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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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67 records · Page 4

Discovery of a z ∼ 0.8 ultra steep spectrum radio halo in the MeerKAT-South Pole Telescope Survey

Radio haloes are diffuse synchrotron sources that trace the turbulent intracluster medium (ICM) of galaxy clusters. However, their origin remains unknown. Two main formation models have been proposed: the hadronic model, in which relativistic electrons are continuously injected by cosmic-ray protons; and the leptonic turbulent re-acceleration model, where cluster mergers re-energize electrons in situ. A key discriminant between the two models would be the existence of ultra-steep spectrum radio haloes (USSRHs), which can only be produced through turbulent re-acceleration. Here, we report the discovery of an USSRH in the galaxy cluster SPT-CLJ2337–5942 at redshift $z = 0.78$ in the MeerKAT-South Pole Telescope 100 deg$^2$ UHF (0.58–1.09 GHz) survey. This discovery is noteworthy for two primary reasons: it is the highest redshift USSRH system to date; and the close correspondence of the radio emission with the thermal ICM as traced by Chandra X-ray observations, further supporting the leptonic re-acceleration model. The halo is underluminous for its mass, consistent with a minor merger origin, which produces steep-spectrum, lower luminosity haloes. This result demonstrates the power of wide-field, high-fidelity, low-frequency ($\lesssim 1$ GHz) surveys like the MeerKAT-SPT 100 deg$^2$ programme to probe the origin and evolution of radio haloes over cosmic time, ahead of the Square Kilometre Array.

X-rays: galaxies↗

Discovery of a nearby radio relic in the low-mass, merging cluster Abell 4067

Shock waves generated during cluster mergers offer a powerful probe of how large-scale structure grows and evolves in the Universe. As part of the MeerKAT-South Pole Telescope (SPT) survey, we report the discovery of a single arc-like radio relic in the galaxy cluster Abell 4067 ($z=0.099$), one of the lowest-mass clusters known to host such a structure. MeerKAT UHF-band (0.58–1.09 GHz) observations reveal a relic with a largest linear size of $\sim 1.48\pm 0.02$ Mpc, located at a projected distance of 0.95 Mpc from the cluster centre. XMM–Newton X-ray data show that the relic’s position and orientation relative to the intracluster medium (ICM) elongation are consistent with a merger-driven shock-wave scenario. The relic has an estimated radio power of $3.10\pm 0.03\times 10^{24}$ W Hz$^{-1}$ at 150 MHz. When placed in the $P_{150\, \mathrm{MHz}}$–$M_{500}$ scaling relation, the Abell 4067 relic appears less luminous compared to relics in more massive clusters, suggesting an association with weak merger shocks. This finding supports the idea that relics in low-mass clusters may form through less energetic merger events, leading to weak merger shocks. The latter is supported by the absence of a detectable central radio halo in Abell 4067, which reinforces the idea that luminous radio haloes are not a universal outcome of cluster mergers and highlights the role of cluster mass, merger energetics, and evolutionary stage in shaping diffuse radio emission in the ICM.

79 ASTRONOMY AND ASTROPHYSICS↗

Probing the 𝑗 dependence of angular distributions and 𝑁=20 shell rigidity via the 36 S (𝑝,𝑑) 35 S reaction

An investigation of the N=20 36 S nucleus has been performed through a detailed study of the 3 6S (p,d)3 5S neutron-removal reaction, employing a 66-MeV proton beam at iThemba Laboratory for Accelerator Based Sciences and an innovative target design. Using the high-resolution K = 600 magnetic spectrometer, 98 states in 3 5S were identified up to 16-MeV excitation energy, including 47 previously unobserved states. Angular distributions and spectroscopic factors, including isobaric analog-state contributions, were extracted for 81 levels. A pronounced j dependence in the angular distributions of ℓ=2 states provides refined insights into the spin-orbit splitting. Finite-range adiabatic distorted-wave approximation calculations qualitatively reproduce the observed j dependence. Comparisons of the measured 1d 5/2 spectroscopic strength distribution with large-scale shell-model and ab initio calculations show good agreement overall, and the robustness of the N=20 shell closure in 36 S is confirmed when comparing the relatively low fp orbital occupancies in 40 Ca and 3 6S across the Fermi surface. This study underscores the utility of neutron-removal reactions in probing nuclear structure and the Fermi surface of sd nuclei and beyond. The findings advance our understanding of shell evolution and offer constraining data for theoretical models.

20 ≤ A ≤ 38↗

First 𝛽-Delayed Two-Neutron Spectroscopy of the 𝑟-Process Nucleus 134 In and Observation of the 𝑖 13/2 Single-Particle Neutron State in 133 Sn

This manuscript reports on the direct observation of a 𝛽-delayed two-neutron emission in a study of 134 In at the ISOLDE Decay Station using neutron spectroscopy. We also report on the first measurement in 𝛽 − decay of the long-sought 13/2 + excited state in 133 Sn, attributed to be the neutron single-particle 𝑖 13/2 orbital. The observation of sequential neutron emission is used to extract the relative population of the 𝑖 13/2 state, which was found to be much smaller than the predictions of the statistical model. The experiment was possible because of the innovative use of a neutron array with neutron discrimination and interaction tracking capabilities. This is the first study of the details of the two-neutron emission for a nucleus, which belongs to the 𝑟-process path. Understanding 𝛽-delayed two-neutron emission probabilities is essential to validate models used in astrophysical 𝑟-process nucleosynthesis calculations. Observing two-neutron emissions in 𝛽 − decay paves the way for new experiments to study energy and angular correlations for 𝛽-delayed multineutron emitters.

Beta decay↗

A haplotype‐resolved reference genome of Quercus alba sheds light on the evolutionary history of oaks

Summary White oak ( Quercus alba ) is an abundant forest tree species across eastern North America that is ecologically, culturally, and economically important. We report the first haplotype‐resolved chromosome‐scale genome assembly of Q. alba and conduct comparative analyses of genome structure and gene content against other published Fagaceae genomes. We investigate the genetic diversity of this widespread species and the phylogenetic relationships among oaks using whole genome data. Despite strongly conserved chromosome synteny and genome size across Quercus , certain gene families have undergone rapid changes in size, including defense genes. Unbiased annotation of resistance (R) genes across oaks revealed that the overall number of R genes is similar across species – as are the chromosomal locations of R gene clusters – but, gene number within clusters is more labile. We found that Q. alba has high genetic diversity, much of which predates its divergence from other oaks and likely impacts divergence time estimations. Our phylogenetic results highlight widespread phylogenetic discordance across the genus. The white oak genome represents a major new resource for studying genome diversity and evolution in Quercus . Additionally, we show that unbiased gene annotation is key to accurately assessing R gene evolution in Quercus .

Larson, Drew A. [Department of Biology Indiana Uni↗

t -channel dark matter models – a whitepaper

This report, summarising work achieved in the context of the LHC Dark Matter Working Group, investigates the phenomenology of t -channel dark matter models, spanning minimal setups with a single dark matter candidate and mediator to more complex constructions closer to UV-complete models. For each considered class of models, we examine collider, cosmological and astrophysical implications. In addition, we explore scenarios with either promptly decaying or long-lived particles, as well as featuring diverse dark matter production mechanisms in the early universe. By providing a unified analysis framework, numerical tools and guidelines, this work aims to support future experimental and theoretical efforts in exploring t -channel dark matter models at colliders and in cosmology.

Arina, Chiara [Universite Catholique de Louvain, L↗

Exascale Computing and Data Handling: Challenges and Opportunities for Weather and Climate Prediction

The emergence of exascale computing and artificial intelligence offer tremendous potential to significantly advance Earth system prediction capabilities. However, enormous challenges must be overcome to adapt models and prediction systems to use these new technologies effectively. A 2022 WMO report on exascale computing recommends “urgency in dedicating efforts and attention to disruptions associated with evolving computing technologies that will be increasingly difficult to overcome, threatening continued advancements in weather and climate prediction capabilities.” Further, the explosive growth in data from observations, model and ensemble output, and postprocessing threatens to overwhelm the ability to deliver timely, accurate, and precise information needed for decision-making. Artificial intelligence (AI) offers untapped opportunities to alter how models are developed, observations are processed, and predictions are analyzed and extracted for decision-making. Given the extraordinarily high cost of computing, growing complexity of prediction systems, and increasingly unmanageable amount of data being produced and consumed, these challenges are rapidly becoming too large for any single institution or country to handle. This paper describes key technical and budgetary challenges, identifies gaps and ways to address them, and makes a number of recommendations.

Atmosphere↗

Global Precipitation Experiment—A New World Climate Research Programme Lighthouse Activity

The future state of the global water cycle and the prediction of freshwater availability for humans around the world remain among the challenges of climate research and are relevant to several United Nations Sustainable Development Goals. The Global Precipitation Experiment (GPEX) takes on the challenge of improving the prediction of precipitation quantity, phase, timing, and intensity, characteristics that are products of a complex integrated system. It will achieve this by leveraging existing World Climate Research Programme (WCRP) activities and community capabilities in satellite, surface-based, and airborne observations, modeling, and experimental research and by conducting new and focused activities. It was launched in October 2023 as a WCRP Lighthouse Activity. Here, we present an overview of the GPEX Science Plan that articulates the primary science questions related to precipitation measurements, process understanding, model performance and improvements, and plans for capacity development. The central phase of GPEX is the WCRP Years of Precipitation for 2–3 years with coordinated global field campaigns focusing on different storm types (atmospheric rivers, mesoscale convective systems, monsoons, and tropical cyclones, among others) over different regions and seasons. Activities are planned over the three phases (before, during, and after the Years of Precipitation) spanning a decade. These include gridded data evaluation and development, advanced modeling, enhanced understanding of processes critical to precipitation, multiscale prediction of precipitation events across scales, and capacity development. These activities will be further developed as part of the GPEX Implementation Plan.

Climate change↗

ARM FY2025 Radar Plan

The U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility is dedicated to delivering high-quality radar data that significantly advance our understanding of cloud and precipitation processes, improving climate models. With radars operating across diverse frequencies, scanning modes, and global climate conditions, extensive staffing is essential for effective management. Due to current staffing constraints, achieving the expected level of operational excellence requires a more strategic approach. To address this challenge, ARM has developed an operational radar plan for the upcoming Fiscal Year 2025 (FY25) based on budget and staffing considerations. This report summarizes the Fiscal Year 2024 (FY24) ARM radar-related activities and outlines the strategic plan for FY25. It presents a comprehensive radar plan that includes detailed activities, priorities, and a projected timeline aligned with the ARM radar roadmap. Key tasks, detailed in Table 1, cover various radar operational stages and coordinated efforts among ARM teams.

54 ENVIRONMENTAL SCIENCES↗

Training and onboarding initiatives in high energy physics experiments

In this article we document the current analysis software training and onboarding activities in several High Energy Physics (HEP) experiments: ATLAS, CMS, LHCb, Belle II and DUNE. Fast and efficient onboarding of new collaboration members is increasingly important for HEP experiments. With rapidly increasing data volumes and larger collaborations the analyses and consequently, the related software, become ever more complex. This necessitates structured onboarding and training. Recognizing this, a meeting series was held by the HEP Software Foundation (HSF) in 2022 for experiments to showcase their initiatives. Here we document and analyze these in an attempt to determine a set of key considerations for future HEP experiments.

analysis software↗

The Kangaroo’s First Hop: The Early Fast Cooling Phase of EP250108a/SN 2025kg

Fast X-ray transients are a rare and poorly understood population of events. Previously difficult to detect in real time, the launch of the Einstein Probe with its Wide-field X-ray Telescope has led to a rapid expansionof the sample and allowed the exploration of these transients across the electromagnetic spectrum. EP250108a is a recently detected example linked to an optical counterpart, SN 2025kg, or “the kangaroo.” Together with a companion Letter we present our observing campaign and analysis of this event. In this letter, we focus on the early evolution of the optical counterpart over the first 6 days, including our measurement of the redshift of z = 0.17641. We compare to other supernovae and fast transients showing similar features, finding significant similarities with SN 2006aj and SN 2020bvc, and show that the source is well modelled by a rapidly expanding cooling blackbody. We show the observed X-ray and radio properties are consistent with a collapsar-powered jet that is low energy (≲10 51 erg) and/or fails to break out of the dense material surrounding it. While we examine the possibility that the optical emission emerges from the shock produced as the supernova ejecta expand into a dense shell of circumstellar material, due to our X-ray and radio inferences, we favour a model where it arises from a shocked cocoon resulting from a trapped jet. This makes SN 2025 one of the few examples of this currently observationally rare event.

79 ASTRONOMY AND ASTROPHYSICS↗

The Detection and Attribution Model Intercomparison Project (DAMIP v2.0) contribution to CMIP7

The first version of the Detection and Attribution Model Intercomparison Project (DAMIP v1.0) coordinated key simulations exploring the role of individual forcings in past, current and future climate as part of the Coupled Model Intercomparison Project, Phase 6 (CMIP6). The simulations have been used extensively in the literature for detection and attribution of long-term changes, constraining projections of climate change, attributing extreme events and understanding drivers of past and future simulated climate changes. Attribution studies using DAMIP v1.0 simulations underpinned prominent assessments of human-induced warming in the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. Here, we describe the set of DAMIP v2.0 simulations, proposed for the next phase of CMIP, CMIP7. Detection and attribution studies rely on pre-industrial control simulations and historical simulations, which will be part of the Diagnostic, Evaluation and Characterization of Klima (DECK) set of simulations for CMIP7. In addition, we identify the three highest-priority single-forcing experiments for CMIP7 to be run as “Assessment Fast Track” simulations in support of the Seventh Assessment Report of the IPCC: simulations with natural forcings only, anthropogenic well-mixed greenhouse gases only and anthropogenic aerosols only. Beyond this, the DAMIP v2.0 experimental design includes full-column ozone-only simulations and land-use-only simulations, such that the set of individual forcing experiments, when these are considered together, represents the full set of historical forcings. While concentration-driven simulations are prioritised for attribution, emissions-driven versions of the DAMIP experiments are also proposed to support understanding of the influence of carbon-cycle feedbacks on the simulated responses to individual forcings.

Gillett, Nathan P. [Environment and Climate Change↗

Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration

The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that challenge traditional analysis pipelines. The LSST Dark Energy Science Collaboration (DESC) aims to derive robust constraints on dark energy and dark matter from these data, requiring methods that are statistically powerful, scalable, and operationally reliable. Artificial intelligence and machine learning (AI/ML) are already embedded across DESC science workflows, from photometric redshifts and transient classification to weak lensing inference and cosmological simulations. Yet their utility for precision cosmology hinges on trustworthy uncertainty quantification, robustness to covariate shift and model misspecification, and reproducible integration within scientific pipelines. This white paper surveys the current landscape of AI/ML across DESC's primary cosmological probes and cross-cutting analyses, revealing that the same core methodologies and fundamental challenges recur across disparate science cases. Since progress on these cross-cutting challenges would benefit multiple probes simultaneously, we identify key methodological research priorities, including Bayesian inference at scale, physics-informed methods, validation frameworks, and active learning for discovery. With an eye on emerging techniques, we also explore the potential of the latest foundation model methodologies and LLM-driven agentic AI systems to reshape DESC workflows, provided their deployment is coupled with rigorous evaluation and governance. Finally, we discuss critical software, computing, data infrastructure, and human capital requirements for the successful deployment of these new methodologies, and consider associated risks and opportunities for broader coordination with external actors.

Aubourg, Eric [APC, Paris] (ORCID:000000025592023X↗