Radial localization of electron temperature pedestal and ELM-like events using ECE measurements at Wendelstein 7-X
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Probing the Environment around GW170817 with DESI: Insights on Galaxy Group Peculiar Velocities for Standard Siren Measurements
We present a new measurement of the Hubble constant, H 0 , following the gravitational-wave event GW170817 and Dark Energy Spectroscopic Instrument (DESI) observations. A standard siren measurement with a nearby (luminosity distance ∼40 Mpc) event such as GW170817 is typically sensitive to the peculiar motion of the host galaxy owing to local dynamics. Previous measurements from this event have taken advantage of peculiar velocity measurements of nearby galaxies, including a handful of objects in the galaxy group that the host of the event, NGC 4993, has been associated with. Still, the group’s properties and NGC 4993’s membership were debated. We present DESI observations of thousands of galaxies in the vicinity of NGC 4993, resulting in 39 group galaxies and a fivefold increase in galaxies compared to previous observations, with many contributing to a peculiar velocity measurement. Examining the local dynamics, our observations support the presence of a galaxy group of which NGC 4993 is a part with a halo mass of order ∼10 13 M ⊙ . Using peculiar velocity measurements from our fundamental plane galaxy observations, we find $H_0 = 70.9^{+6.4}_{-8.5}$ km s −1 Mpc −1 . In addition, using a peculiar velocity measurement for NGC 4993 from surface brightness fluctuations in Cosmicflows-4, we find $H_0 = 73.4^{+3.3}_{-3.9}$ km s −1 Mpc −1 . We study the impact of different galaxy selection criteria on the determination of the peculiar velocity and, in turn, on the H 0 measurement. Our results demonstrate the value of multiplexed spectroscopic observations for probing the local environments of gravitational-wave events used in standard siren measurements.
Amsellem, A. J. [Carnegie Mellon University, Pitts↗
Data-Driven Event Detection of Power Systems Based on Unequal-Interval Reduction of PMU Data and Local Outlier Factor
With the deployment of phasor measurement units (PMU) and wide area measurement system (WAMS), it is feasible to have an insight into the events occurred in power systems based on measured data. Thus, a novel data-driven algorithm based on local outlier factor (LOF) is proposed in this work to detect and locate events in power systems using reduced PMU data. First, the unequal-interval reduction method is presented to reduce the scale of PMU data in sub-stations and reconstruct it in master station of WAMS, which can relieve the burden of communication systems. Then, principle component analysis (PCA)-based similarity search method is proposed to measure the differences of operation state between any two buses. Next, LOF is presented to detect the abnormal events in power systems, and employed to determine the region of the event source. Finally, six cases from the Western electricity coordinating council (WECC) 179-bus power system, a case from the South China power system (SCPS), and a case from the Guangdong power system (GDPS) are utilized to demonstrate the effectiveness of the proposed algorithm. Overall, the results show that proposed algorithm is effective and can be applied to event detection, event location, and online monitoring, which can enhance the situation awareness ability of power system operators.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
TRACER-Uncrewed Aircraft System (TRACER-UAS) Field Campaign Report
Convective processes drive the development of clouds across a variety of scales, thereby playing a central role in governing weather and climate globally. These processes help to set the stage for circulations that redistribute heat and moisture throughout the lower atmosphere, and simultaneously develop storms that supply precipitation to regions that depend on such rain events for supporting a variety of societal needs. At the same time, extreme precipitation events can result in localized flooding of low-lying areas, posing hazards to transportation and regional inhabitants, and potentially damaging structures and infrastructure. As a result, there is an inherent need to better understand the drivers and modulators of clouds and precipitation and leverage such understanding to make projections of how these important systems may evolve with a changing climate. With nearly three billion of Earth’s human inhabitants living within 200 km of a shoreline, development of such understanding is particularly important in coastal regimes. Central drivers of convective cloud development and life cycle in coastal environments include synoptic forcing, local meso- and microscale circulation regimes, microphysical evolution, and aerosol properties. Atmospheric boundary layer (ABL) development and its evolution can help drive the formation and organization of convective clouds, which then impart their own controls through dynamic processes related to latent heating and cooling (including cold-pool formation and propagation), three-dimensional radiative effects, and background environmental conditions (Fan et al. 2016). Such clouds have been contributing to record precipitation events in southeast Texas in recent years, relative to the last several decades of data from regional precipitation gauges (Fagnant et al. 2020). The greater Houston urban area has experienced particularly large increases in the frequency of extreme rainfall events, with enhanced intensity of extreme events (stretching of distribution tails) having potentially significant implications for watershed floodplain planning and mapping in greater Houston and Harris County. While the most extreme precipitation events were associated with tropical cyclones (e.g., Tropical Storm Allison and Hurricane Harvey; Blood 2014, Kao et al. 2019), strong thunderstorms can also deliver large amounts of precipitation over the area over relatively short periods.
54 ENVIRONMENTAL SCIENCES↗
Search for Continuous and Transient Neutrino Emission Associated with IceCube’s Highest-energy Tracks: An 11 yr Analysis
IceCube alert events are neutrinos with a moderate-to-high probability of having astrophysical origin. In this study, we analyze 11 yr of IceCube data and investigate 122 alert events and a selection of high-energy tracks detected between 2009 and the end of 2021. This high-energy event selection (alert events + high-energy tracks) has an average probability of ≥0.5 of being of astrophysical origin. We search for additional continuous and transient neutrino emission within the high-energy events' error regions. We find no evidence for significant continuous neutrino emission from any of the alert event directions. The only locally significant neutrino emission is the transient emission associated with the blazar TXS 0506+056, with a local significance of 3σ, which confirms previous IceCube studies. When correcting for 122 test positions, the global p-value is 0.156 and compatible with the background hypothesis. We constrain the total continuous flux emitted from all 122 test positions at 100 TeV to be below 1.2 × 10 –15 (TeV cm 2 s) –1 at 90% confidence assuming an E –2 spectrum. This corresponds to 4.5% of IceCube's astrophysical diffuse flux. Overall, we find no indication that alert events in general are linked to lower-energetic continuous or transient neutrino emission.
79 ASTRONOMY AND ASTROPHYSICS↗
Identifying Direct SP -Converted Waves Constrains Local Induced Earthquake Depths
Abstract Seismicity in southern Kansas and northern Oklahoma in the past decade has been associated with fluid injections. In southcentral Kansas, the Wellington earthquake catalog is primarily composed of local, low-magnitude events. Approximately 22% of recorded earthquakes over a 2.5 yr period exhibit a seismic phase arriving between the direct P phase and direct S phase with particle motion similar to the P wave. This intermediate phase was identified as an S to P conversion (SP phase) occurring in the sedimentary rocks instead of the hypothesized basement to sedimentary section transition. We exploit the SP-converted phases to improve the depth accuracy of shallow earthquakes and to constrain VP/VS. The revised depth calculations further confirm that these local induced earthquakes are occurring in the shallow crystalline basement, below the sedimentary section in which fluids are injected.
Geochemistry & Geophysics↗
Probing gravity and growth of structure with gravitational waves and galaxies’ peculiar velocity
The low-redshift velocity field is a unique probe of the growth of cosmic structure and gravity. Here, we propose to use distances from gravitational wave (GW) detections, in conjunction with the redshifts of their host galaxies from wide field spectroscopic surveys (e.g., DESI, 4MOST, TAIPAN), to measure peculiar motions within the local Universe. Such measurement has the potential to constrain the growth rate f σ 8 and test gravity through determination of the gravitational growth index γ , complementing constraints from other peculiar velocity measurements. We find that binary neutron star mergers with associated counterpart at z ≲ 0.2 that will be detected by the Einstein Telescope (ET) will be able to constrain f σ 8 to ~ 3 % precision after 10 years of operations when combined with galaxy overdensities from DESI and TAIPAN. If a larger network of third generation GW detectors is available (e.g., including the Cosmic Explorer), the same constraints can be reached over a shorter timescale ( ~ 5 years for a 3 detectors network). The same events (plus information from their hosts’ redshifts) can constrain γ to σ γ ≲ 0.04 . This constraint is precise enough to discern general relativity from other popular gravity models at 3 σ . This constraint is improved to σ γ ~ 0.02 – 0.03 when combined with galaxy overdensities. The potential of combining galaxies’ peculiar velocities with gravitational wave detections for cosmology highlights the need for extensive optical to near-infrared follow-up of nearby gravitational wave events, or exquisite GW localization, in the next decade.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Intermittent Criticality Multi‐Scale Processes Leading to Large Slip Events on Rough Laboratory Faults
Abstract We discuss data of three laboratory stick‐slip experiments on Westerly Granite samples performed at elevated confining pressure and constant displacement rate on rough fracture surfaces. The experiments produced complex slip patterns including fast and slow ruptures with large and small fault slips, as well as failure events on the fault surface producing acoustic emission bursts without externally‐detectable stress drop. Preparatory processes leading to large slips were tracked with an ensemble of ten seismo‐mechanical and statistical parameters characterizing local and global damage and stress evolution, localization and clustering processes, as well as event interactions. We decompose complex spatio‐temporal trends in the lab‐quake characteristics and identify persistent effects of evolving fault roughness and damage at different length scales, and local stress evolution approaching large events. The observed trends highlight labquake localization processes on different spatial and temporal scales. The preparatory process of large slip events includes smaller events marked by confined bursts of acoustic emission activity that collectively prepare the fault surface for a system‐wide failure by conditioning the large‐scale stress field. Our results are consistent overall with an evolving process of intermittent criticality leading to large failure events, and may contribute to improved forecasting of large natural earthquakes.
Geochemistry & Geophysics↗
Using convolutional neural networks to detect edge localized modes in DIII-D from Doppler backscattering measurements
In H-mode tokamak plasmas, the plasma is sometimes ejected beyond the edge transport barrier. These events are known as edge localized modes (ELMs). ELMs cause a loss of energy and damage the vessel walls. Understanding the physics of ELMs, and by extension, how to detect and mitigate them, is an important challenge. In this paper, we focus on two diagnostic methods—deuterium-alpha (D α ) spectroscopy and Doppler backscattering (DBS). The former detects ELMs by measuring Balmer alpha emission, while the latter uses microwave radiation to probe the plasma. DBS has the advantages of having a higher temporal resolution and robustness to damage. These advantages of DBS diagnostic may be beneficial for future operational tokamaks, and thus, data processing techniques for DBS should be developed in preparation. In sight of this, we explore the training of neural networks to detect ELMs from DBS data, using D α data as the ground truth. With shots found in the DIII-D database, the model is trained to classify each time step based on the occurrence of an ELM event. The results are promising. When tested on shots similar to those used for training, the model is capable of consistently achieving a high f1-score of 0.93. Furthermore, this score is a performance metric for imbalanced datasets that ranges between 0 and 1. We evaluate the performance of our neural network on a variety of ELMs in different high confinement regimes (grassy ELM, RMP mitigated, and wide-pedestal), finding broad applicability. Beyond ELMs, our work demonstrates the wider feasibility of applying neural networks to data from DBS diagnostic.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Early Alarm: Robust Event Analysis for Power Systems using 1-D Fully Convolutional Network
This work presents a novel deep learning model for early, accurate, and robust detection, recognition, and temporal localization of multi-type events in large-scale power systems. The proposed method develops a unified 1-D fully convolutional network (FCN) model that takes time series of raw frequency signals measured from a power system as input, extracts distinguishing features, and predicts at every temporal point in the time series if an event is happening and what the type of the event is. Compared to existing methods, the proposed model eliminates the necessity for hand-crafted feature extraction or complicated data pre-processing, can flexibly handle input signals of arbitrary length, and precisely infer the event occurrence time. Most importantly, the model is intentionally trained with incomplete patterns, such that it is more robust to partial features of an event which is common in real-world online recognition, resulting in early alarm for power system failures. Extensive experimental results demonstrate that the proposed method achieves superior performance to the state-of-the-art, and also shows strong robustness to noise and system oscillations.
Li, Chengcheng↗
Modulations of Atmospheric River Climatology by the Stratospheric Quasi‐Biennial Oscillation
Abstract This study reveals the significant Quasi‐Biennial Oscillation (QBO) influences on the seasonal atmospheric river (AR) climatology around the globe. The North Pacific (NP) AR climatology in the boreal winter to early fall seasons in a QBO easterly (QBOE) phase is systematically shifted poleward compared with those in a QBO westerly (QBOW) phase, and such difference peaks in the local late spring season. We also find the similar poleward shift for the AR climatology over the South Pacific (SP) in the austral winter seasons in the QBOE phase. A significant equatorward shift and an overall enhancement of the AR climatology over the SP are observed in the QBOE phase during local spring and summer seasons, respectively. The QBO impacts on the AR climatology over the Atlantic Ocean are less organized. Strong QBO impacts exist in almost all seasons for the North Atlantic AR but only in the austral spring season for the South Atlantic AR. These QBO modulations of the AR climatology over the ocean basins also change the season‐mean AR frequencies around coastal regions, suggesting significant QBO impacts on the local land‐falling AR events. The QBO modulations of the seasonal background mean states and the MJO‐teleconnections are two potential mechanisms mostly over the north hemisphere. The QBOE modulation of the Madden‐Julian Oscillation (MJO)‐teleconnection over the northern hemisphere is asymmetric between the MJO convection over the Indian Ocean and that over the Pacific Ocean, which is the key to explain the QBO influences on the AR activity on the seasonal timescale.
Huang, Kai [U.S. National Science Foundation Natio↗
What Technical Choices Matter to Characterize Heat Wave and Cold Snap Events in Support of Bulk Power Grid Reliability Studies?
Extreme weather events, such as Heat Waves (HW) and Cold Snaps (CS), pose significant risks to the power grid. The United States (U.S.) Federal Energy Regulatory Commission Order No. 896 mandates regional coordination standards that account for extreme thermal events. However, the lack of a universal definition for extreme thermal events may lead to inconsistent compliance efforts among neighboring entities, undermining the reliability of the transmission system. This study directly addresses this challenge by systematically evaluating how varying technical choices in defining HW and CS fundamentally impact the characterization and ranking of extreme events for power grid reliability studies. We used 12 event definitions and multiple temperature spatial aggregation approaches to construct historical (1980–2024) regional extreme thermal event libraries across North American Electric Reliability Corporation (NERC) subregions in the conterminous U.S. We examined the sensitivity of event characteristics (e.g., duration, frequency, intensity, and spatial coverage) to different definitions. While some definitions produced similar libraries and top event rankings, definitions based on moving-window-averaged temperatures yielded markedly different characteristics. Spatial aggregation methods had minimal impact on heat wave or cold snap intensity, frequency and duration but significantly influenced spatial coverage. The top events identified across different aggregation methods were consistent, but their ranking order varied. These findings offer critical insights for characterizing and selecting extreme thermal events and for supporting local and cross-regional coordination as required by reliability standards.
Wan, Heng [Pacific Northwest National Laboratory (↗
Anomalous temperature dependence of elastic limit in metallic glasses
Abstract Understanding the atomistic mechanisms of inelastic deformation in metallic glasses (MGs) remains challenging due to their amorphous structure, where local carriers of plasticity cannot be easily defined. Using molecular dynamics (MD) simulations, we analyzed the onset of inelastic deformation in CuZr MGs, specifically the temperature dependence of the elastic limit, in terms of localized shear transformation (ST) events. We find that although the ST events initiate at lower strain with increasing temperature, the elastic limit increases with temperature in certain temperature ranges. We explain this anomalous behavior through the framework of an energy-strain landscape (ESL) constructed from high-throughput strain-dependent energy barrier calculations for the ST events identified in the MD simulations. The ESL reveals that the anomalous behavior is caused by the transition of ST events from irreversible to reversible with increasing temperature. An analytical formulation is developed to predict this transition and the temperature dependence of the elastic limit.
36 MATERIALS SCIENCE↗
Interpreting AI for fusion: An application to plasma profile analysis for tearing mode stability
Artificial intelligence models have demonstrated strong predictive capabilities for various instabilities in fusion devices such as Tokamaks, including tearing modes (TM), edge localized modes, and disruptive events, but their opaque nature raises concerns about safety and trustworthiness when applied to fusion power plants. Here, we present a physics-based interpretation framework using a TM prediction model as a demonstration that is validated through a dedicated DIII-D TM avoidance experiment. By applying Shapley analysis, we identify how profiles such as rotation, temperature, and density contribute to the model's prediction of TM stability. Our analysis shows that in our experimental scenario, core electron temperature and rotation peaking play the primary role in TM stability, while density changes have smaller effects on stability. We show that off-axis ion temperature stabilizes TMs, suggesting that off-axis neutral beam heating can further stabilize this scenario. This work presents a generalizable ML-based event prediction methodology, from training to physics-driven interpretation, bridging the gap between physics understanding and opaque ML models.
Farre-Kaga, Hiro J. [Princeton Univ., NJ (United S↗
Emergent facilitation and glassy dynamics in supercooled liquids
In supercooled liquids, dynamical facilitation refers to a phenomenon where microscopic motion begets further motion nearby, resulting in spatially heterogeneous dynamics. This is central to the glassy relaxation dynamics of such liquids, which show super-Arrhenius growth of relaxation timescales with decreasing temperature. Despite the importance of dynamical facilitation, there is no theoretical understanding of how facilitation emerges and impacts relaxation dynamics. Here, we present a theory that explains the microscopic origins of dynamical facilitation. We show that dynamics proceeds by localized bond-exchange events, also known as excitations, resulting in the accumulation of elastic stresses with which new excitations can interact. At low temperatures, these elastic interactions dominate and facilitate the creation of new excitations near prior excitations. Using the theory of linear elasticity and Markov processes, we simulate a model, which reproduces multiple aspects of glassy dynamics observed in experiments and molecular simulations, including the stretched exponential decay of relaxation functions, the super-Arrhenius behavior of relaxation timescales as well as their two-dimensional finite-size effects. The model also predicts the subdiffusive behavior of the mean squared displacement (MSD) on short, intermediate timescales. Furthermore, we derive the phonon contributions to diffusion and relaxation, which when combined with the excitation contributions produce the two-step relaxation processes, and the ballistic–subdiffusive–diffusive crossover MSD behaviors commonly found in supercooled liquids.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Characterizing gravitational wave detector networks: from A # to cosmic explorer
Gravitational-wave observations by the laser interferometer gravitational-wave observatory (LIGO) and Virgo have provided us a new tool to explore the Universe on all scales from nuclear physics to the cosmos and have the massive potential to further impact fundamental physics, astrophysics, and cosmology for decades to come. In this paper we have studied the science capabilities of a network of LIGO detectors when they reach their best possible sensitivity, called A # , given the infrastructure in which they exist and a new generation of observatories that are factor of 10 to 100 times more sensitive (depending on the frequency), in particular a pair of L-shaped cosmic explorer (CE) observatories (one 40 km and one 20 km arm length) in the US and the triangular Einstein telescope with 10 km arms in Europe. We use a set of science metrics derived from the top priorities of several funding agencies to characterize the science capabilities of different networks. The presence of one or two A # observatories in a network containing two or one next generation observatories, respectively, will provide good localization capabilities for facilitating multimessenger astronomy (MMA) and precision measurement of the Hubble parameter. Two CE observatories are indispensable for achieving precise localization of binary neutron star events, facilitating detection of electromagnetic counterparts and transforming MMA. Their combined operation is even more important in the detection and localization of high-redshift sources, such as binary neutron stars, beyond the star-formation peak, and primordial black hole mergers, which may occur roughly 100 million years after the Big Bang. The addition of the Einstein Telescope to a network of two CE observatories is critical for accomplishing all the identified science metrics including the nuclear equation of state, cosmological parameters, the growth of black holes through cosmic history, but also make new discoveries such as the presence of dark matter within or around neutron stars and black holes, continuous gravitational waves from rotating neutron stars, transient signals from supernovae, and the production of stellar-mass black holes in the early Universe. For most metrics the triple network of next generation terrestrial observatories are a factor 100 better than what can be accomplished by a network of three A # observatories.
Einstein telescope↗
Generation of a chromosome-scale genome assembly of the insect-repellent terpenoid-producing Lamiaceae species, Callicarpa americana
Plants exhibit wide chemical diversity due to the production of specialized metabolites that function as pollinator attractants, defensive compounds, and signaling molecules. Lamiaceae (mints) are known for their chemodiversity and have been cultivated for use as culinary herbs, as well as sources of insect repellents, health-promoting compounds, and fragrance. We report the chromosome-scale genome assembly of Callicarpa americana L. (American beautyberry), a species within the early-diverging Callicarpoideae clade of Lamiaceae, known for its metallic purple fruits and use as an insect repellent due to its production of terpenoids. Using long-read sequencing and Hi-C scaffolding, we generated a 506.1-Mb assembly spanning 17 pseudomolecules with N50 contig and N50 scaffold sizes of 7.5 and 29.0 Mb, respectively. In all, 32,164 genes were annotated, including 53 candidate terpene synthases and 47 putative clusters of specialized metabolite biosynthetic pathways. Our analyses revealed 3 putative whole-genome duplication events, which, together with local tandem duplications, contributed to gene family expansion of terpene synthases. Kolavenyl diphosphate is a gateway to many of the bioactive terpenoids in C. americana; experimental validation confirmed that CamTPS2 encodes kolavenyl diphosphate synthase. Syntenic analyses with Tectona grandis L. f. (teak), a member of the Tectonoideae clade of Lamiaceae known for exceptionally strong wood resistant to insects, revealed 963 collinear blocks and 21,297 C. americana syntelogs. Access to the C. americana genome provides a road map for rapid discovery of genes encoding plant-derived agrichemicals and a key resource for understanding the evolution of chemical diversity in Lamiaceae.
59 BASIC BIOLOGICAL SCIENCES↗
Intrinsic nonlocality of spin- and polarization-resolved probabilities in strong-field quantum electrodynamics
Spin and polarization are central to precision tests of fundamental physics and for interpreting radiation from astrophysical sources and ultraintense laser-matter experiments. Here, focusing on the fundamental process of nonlinear Compton scattering, we demonstrate that a key assumption underlying current strong-field quantum electrodynamics models, i.e., that emission can be treated as an instantaneous random event sampled from a local differential rate, is inconsistent once emission angles, electron spin, and/or photon polarization are resolved. Namely, even in strictly constant and uniform fields , the resulting fully differential distribution is sign indefinite, yielding negative inferred probabilities. The physical reason is that the photon emission probability builds up over a finite length of the electron trajectory, the formation region, during which the electron direction changes by roughly the same small angle that defines the radiation cone. Therefore, we put forward a new method where we integrate over this formation region analytically to obtain a physically consistent electron spin and photon polarization model. We show that the implementation of our model is compatible with existing Monte Carlo and particle-in-cell workflows. Simulations of a GeV-class electron-laser collision accessible at current petawatt facilities and of emission in a pulsarlike magnetic field are shown to reveal spin and polarization patterns that differ even qualitatively from state-of-the-art local models. In particular, our new model predicts substantial angle-dependent circular photon polarization where the well-known collinear-emission approach yields none, and a pronounced helicity bias in the recoiling electrons absent from current predictions. These findings have direct implications for upcoming strong-field QED experiments and for interpreting polarized radiation from extreme astrophysical environments.
astrophysical electromagnetic fields↗