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At least 37 records · Page 2

The Dark Energy Survey Supernova Program: an updated measurement of the Hubble constant using the inverse distance ladder

We measure the current expansion rate of the Universe, Hubble’s constant $H_0$, by calibrating the absolute magnitudes of supernovae to distances measured by baryon acoustic oscillations (BAO). This ‘inverse distance ladder’ technique provides an alternative to calibrating supernovae using nearby absolute distance measurements, replacing the calibration with a high-redshift anchor. We use the recent release of 1829 supernovae from the Dark Energy Survey spanning $0.01\lt z\lt 1.13$ anchored to the recent baryon acoustic oscillation measurements from Dark Energy Spectroscopic Instrument (DESI) spanning $0.30 \lt z_{\mathrm{eff}}\lt 2.33$. To trace cosmology to $z=0$, we use the third-, fourth-, and fifth-order cosmographic models, which, by design, are agnostic about the energy content and expansion history of the universe. With the inclusion of the higher redshift DESI-BAO data, the third-order model is a poor fit to both data sets, with the fourth-order model being preferred by the Akaike Information Criterion. Using the fourth-order cosmographic model, we find $H_0=67.19^{+0.66}_{-0.64}\mathrm{~km} \mathrm{~s}^{-1} \mathrm{~Mpc}^{-1}$, in agreement with the value found by Planck without the need to assume Flat-$\Lambda$CDM. However, the best-fitting expansion history differs from that of Planck, providing continued motivation to investigate these tensions.

79 ASTRONOMY AND ASTROPHYSICS↗

Universal bounds on CFT Distance Conjecture

For any unitary conformal field theory in two dimensions with the central charge c, we prove that, if there is a nontrivial primary operator whose conformal dimension ∆ vanishes in some limit on the conformal manifold, the Zamolodchikov distance t to the limit is infinite, the approach to this limit is exponential ∆ = exp(−αt + O(1)), and the decay rate obeys the universal bounds c−1/2 ≤ α ≤ 1. In the limit, we also find that an infinite tower of primary operators emerges without a gap above the vacuum and that the conformal field theory becomes locally a tensor product of a sigma-model in the large radius limit and a compact theory. As a corollary, we establish a part of the Distance Conjecture about gravitational theories in three-dimensional anti-de Sitter space. In particular, our bounds on α indicate that the emergence of exponentially light states is inevitable as the moduli field corresponding to t rolls beyond the Planck scale along the steepest path and that this phenomenon can begin already at the curvature scale of the bulk geometry. We also comment on implications of our bounds for gravity in asymptotically flat spacetime by taking the flat space limit and compare with the Sharpened Distance Conjecture.

AdS-CFT Correspondence↗

Structural Gating Enhances Long-Distance Light-Driven Interfacial Electron Transfer

Structural gating provides a molecular means to transfer electrons preferentially in one desired vectorial direction, a behavior needed for applications in artificial photosynthesis. At the interfaces utilized herein, visible-light absorption by a transition metal complex opens a “structural gate” by planarization of otherwise rotating phenyl rings in p-phenylene ethynylene (PE) bridge units. Planarization provides a conjugated pathway for electron flow toward a conductive oxide surface. Interfacial electron transfer to the oxide restores rotation and closes the gate to the unwanted recombination reaction. This structural gating results in nearly quantitative long-distance (>20 Å) interfacial electron transfer that occurs ~1000 times faster than transfer in the opposite direction. A comparative kinetic study of these complexes with those that contain ionic bridge units, without gating function, as a function of the applied potential and hence –ΔG° provided a physical basis for the structural gating. A small distance-dependent reorganization energy with weak electronic coupling underlies the success of this gate that enables efficient long-distance electron transfer and slow recombination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Photoinduced Electron-Transfer Distance Is Controlled by the Driving Force in Solid-State Organic Donor-Acceptor Systems

Understanding how short-range electron transfer generates photocurrent in organic solar cells and what photochemical driving force is needed to maximize efficiencies has been an immensely difficult problem. Here we show how these questions are intertwined: the driving force controls the average charge-transfer distance, skipping the shortest-range states in the optimal case. Using photoinduced absorption-detected magnetic resonance, we measure average charge-separation distances in dilute donor–acceptor blends as a function of driving force, and compare these with free charge yields measured by time-resolved microwave conductivity. We find that the largest driving forces show the shortest charge-separation distances, explaining their suppressed free-carrier generation. These results support a long-range electron-transfer model, wherein the driving force controls the initial delocalization of the electron–hole pair. The minimum driving force required for efficient charge separation (and minimal voltage losses) is ultimately set by the dielectric constant of the material.

14 SOLAR ENERGY↗

Impact of Geomagnetic Induced Current Neutral Blocking Devices on Distance Relays in Sub-transmission Networks with IBR

Geomagnetically induced currents (GICs) can flow through transmission lines during geomagnetic disturbances, such as solar flares or coronal mass ejections. These currents can cause problems like transformer saturation and equipment damage. The most common method of mitigating GICs involves installing GIC neutral blocking devices (NBDs) in transformer neutrals. However, the wide application of capacitive GIC blocking devices may have unintended adverse effects on other devices, such as distance protection relays. As the number of inverter-based resources being connected to the transmission and sub-transmission systems increases, the likelihood of a sub-transmission line protected by a distance relay connected to a transformer with NBDs is increasing. Therefore, distance relays fed by IBRs and transmission lines with GIC-NBDs must be studied. This paper studies the effect of GIC-NBDs on a 69kV sub-transmission line of various lengths fed by a 25 MVA IBR and synchronous source. This work focused on the behavior of the GIC-NBDs using the measured apparent phase-to-ground and phase-to-phase impedance calculated by the relay and the source impedance ratio (SIR) during various electrical faults.

Patel, Trupal R [Sandia National Laboratories (SNL↗

Robust COTS objective for diffraction-limited, high-NA, long front working distance imaging

We present a robust objective lens optimized for applications requiring both high numerical aperture (NA) and long front working distance imaging, comprised of all commercial-off-the-shelf (COTS) spherical singlet lenses. Unlike traditional designs that require separate collimation and refocusing stages, our approach directly converges imaged light to the back focal plane using a single lens group. Our configuration corrects spherical aberrations and efficiently collects light to achieve diffraction-limited performance across a wide range of wavelengths while simplifying alignment and assembly. Using this approach, we design and construct an example objective lens that features a long front working distance of 61 mm and a clipped NA of 0.30 (limited by an aperture in our experimental setup). We experimentally verify that it achieves monochromatic diffraction-limited resolution at wavelengths from 375 nm to 866 nm without requiring replacement of the lenses or changing the inter-lens spacings, and its performance remains robust across a 46 mm range variation in total length (by adjusting mainly the back working distance). Additionally, we develop a quantitative method to measure the field of view (FOV) using an experimentally calibrated pinhole target. Under 397 nm illumination (i.e., from 40 Ca + ion fluorescence), the objective achieves a resolution of 0.87 μm with a 540 μm FOV. This robust, all-COTS, and versatile design is well-suited for a broad range of experiments, supporting high-precision measurements and exploring quantum phenomena.

Cui, Jiafeng [Oak Ridge National Laboratory (ORNL)↗

Development of the Table of Initial Isolation and Protective Action Distances for the 2024 Emergency Response Guidebook

The transportation of hazardous materials creates numerous opportunities for the release of toxic substances into the environment, whether caused by traffic accidents, train derailments, equipment failures, or human error. Such releases can pose acute hazards to the general public and to emergency response personnel who are the first to arrive at the scene. To help first responders determine whether a shipment is potentially hazardous and decide what actions should be taken if a toxic spill does occur, the Emergency Response Guidebook (ERG) is published by the U.S. Department of Transportation (DOT), Transport Canada, and the Secretariat of Transport and Communications of Mexico; with contributions from Centro de Informaciòn Quìmica para Emergencias of Argentina. The most recent version is the 2024 edition of the ERG (ERG 2024), titled 2024 Emergency Response Guidebook (ERG2024). The ERG provides essential information about firefighting, spill response, and potential public health effects. For chemicals that are toxic by inhalation (TIH) and chemicals that produce TIH gases upon reaction with water (TIH by water reactivity or TIHWR), the ERG provides initial isolation distances (IIDs) and protective action distances (PADs). The IID defines the radius of the zone around the spill that should be accessed solely by people who are directly involved in emergency response. The PAD is the distance downwind of the source of the release within which persons should be either evacuated or sheltered in place, depending on the severity of the incident and the nature of the population (e.g., density, age, health).

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

Comparison of structurally diverse simulation models for prediction of epidemic outcomes caused by a long-distance dispersed pathogen

Long-distance dispersal (LDD) pathogens pose substantial challenges for epidemic control due to their ability to generate new infection foci at great distances. While various modeling approaches have been developed to understand and manage such outbreaks, little work has compared how models of different structures behave under shared conditions. Here, in this study, we compare four structurally distinct epidemiological models — EPIMUL, GEMF, PoPS, and Warwick — each adapted to simulate the spread of wheat stripe rust (WSR), a wind-dispersed LDD pathogen, under identical epidemiological parameters and dispersal kernel. Using data from a controlled field experiment, we evaluate the ability of each model to replicate disease prevalence under nine intervention scenarios that vary in timing and culling area. While the models differ substantially in design — ranging from spatial grid-based to network-based and raster-based frameworks — the shared dispersal kernel allowed for close alignment in their predictions. All models accurately captured general epidemic trends, particularly the strong effect of early intervention on disease suppression. We qualitatively compared their behavioral responses across scenarios and also evaluated an ensemble prediction by averaging across model outputs. Our findings highlight how integrating shared epidemiological components into distinct modeling frameworks can improve consistency and accuracy, while reinforcing the importance of early culling in managing LDD pathogen outbreaks.

Dispersal kernel↗

Hybrid bilayered vanadium oxide electrodes with large and tunable interlayer distances in lithium-ion batteries

The interlayer distances in layered electrode materials, influenced by the chemical composition of the confined interlayer regions, have a significant impact on their electrochemical performance. Chemical preintercalation of inorganic metal ions affects the interlayer spacing, yet expansion is limited by the hydrated ion radii. Herein, we demonstrate that using varying concentrations of decyltrimethylammonium (DTA + ) and cetyltrimethylammonium (CTA + ) cations in chemical preintercalation synthesis followed by hydrothermal treatment, the interlayer distance of hybrid bilayered vanadium oxides (BVOs) can be tuned between 11.1 Å and 35.6 Å. Our analyses reveal that these variations in interlayer spacing are due to different amounts of structural water and alkylammonium cations confined within the interlayer regions. Increased concentrations of alkylammonium cations not only expand the interlayer spacing but also induce local bending and disordering of the V-O bilayers. Electrochemical cycling of hybrid BVO electrodes in non-aqueous lithium-ion cells show that specific capacities decrease as interlayer regions expand, suggesting that the densely packed alkylammonium cations obstruct intercalation sites and hinder Li + ion transport. Furthermore, we found that greater layer separation facilitates the dissolution of active material into the electrolyte, resulting in rapid capacity decay during extended cycling. In conclusion, this study emphasizes that layered electrode materials require both spacious interlayer regions as well as high structural and chemical stabilities, providing guidelines for structural engineering of organic–inorganic hybrids.

25 ENERGY STORAGE↗

photoD with Rubin ’s Data Preview 1: First stellar photometric distances and faint blue star deficits

Aims. We investigate the utility of Rubin’s Data Preview 1 (DP1) for estimating stellar number density profiles across the Milky Way halo. Methods. We used stellar broad-band near-UV to near-IR ugrizy photometry released in Rubin’s DP1 to estimate distance and metallicity for blue main sequence stars brighter than r = 24 in three ~1.1 sq. deg. fields at southern Galactic latitudes. Results. Compared to TRILEGAL simulations of the Galaxy’s stellar content, we found a likely deficit of blue main sequence turn-off stars with 22 < r < 24. We interpreted this discrepancy as a signature of a steeper halo number density profile at galactocentric distances 10–50 kpc than the canonical ~1/r 3 profile assumed in TRILEGAL simulations. Conclusions. This interpretation is consistent with earlier suggestions based on observations of more luminous, but much less numerous, evolved stellar populations, along with a few pencil beam surveys of blue main sequence stars in the northern sky. These results bode well for the future Galactic halo exploration with Rubin’s Legacy Survey of Space and Time (LSST).

Galaxy: fundamental parameters↗

Modelling the impact of host galaxy dust on type Ia supernova distance measurements

Type Ia Supernovae (SNe Ia) are a critical tool in measuring the accelerating expansion of the universe. Recent efforts to improve these standard candles have focused on incorporating the effects of dust on distance measurements with SNe Ia. In this paper, we use the state-of-the-art Dark Energy Survey 5 year sample to evaluate two different families of dust models: empirical extinction models derived from SNe Ia data and physical attenuation models from the spectra of galaxies. In this work, we use realistic simulations of SNe Ia to forward-model different models of dust and compare summary statistics in order to test different assumptions and impacts on SNe Ia data. Among the SNe Ia-derived models, we find that a logistic function of the total-to-selective extinction R V best recreates the correlations between supernova distance measurements and host galaxy properties, though an additional 0.02 mag of grey scatter is needed to fully explain the scatter in SNIa brightness in all cases. These empirically derived extinction distributions are highly incompatible with the physical attenuation models from galactic spectral measurements. From these results, we conclude that SNe Ia must either preferentially select extreme ends of galactic dust distributions, or that the characterization of dust along the SNe Ia line-of-sight is incompatible with that of galactic dust distributions.

79 ASTRONOMY AND ASTROPHYSICS↗

Digital-Threat Bias and Psychological Distance: Barriers to Foundational Digital-Security Improvement

Modern life is held together by a web of digital dependencies that enable and provide delivery of critical services and functions—think the provision of utilities such as electricity and water, as well as our dependency on digital services for social and economic services (internet, communication, etc.). As this dependency grows, the complexity related to the delivery of these critical services increases as well. As complexity increases, the understanding of the risk and impact associated with potential disruption, degradation, or destruction—due to either malicious or non-malicious events of those digitally enabled functions—decreases. One potential explanation for the difficulty to 1) understand the risks faced and 2) address them appropriately and effectively is the abstractness and psychological distance assigned to “digital threat.” The complexity of these digitally enabled services creates a perceived complicatedness; as a result, digital threats are treated differently than similarly devasting (but more easily understood) kinetic or physical threats. How we categorize these threats also matters. Acts of cyber-enabled sabotage to critical infrastructure need to be defined as irregular warfare. By inadequately defining the threat, we compound the problem. Acknowledging this digital-threat bias is foundational to improving the ability to protect critical infrastructure. Using construal-level theory and psychological-distance concepts provides an intriguing starting point to address these issues, to reframe the challenges faced, and pursue more effective critical infrastructure security and defense policy.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗

Mechanisms Behind the Long‐Distance Diurnal Offshore Precipitation Propagation in Northwestern South America

Abstract Northwestern South America (NWSA) is the rainiest region on Earth, with diurnal precipitation exhibiting extensive westward offshore propagation of up to about 1,200 km in boreal spring (March‐May). The diurnal offshore precipitation propagation begins slowly (3–10 m s −1 ) near the coast of NWSA (<200 km) but accelerates significantly (∼20 m s −1 ) and shows an afternoon enhancement far from the coast (>400 km). However, the driving mechanisms behind this long‐distance precipitation propagation remain unclear. Using a new cloud tracking and classification data set, we found that mesoscale convective systems (MCSs) are the dominant precipitation contributors in the offshore region of NWSA. Cloud tracking shows that the long‐distance propagation and the afternoon enhancement of diurnal precipitation primarily originate from MCSs initiated in the early morning, either over open oceans or from the coast of Central America. Composite tendency analysis shows that MCSs initiated near the coast of Central America have significant upward cooling and moistening signals starting from the surface before initiation. Further analysis of surface diurnal perturbation fields indicates that the land breeze is the primary driving mechanism for MCS initiation. Conversely, for MCSs initiated over open oceans, a significant downward cooling signal from 400 hPa is observed ∼7 hr before initiation, corresponding to the passage of diurnal gravity waves emitted from the Andes. Additionally, our findings highlight the critical role of lower and mid‐level moisture conditions in MCS initiation, alongside the influence of gravity waves.

Hu, Jingyi [Department of Meteorology and Atmosphe↗

Distance preserving machine learning for uncertainty aware accelerator capacitance predictions

Abstract Accurate uncertainty estimations are essential for producing reliable machine learning models, especially in safety-critical applications such as accelerator systems. Gaussian process models are generally regarded as the gold standard for this task; however, they can struggle with large, high-dimensional datasets. Combining deep neural networks with Gaussian process approximation techniques has shown promising results, but dimensionality reduction through standard deep neural network layers is not guaranteed to maintain the distance information necessary for Gaussian process models. We build on previous work by comparing the use of the singular value decomposition against a spectral-normalized dense layer as a feature extractor for a deep neural Gaussian process approximation model and apply it to a capacitance prediction problem for the High Voltage Converter Modulators in the Oak Ridge Spallation Neutron Source. Our model shows improved distance preservation and predicts in-distribution capacitance values with less than 1% error.

43 PARTICLE ACCELERATORS↗

Hadronic Vacuum Polarization for the Muon 𝑔 − 2 from Lattice QCD: Long-Distance and Full Light-Quark Connected Contribution

We present results for the dominant light-quark connected contribution to the long-distance window of the hadronic vacuum polarization (HVP) contribution to the muon 𝑔 − 2 from lattice quantum chromodynamics. Specifically, with a new determination of the lattice scale on MILC’s physical-mass HISQ ensembles, using the Ω− baryon mass, we obtain a result of 𝑎$^{𝑙⁢𝑙,LD}_{𝜇}$⁡(conn) = 400.2⁢(2.3) stat ⁢(3.7) syst ⁢[4.3] total × 10 −10 . Summing this result with our recent determinations of the light-quark connected contributions to the short- and intermediate-distance windows, we obtain a subpercent precision determination of the light-quark-connected contribution to HVP of 𝑎$^{𝑙⁢𝑙}_{𝜇}$⁡(conn) = 655.2⁢(2.3) stat ⁢(3.9) syst ⁢[4.5]total×10 −10 . Finally, as a consistency check, we verify that an independent analysis of the full contribution is in agreement with the sum of individual windows. We discuss our future plans for improvements of our HVP calculations to meet the target precision of the Fermilab 𝑔 − 2 experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Polarized and unpolarized gluon PDFs: Generative machine learning applications for lattice QCD matrix elements at short distance and large momentum

Lattice quantum chromodynamics (QCD) calculations share a defining challenge by requiring a small finite range of spatial separation z between quark/gluon bilinears for controllable power corrections in the perturbative QCD factorization, and a large hadron boost p z for a successful determination of collinear parton distribution functions (PDFs). However, these two requirements make the determination of PDFs from lattice data very challenging. We present the application of generative machine learning algorithms to estimate the polarized and unpolarized gluon correlation functions utilizing short-distance data and extending the correlation up to z p z ≲ 14 , surpassing the current capabilities of lattice QCD calculations. We train physics-informed machine learning algorithms to learn from the short-distance correlation at z ≲ 0.36 fm and take the limit, p z → ∞ , thereby minimizing possible contamination from the higher-twist effects for a successful reconstruction of the polarized gluon PDF. We also expose the bias and problems with underestimating uncertainties associated with the use of model-dependent and overly constrained functional forms, such as x α ( 1 − x ) β and its variants to extract PDFs from the lattice data. We propose the use of generative machine learning algorithms to mitigate these issues and present our determination of the polarized and unpolarized gluon PDFs in the nucleon. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Phase Picking Beyond Local Distances: Where Waveform Filtering Still Matters for Deep Learning Models

Waveform filtering is a standard step in traditional seismic phase picking but often receives little attention in deep learning workflows, where models are typically trained on raw or minimally processed waveforms. Although this strategy performs well for local events, we show that performance can degrade substantially at regional distances. To address this limitation, we introduce two ways to incorporate multiband-filtered waveforms into deep learning phase pickers. The stacking approach concatenates filtered inputs along the channel dimension, while the branching approach processes each frequency band through a dedicated network branch before feature fusion. Both approaches can substantially improve performance across epicentral distances of 0° to 20°, but their effectiveness depends strongly on the selected frequency bands. Tests with multiple filter banks show that filter-bank design should be treated as part of model optimization rather than as a fixed preprocessing choice. Grad-CAM analysis of the branching model indicates that band importance varies among waveform samples and across training realizations, with only a weak overall preference for the 0.25 to 0.5 Hz band. These results show that no single filter band is consistently optimal and demonstrate that explicit feature engineering remains valuable for robust deep learning-based seismic phase picking.

58 GEOSCIENCES↗

Dose Exceedance Distance Sensitivity Based on Parametric Uncertainty

Sandia National Laboratories (SNL) collaborated with the US Nuclear Regulatory Commission's (NRC) Office of Nuclear Security and Incident Response (NSIR) and Office of Nuclear Regulatory Research (RES) to investigate the reasonable variability in the estimation of dose exceedance distances. SNL performed calculations using the MACCS code to elucidate the sensitivity of dose exceedance distances to variations in user input parameters.

61 RADIATION PROTECTION AND DOSIMETRY↗