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DOE OSTI2023

Measuring the giant radio galaxy length distribution with the LoTSS

Many massive galaxies launch jets from the accretion disk of their central black hole, but only ~10 3 instances are known in which the associated outflows form giant radio galaxies (GRGs, or giants): luminous structures of megaparsec extent that consist of atomic nuclei, relativistic electrons, and magnetic fields. Large samples are imperative to understanding the enigmatic growth of giants, and recent systematic searches in homogeneous surveys constitute a promising development. For the first time, it is possible to perform meaningful precision statistics with GRG lengths, but a framework to do so is missing. We measured the intrinsic GRG length distribution by combining a novel statistical framework with a LOFAR Two-metre Sky Survey (LoTSS) sample of freshly discovered giants. In turn, this allowed us to answer an array of questions on giants. For example, we can now assess how rare a 5 Mpc giant is compared with one of 1 Mpc, and how much larger – given a projected length – the corresponding intrinsic length is expected to be. Notably, we can now also infer the GRG number density in the Local Universe. We assumed the intrinsic GRG length distribution to be Paretian (i.e. of power-law form) with tail index ξ, and predicted the observed distribution by modelling projection and selection effects. To infer ξ, we also systematically searched the LoTSS for hitherto unknown giants and compiled the largest catalogue of giants to date. We show that if intrinsic GRG lengths are Pareto distributed with index ξ, then projected GRG lengths are also Pareto distributed with index ξ. Selection effects induce curvature in the observed projected GRG length distribution: angular length selection flattens it towards the lower end, while surface brightness selection steepens it towards the higher end. We explicitly derived a GRG’s posterior over intrinsic lengths given its projected length, laying bare the ξ dependence. We also discovered 2060 giants within LoTSS DR2 pipeline products; our sample more than doubles the known population. Spectacular discoveries include the largest, second-largest, and fourth-largest GRG known (l p = 5.1 Mpc, l p = 5.0 Mpc, and l p = 4.8 Mpc), the largest GRG known hosted by a spiral galaxy (l p = 2.5 Mpc), and the largest secure GRG known beyond redshift 1 (l p = 3.9 Mpc). We increase the number of known giants whose angular length exceeds that of the Moon from 10 to 23; among the discoveries is the angularly largest known radio galaxy in the Northern Sky, which is also the angularly largest known GRG ($\phi$ = 2°). Combining theory and data, we determined that intrinsic GRG lengths are well described by a Pareto distribution, and measured the index ξ = –3.5 ± 0.5. This implies that, given its projected length, a GRG’s intrinsic length is expected to be just 15% larger. Finally, we determined the comoving number density of giants in the Local Universe to be n GRG = 5 ± 2(100 Mpc) –3 . We developed a practical mathematical framework that elucidates the statistics of giant radio galaxy lengths. Through a LoTSS search, we also discovered 2060 new giants. By combining both advances, we determined that intrinsic GRG lengths are well described by a Pareto distribution with index ξ = –3.5 ± 0.5, and that giants are truly rare in a cosmological sense: most clusters and filaments of the Cosmic Web are not currently home to a giant. Thus, our work yields new observational constraints for analytical models and simulations featuring radio galaxy growth.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Seeing through noise in power laws

Despite widespread claims of power laws across the natural and social sciences, evidence in data is often equivocal. Modern data and statistical methods reject even classic power laws such as Pareto’s law of wealth and the Gutenberg–Richter law for earthquake magnitudes. We show that the maximum-likelihood estimators and Kolmogorov–Smirnov (K-S) statistics in widespread use are unexpectedly sensitive to ubiquitous errors in data such as measurement noise, quantization noise, heaping and censorship of small values. This sensitivity causes spurious rejection of power laws and biases parameter estimates even in arbitrarily large samples, which explains inconsistencies between theory and data. We show that logarithmic binning by powers of λ > 1 attenuates these errors in a manner analogous to noise averaging in normal statistics and that λ thereby tunes a trade-off between accuracy and precision in estimation. Binning also removes potentially misleading within-scale information while preserving information about the shape of a distribution over powers of λ, and we show that some amount of binning can improve sensitivity and specificity of K-S tests without any cost, while more extreme binning tunes a trade-off between sensitivity and specificity. We therefore advocate logarithmic binning as a simple essential step in power-law inference.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Seeing through noise in power laws

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Logarithmic Resilience Risk Metrics That Address the Huge Variations in Blackout Cost

Resilience risk metrics must address the customer cost of the largest blackouts of greatest impact. However, there are huge variations in blackout cost in observed distribution utility data that make it impractical to properly estimate the mean large blackout cost and the corresponding risk. These problems are caused by the heavy tail observed in the distribution of customer costs. To solve these problems, we propose resilience metrics that describe large blackout risk using the mean of the logarithm of the cost of large-cost blackouts, the slope index of the heavy tail, and the frequency of large-cost blackouts.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Spectral Properties of Globally Distributed ENA Fluxes across Diverse Regions of the Heliosphere

This study analyzes energetic neutral atom (ENA) spectral properties across distinct regions of globally distributed flux (GDF) sky maps, using Interstellar Boundary Explorer data from a full solar cycle, corrected for time dispersion. By time-shifting the data to the heliosheath using GDF source distances from D. B. Reisenfeld et al., we achieve a more accurate representation of heliosheath GDF energy spectra. We quantify ENA spectral characteristics, heliosheath line-of-sight-integrated proton pressure, and heliosheath proton temperature, comparing these to solar wind properties at 1 au and interplanetary scintillation-derived solar wind data. Our findings show that the spectral index is generally anticorrelated with heliosheath proton temperature and pressure, except in the central tail, where a partial positive correlation is observed. The lowest spectral index values occur when high-latitude heliosheath regions are dominated by fast solar wind from polar coronal holes. The south pole exhibits the flattest energy spectra due to plasma heating from both fast solar wind and a late-2014 pressure pulse. The central tail shows shorter variability (5–6 yr) for spectral index and heliosheath proton temperature, while proton pressure follows the 11 yr solar cycle. Most spectral shapes exhibit a “knee” distribution, peaking during solar maximum, with an “ankle” shape observed only at the south pole during solar cycle transitions. Asymmetry in proton pressure in the lobes is driven by the draping effect of the local interstellar magnetic field. This study provides insights into the energetic properties of GDF across the heliosphere, enhancing our understanding of the heliospheric environment.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Learning interpretable surface elasticity properties from bulk properties via neural network equation learners

Surface elasticity is central to understanding the mechanics and stability of surfaces and interfaces. It is characterized by quantities such as surface tension, residual surface stress, and surface stiffness. However their analytical expressions are typically difficult to derive from atomistic data, and depend strongly on modeling choices. This work presents a neural network-based equation learner which combines customized activation functions and connection-based pruning to discover parsimonious, closed-form equations for surface elasticity from atomistic simulations. Applying the method to seven face-centered cubic (FCC) metals, our equation learner uncovers interpretable equations that describe both low-Miller index and high-Miller index surface properties, capturing long-tail property distributions accurately. The discovered expressions are decoupled into two components: a universal, geometry-driven orientation function, and material-specific baseline coefficients. We find that lower-order properties such as surface tension are fundamentally geometry dependent, while higher-order properties such as surface stress and elasticity show more complex geometry and material dependence. We also relate material dependent coefficients to bulk properties, forming a clear map from bulk material properties to surface elasticity. Overall, this approach demonstrates that interpretable neurosymbolic machine learning can bridge the gap between atomistic simulations and physical laws, enabling the discovery of generalizable structure–property relationships for materials science phenomena such as surface elasticity.

Equation learning↗

DOE OSTI2023

MeerKAT view of the dancing ghosts – peculiar galaxy pair PKS 2130−538 in Abell 3785

ABSTRACT We present MeerKAT L-band (886–1682 MHz) observations of the extended radio structure of the peculiar galaxy pair PKS 2130−538 known as the ‘Dancing Ghosts’. The complex of bending and possibly interacting jets and lobes originate from two active galactic nuclei hosts in the Abell 3785 galaxy cluster, one of which is the brightest cluster galaxy. The radio properties of the PKS 2130−538 – flux density, spectral index, and polarization – are typical for large, bent-tail galaxies. We also investigate a number of thin extended low surface brightness filaments originating from the lobes. South-east from the Dancing Ghosts, we detect a region of low surface brightness emission that has no clear origin. While it could originate from the Abell 3785 radio halo, we investigate the possibility that it is associated with the two PKS 2130−538 hosts. We find no evidence of interaction between the two PKS 2130−538 hosts.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Ion Acceleration and the Development of a Power-law Energy Spectrum in Magnetic Reconnection

How charged particles are accelerated efficiently and form a power-law energy spectrum in magnetic reconnection is a problem that is not well understood. In a previous paper, it was shown that the electron Kelvin–Helmholtz instability (EKHI) in force-free magnetic reconnection generates fast-expanding vortices that can accelerate electrons in a few tens of ion gyroperiods (less than 1 ms in the solar corona) to form a power-law energy distribution. In this paper, we present a particle-in-cell (PIC) simulation study of ion acceleration in force-free magnetic reconnection in the presence of the EKHI-induced turbulence. We find that ions are not significantly accelerated by the EKHI-induced stochastic electric field until the magnetic vortices expand to sizes comparable to the ion gyroradius. The Alfvén waves generated by the EKHI couple with the magnetic vortices, leading to resonance between the ions inside the magnetic vortices and Alfvén waves and enhanced ion heating. The induced Alfvén wave resonance results in a broken power-law energy spectrum with a breakpoint at $\sim {m}_{i}{v}_{A}^{2}$, where v A is the Alfvén velocity. Here, we show that the process that forms the nonthermal tail is a second-order Fermi mechanism and the mean spectral index is α = (1 + 4 a 2 D/R) /2, where D is the spatial scale of the inductive electric field, R is that of vortices, and a = B g /B 0 , with ratio of guide field B g and asymptotic B 0 .

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2022

Early-type dwarf galaxies in the local universe. Evidence of ex situ growth

We report the discovery of a rare early-type dwarf galaxy (dE), SDSS J125651.47+163024.2 (hereafter, dE1256), possessing a tidal feature that was likely built up by accretion of an even smaller dwarf galaxy. dE1256 is located in a nearly isolated environment, at the outskirt of the Virgo cluster. A detailed morphological examination reveals that the accreted stellar population is mainly deposited in the outer part of dE1256, where the tidal tail is most prominent. The inner part of dE1256 is perfectly modelled with a simple Sérsic function of index n = 0.63 and half-light radius R h = 0.6 kpc, but in contrast, the entire galaxy has a size of R h = 1.2 kpc. The mass ratio between the host and the putative accreted dwarf galaxy is calculated to be 5:1, assuming that the observed two components, inner Sérsic and outer tidal tail residual, represent the host’s and accreted galaxy’s stellar populations, respectively. We suggest that while the accretion contributes only 20 per cent of the overall stellar population, the size of dE1256 grew by a factor of two via the accretion event. Our results provide, for the first time, strong observational evidence that a dE is undergoing a two-phase growth, a common phenomenon for massive galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Quantifying Distribution System Resilience From Utility Data: Large Event Risk and Benefits of Investments

We focus on blackouts in electric distribution systems that have a large cost to customers. To quantify resilience to these events, we show how to calculate risk metrics from the historical outage data routinely collected by utilities' outage management systems. Risk is defined using a customer cost exceedance curve. The exceedance curve has a heavy tail that implies large fluctuations in large blackout costs, and this makes estimating the mean large cost in the usual way impractical. To avoid this problem, we use new resilience metrics describing the large event risk; these metrics are the probability of a large cost event, the annual log cost resilience index, and the average of the logarithm of the cost of large-cost events or the slope magnitude of the tail on a log–log exceedance curve. Resilience can be improved by planned investments to upgrade system components or speed up restoration. The benefits that these investments would have had if they had been made in the past can be quantified by “rerunning history” with the effects of the investment included, and then recalculating the large event risk to find the improvement in resilience. An example using utility data shows a 2% reduction in the probability of a large cost event due to 10% wind hardening and 6%–7% reduction due to 10% faster restoration in two different areas of a distribution utility. This new data-driven approach to quantify resilience and resilience investments is realistic and much easier to apply than complicated approaches based on modeling all the phases of resilience. Moreover, an appeal to improvements to past lived experience may well be persuasive to customers and regulators in making the case for resilience investments.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Unveiling mechanisms and onset threshold of humping in high-speed laser welding

The fabrication of fuel cells relies on a rapid laser welding process. However, challenges arise with the occurrence of humping when the welding speed surpasses a critical threshold, which poses difficulties in achieving a smooth surface finish and a consistent weld strength. This study aims to elucidate the humping mechanisms by analyzing the morphology of molten pool and the characteristics of melt flow at varying welding speeds via in situ synchrotron high-speed X-ray imaging and computational fluid dynamics simulations. Our findings indicate that the short keyhole rear wall, the high backward melt velocity, and the prolonged tail of molten pool are the primary factors contributing to the onset of humping. Furthermore, a dimensionless humping index (π h ) was introduced, which successfully captured the onset threshold of humping across different literatures. This index not only provides a quantitative description of the humping formation tendency but also serves as a valuable tool for optimizing the laser welding process.

42 ENGINEERING↗

DOE OSTI2022

Statistical properties of the population of the Galactic centre filaments – II. The spacing between filaments

ABSTRACT We carry out a population study of magnetized radio filaments in the Galactic centre using MeerKAT data by focusing on the spacing between the filaments that are grouped. The morphology of a sample of 43 groupings containing 174 magnetized radio filaments are presented. Many grouped filaments show harp-like, fragmented cometary tail-like, or loop-like structures in contrast to many straight filaments running mainly perpendicular to the Galactic plane. There are many striking examples of a single filament splitting into two prongs at a junction, suggestive of a flow of plasma along the filaments. Spatial variations in spectral index, brightness, bending, and sharpening along the filaments indicate that they are evolving on a 105−6-yr time-scale. The mean spacings between parallel filaments in a given grouping peaks at ∼16 arcsec. We argue by modeling that the filaments in a grouping all lie on the same plane and that the groupings are isotropically oriented in 3D space. One candidate for the origin of filamentation is interaction with an obstacle, which could be a compact radio source, before a filament splits and bends into multiple filaments. In this picture, the obstacle or sets the length scale of the separation between the filaments. Another possibility is synchrotron cooling instability occurring in cometary tails formed as a result of the interaction of cosmic ray driven Galactic centre outflow with obstacles such as stellar winds. In this picture, the mean spacing and the mean width of the filaments are expected to be a fraction of a parsec, consistent with observed spacing.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2023

Four Years of Type Ia Supernovae Observed by TESS: Early-time Light-curve Shapes and Constraints on Companion Interaction Models

Abstract We present 307 type Ia supernova (SN) light curves from the first 4 yr of the Transiting Exoplanet Survey Satellite mission. We use this sample to characterize the shapes of the early-time light curves, measure the rise times from first light to peak, and search for companion star interactions. Using simulations, we show that light curves must have noise <10% of the peak flux to avoid biases in the early-time light-curve shape, restricting our quantitative analysis to 74 light curves. We find that the mean power-law index t β 1 of the early-time light curves isβ 1 = 1.93 ± 0.57, and the mean rise time to peak is 15.7 ± 3.5 days. The underlying population distribution forβ 1 may instead consist of a Gaussian component with mean 2.29, width 0.34, and a long tail extending to values less than 1.0. We find that the data can rarely distinguish between models with and without companion interaction models. Nevertheless, we find three high-quality light curves that tentatively prefer the addition of a companion interaction model, but the statistical evidence for the companion interactions is not robust. We also find two SNe that disfavor the addition of a companion interaction model to a curved power-law model. Taking the 74 SNe together, we calculate 3σupper limits on the presence of companion signatures to control for orientation effects that can hide companions in individual light curves. Our results rule out common progenitor systems with companions having Roche lobe radii >31R ⊙ (separations >5.7 × 10 12 cm, 99.9% confidence level) and disfavor companions having Roche lobe radii >10R ⊙ (separations >1.9 × 10 12 cm, 95% confidence level). Lastly, we discuss the implications of our results for the intrinsic fraction of single degenerate progenitor systems.

Astronomy & Astrophysics↗

DOE OSTI2026

From observation to replication: machine-learning-driven quantification and replication of fine-scale fish kinematics and behavior

Long-term quantification of fish behavior is essential for aquatic ecology, wildlife telemetry, and biomechanical device development. However, the observation duration required to obtain reliable behavioral and kinematic metrics remains unclear, and few tools exist to physically reproduce natural swimming motion for controlled experimentation. We address these challenges by developing a generalizable framework that models behavioral reliability (Spearman–Brown reliability index) as a function of observation duration and derives metric-specific monitoring thresholds. Using juvenile white sturgeon (Acipenser transmontanus) as a case study, we demonstrate that the minimum duration needed for reliable estimates varies substantially across kinematic features: to exceed a reliability of 0.8, total distance traveled requires 12 days, average curvature (mm?¹) 15 days, tail-beat frequency (Hz) 8 days, and average speed (body length/s) 17 days. We further bridge digital analysis and physical testing by developing a hardware-in-the-loop simulator that reconstructs machine-learning-derived swimming kinematics with high fidelity (correlation coefficient 0.98–0.99, RMSE 1.22–1.27 mm over a 5-minute segment). This platform enables realistic, repeatable motion stimuli for evaluating aquatic sensing technologies and bio-integrated devices under controlled conditions. Together, these contributions provide a scalable approach for designing long-term behavioral studies and a data-driven connection between ecological observation and robotic experimentation.

Hwang, SungJoo↗

DOE OSTI2024

Magnetotail Variability During Magnetospheric Substorms

Abstract In this work, we present a statistical study of substorms covering a five‐year period 2016–2020. Substorm phases were identified from time series of the SuperMAG AL (SML) index using a list of 5,077 previously identified substorm onsets, the SML peak value marking transition from expansion to recovery phase, and the recovery identified as return to activity less than −100 nT in the SML index. Magnetic field observations from THEMIS, RBSP, and MMS missions were used to study the magnetotail characteristics during the substorm evolution. A superposed epoch analysis indicates that the substorm onset occurs almost simultaneously with a few minutes of uncertainty throughout the magnetotail, ranging from geostationary orbit to 20 RE. The onset in the transition region precedes the ground onset by a few minutes. The peak SML time coincides with the peak of the outer transition region Δ B Z , which suggests that the field‐aligned currents driving the SML activity arise from the outer transition region. Analysis of 2D maps of the tail magnetic field shows that the magnetotail current changes are limited to the center of the tail within | Y | < 10 R E . The substorm recovery is fastest in the inner transition region and lasts longer when moving further out. We did not find major asymmetries in the substorm signatures associated with IMF B Y or B Z .

Kumar, S.↗

DOE OSTI2024

Defining blood hematology reference values in female pig-tailed macaques ( Macaca nemestrina ) using the Isolation Forest algorithm

Background: Pig-tailed macaques (PTMs) are commonly used as preclinical models to assess antiretroviral drugs for HIV prevention research. Drug toxicities and disease pathologies are often preceded by changes in blood hematology. To better assess the safety profile of pharmaceuticals, we defined normal ranges of hematological values in PTMs using an Isolation Forest (iForest) algorithm. Methods: Eighteen female PTMs were evaluated. Blood was collected 1–24 times per animal for a total of 159 samples. Complete blood counts were performed, and iForest was used to analyze the hematology data to detect outliers. Results: Median, IQR, and ranges were calculated for 13 hematology parameters. From all samples, 22 outliers were detected. These outliers were excluded from the reference index. Conclusions: Using iForest, we defined a normal range for hematology parameters in female PTMs. This reference index can be a valuable tool for future studies evaluating drug toxicities in PTMs.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

The Nature of LoBAL QSOs. II. HST/WFC3 Observations Reveal Host Galaxies Dominated by Mergers

Low-ionization broad absorption line QSOs (LoBALs) are suspected to be merging systems in which extreme, active galactic nucleus-driven outflows have been triggered. Whether or not LoBALs are uniquely associated with mergers, however, has yet to be established. To characterize the morphologies of LoBALs, we present the first high-resolution morphological analysis of a volume-limited sample of 22 Sloan Digital Sky Survey (SDSS)-selected LoBALs at 0.5 < z < 0.6 from Hubble Space Telescope Wide Field Camera 3 observations. Host galaxies are resolved in 86% of the systems in F125W, which is sensitive to old stellar populations, while only 18% are detected in F475W, which traces young, unobscured stellar populations. Signs of recent or ongoing tidal interaction are present in 45%–64% of the hosts, including double nuclei, tidal tails, bridges, plumes, shells, and extended debris. Ongoing interaction with a companion is apparent in 27%-41% of the LoBALs, with as much as 1/3 of the sample representing late-stage mergers at projected nuclear separations <10 kpc. Detailed surface brightness modeling indicates that 41% of the hosts are bulge dominated while only 18% are disks. We discuss trends in various properties as a function of merger stage and parametric morphology. Notably, mergers are associated with slower, dustier winds than those seen in undisturbed/unresolved hosts. Our results favor an evolutionary scenario in which quasar-level accretion during various merger stages is associated with the observed outflows in low-z LoBALs. We discuss differences between LoBALs and FeLoBALs and show that selection via the traditional balnicity index would have excluded all but one of the mergers.

Quasars↗

DOE OSTI2022

Evidence for Impact of Galaxy Mergers on Stellar Kinematics of Early-type Galaxies

We provide observational evidence that galaxy mergers significantly affect stellar kinematics of early-type galaxies (ETGs) such as specific stellar angular momentum within the half-light radius (${\lambda }_{{R}_{e}}$) and kinematic misalignment (ψ mis ), using MaNGA integral field unit spectroscopic data that are in the Stripe 82 region of the Sloan Digital Sky Survey. In this study, tidal features around ETGs, which are detected in deep coadded images, are used as direct evidence for mergers that occurred recently. In the case of ETGs that do not have dust lanes, ${\lambda }_{{R}_{e}}$ is lower in ETGs with tidal features than in those without tidal features (median ${\lambda }_{{R}_{e}}$: 0.21 versus 0.39) in all stellar mass and Sérsic index ranges except the most massive bin, so that the fraction of ETGs with tidal features in slow rotators is more than twice as large as that in fast rotators (42% versus 18%). Moreover, ETGs with tidal features have larger ψ mis than those without tidal features (mean ψ mis : 28° versus 15°). By contrast, ETGs with dust lanes are fast rotators, and ETGs with both dust lanes and tidal features have the highest ${\lambda }_{{R}_{e}}$ (median ${\lambda }_{{R}_{e}}$: 0.59) among all ETG categories. In addition, ETGs with dust lanes have small ψ mis regardless of the existence of tidal features (Ψ mis <7$^{°}_{.}$5). Our results can be explained if mergers with different gas fractions generate merger remnants that have different kinematic properties.

79 ASTRONOMY AND ASTROPHYSICS↗