds of kiloparsecs: mini-haloes. However, the mechanism responsible for generating them, as well as their connection with central active galactic nuclei, is elusive and many questions related to their physical properties and origins remain unanswered. This paper presents new radio observations of the galaxy cluster Abell 1413 performed with MeerKAT (L-band; 872 to 1712 MHz) and LOFAR HBA (120 to 168 MHz) as part of a statistical and homogeneous census of mini-haloes. Abell 1413 is unique among mini-halo clusters as it is a moderately disturbed non-cool-core cluster. Our study reveals an asymmetric mini-halo up to 584 kpc in size at 1283 MHz, twice as large as first reported at similar frequencies. The spectral index is flatter than previously reported, with an integrated value of α = −1.01 ± 0.06, shows significant spatial variation, and a tentative radial steepening. We studied the point-to-point X-ray/radio surface brightness correlation to investigate the thermal/non-thermal connection: our results show a strong connection between these components, with a superlinear slope of $b = 1.63^{+0.10}_{-0.10}$ at 1283 MHz and $b = 1.20^{+0.13}_{-0.11}$ at 145 MHz. We also explore the X-ray surface brightness/radio spectral index correlation, finding a slope of $b = 0.59^{+0.11}_{-0.11}$. Both investigations support the evidence of spectral steepening. Finally, in the context of understanding the particle acceleration mechanism, we present a simple theoretical model which demonstrates that hybrid scenarios – secondary electrons (re-)accelerated by turbulence – reproduce a superlinear correlation slope.
79 ASTRONOMY AND ASTROPHYSICS↗
Discovering Dark Matter Clumps and Primordial Particles with Galaxies
Cosmological observations and galaxy dynamics seem to imply that five out of six parts in mass of all matter in the universe is composed of dark matter, which is not accounted for by the Standard Model of particles. The cold dark matter (CDM) paradigm has been extremely successful at describing observations on large-cosmological scale. However, many different dark matter candidates have the same observable effects as CDM on large-length scales. One possible avenue to distinguish between these different models is to look on much smaller-length scales, where usually dark matter models become distinguishable. This research developed the theoretical framework and statistical tools needed to map the detailed distribution of dark matter on subgalactic scales using strong gravitational lensing. A second goal of this research was to build new statistical techniques that efficiently exploit the full power of cosmic-structure data from next-generation surveys. Galaxy clustering on large scales provides significant cosmological information through the power spectrum. Additional information can be gained from higher-order statistics. This research provided new ways to understand the initial conditions of the universe from current and upcoming cosmological surveys.
79 ASTRONOMY AND ASTROPHYSICS↗
Projecting Future Energy Production from Operating Wind Farms in North America. Part II: Statistical Downscaling
Abstract Capacity factors (CFs) derived from daily expected power at 22 operating wind farms in different regions of North America are used as predictands to train statistical downscaling algorithms using output from ERA5. The statistical downscaling models are then used to make CF projections for a suite of CMIP6 Earth System Models (ESMs). Downscaling is performed using a hybrid statistical approach that employs synoptic types derived using k -means clustering applied to sea level pressure fields with variance corrections applied as a function of the pressure gradient intensity. ESMs exhibit marked variability in terms of the skill with which the frequency of synoptic types and pressure gradients are reproduced relative to ERA5, and that differential skill is used to infer differential credibility in the associated CF projections. Projections of median annual mean CF [P50(CF)] in each 20-yr period from 1980 to 2099 show evidence of declines at most wind farms except in parts of the southern Great Plains, although the magnitude of the changes is strongly dependent on the ESM. For example, P50(CF) in 2080–99 deviate from those in 1980–99 by from −3.1 to +0.2 percentage points in the Northeast. The largest-magnitude declines in P50(CF) ranging from −3.9 to −2 percentage points are projected for the southern West Coast. CF trends exhibit marked seasonality and are strongly linked to changes in the relative intensity of future synoptic patterns, with much less impact from shifts in the occurrence of synoptic types over time. Internal climate modes continue to play a significant role in inducing interannual variability in wind power production, even under high radiative forcing scenarios. Significance Statement We describe how future climate changes may affect wind resources and wind power generation. Near-term changes in projected wind power electricity generation potential at operating wind farms over North America are small, but by the end of the current century electricity production is projected to decrease in many areas but may increase in parts of the southern Great Plains. The amount of change in projected wind power production is a strong function of the Earth system model that is downscaled and also depends on the continued presence of internally forced climate variability. An additional dependence on the amount of greenhouse gas–induced global warming indicates the transition of the energy sector to low-carbon sources may assist in maintaining the abundant U.S. wind resource.
Meteorology & Atmospheric Sciences↗
A bi-level spatiotemporal clustering approach and its application to drought extraction
We present a novel flexible bi-level spatiotemporal clustering algorithm to extract events based on their intensity and spatiotemporal structures. Our algorithm consists of using (i) a novel space-time k-means clustering to obtain spatiotemporally coherent intensity clusters, and (ii) a density-based spatial clustering of applications with noise (DBSCAN) to spatiotemporally section the intensity clusters into individual events. We discuss the development of the algorithm, the selection, tuning and meaning of the parameters within each step, as well as its validation. Finally, we apply the algorithm to a spatiotemporal drought index, standardized vapor pressure deficit drought index (SVDI), over the continental United States (US) from 1980–2021 and show that it captures historical drought events over the continental United States and their spatiotemporal extents.
17 WIND ENERGY↗