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At least 253 records · Page 14

The Cycle of Cosmic Dust

The presence of dust in the interstellar medium of galaxies dramatically affects their spectral appearance, and the interpretation of their underlying physical properties. Consequently, the diagnostic of galaxy spectra depends crucially on our understanding of the nature and properties of these dust particles. Models of interstellar dust particles must be able to reproduce a basic set of observational constraints, including the general interstellar extinction and infrared emission observed in the diffuse interstellar medium (ISM). Recent analysis of the solar spectrum have resulted in a convergence between the solar and B star abundances. This development, and the steadiness in the solar abundance determination of the primary refractory elements Mg, Si, and Fe, strongly suggest that any viable dust model must also obey interstellar abundances constraints. I will present fifteen dust models that differ in composition and size distribution and that simultaneously satisfy the local extinction, infrared emission, and abundances constraints have been shown to exist. This multitude of viable dust models provides us with an increased flexibility in understanding dust evolution and the many variations in dust properties in different phases of the ISM and stellar environments.

Dwek, Eliahu↗

Photoevaporation of Clumps in Photodissociation Regions

We present the results of an investigation of the effects of Far Ultraviolet (FUV) radiation (6.0eV < hv < 13.6eV) from hot early type OB stars on clumps in star-forming molecular clouds. Clumps in FUV-illuminated regions (or photodissociation regions or PDRs) undergo external heating and photodissociation as they are exposed to the FUV field, resulting in a loss of cold, molecular lump mass as it is converted to warm atomic gas. The heating, if rapid, creates strong photoevaporative mass flows off the clump surfaces, and drives shocks into the clumps, compressing them to high densities. The clumps lose mass on relatively short timescales. The evolution of an individual clump is found to be sensitive to three dimensionless parameters: Nc0, the ratio of the initial column density of the clump to the column N(0) approx. 10(exp 21) cm(exp -2) of a warm FUV-heated surface region; upsilon, the ratio of the sound speed in the heated surface to that in the cold clump material: and t(FUV)t(c), the ratio of the "turn-on time" t(FUV) of the heating flux on a clump to its initial sound crossing-time t(c). The evolution also depends on whether a confining interclump medium exists, or whether the interclump region has negligible pressure, as is the case for turbulence-generated clumps. In this paper, we use spherical 1-D numerical hydrodynamic models as well as approximate analytical models to study the dependence of clump photoevaporation on the physical parameters of the clump, and to derive the dynamical evolution, mass loss rates and photoevaporative timescales of a clump for a variety of astrophysical situations. Turbulent clumps evolve so that their column densities are equal to a critical value determined by the local FUV field, and typically have short photo evaporation timescales, approx. 10(exp 4-5) years for a 1 M(solar mass) clump in a typical star-forming region (Nc0 = 10, upsilon = 10). Clumps with insufficient magnetic pressure support, and in strong FUV fields may be driven to collapse by the compressional effect of converging shock waves. We also estimate the rocket effect on photoevaporating clumps and find that it is significant only for the smallest clumps, with sizes much less than the extent of the PDR itself. Clumps that are confined by all interclump medium may either get completely photoevaporated, or may preserve a shielded core with a warm, dissociated, protective shell that, absorbs the incident FUV flux. We compare our results with observations of some well studied PDRs: the Orion Bar, M17SW NGC 2023 and the Rosette Nebula. The data are consistent with both interpretations of clump origin. turbulence and pressure confinement, with a slight indication for favouring the turbulent model for clumps over pressure-confined

Gorti, Uma↗

An intense, quasi-steady thunderstorm over mountainous terrain. I - Evolution of the storm-initiating mesoscale circulation

The evolution of mesoscale systems that eventually lead to the formation of large quasi-steady storm systems is investigated. The morphological and turbulent structure of the quasi-steady storm is described. Data obtained during the South Park Area Cumulus Experiment from surface meteorological stations, rawinsondes and tethered balloons, conventional and Doppler radars, powered aircraft, and satellites, indicate that on July 19, 1977, a north-south oriented line of intense convective cells formed and remained within South Park. Elevated surface heating created a region of low-level convergence, importing Pacific moisture from west of the Rockies. The mesoscale thunderstorm line formed over this convergence zone, and a single large convective cell was observed to grow on the southern end of the mesoscale line, exhibiting supercell characteristics and substantial modifications of the environmental flow.

Cotton, W. R.↗

Overview of NLR Automated Mobility District Implementation Research - Phases I, II, and III. The Convergence of Automation, Electrification, and On-Demand Services: Enabling Resilient Automated Mobility Districts

A research program by the National Renewable Energy Laboratory has been investigating the implementation prospects for fully automated passenger transport systems that are deployed to operate within dense urban settings, referred to as Automated Mobility Districts (AMDs). An AMD emphasizes the deployment of automated vehicles (AV) passenger transport services within a dense urban setting and other major activity centers with intense passenger origin-destination demand patterns, such as those found in large business districts, airports, and university and medical campuses. Phase I and II surveyed 10 early deployment sites and subsequently collected and evaluated the lessons learned from these early deployment sites, with particular attention to fleet operations, impacts of service reliability, and vehicle technology evolution as the field of companies was being progressively winnowed by the challenges of full automation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Doppler-radar observation of the evolution of downdrafts in convective clouds

A detailed analysis of the 20 July 1977 thunderstorm complex which formed and evolve over the South Park region in Central Colorado is presented. The storm was extensively analyzed using multiple Doppler radar and surface mesonet data, developed within an environment having very weak wind shear. The storm owed its intensification to the strength of the downdraft, which was nearly coincident with the region where the cloud had grown. The noteworthy features of this storm were its motion to the right of the cloud-level winds, its multicellular nature and discrete propagation, its north-south orientation, and its relatively large storm size and high reflectivity factor (55 dBZ). This scenario accounts for the observed mesoscale and cloud-scale event. A line of convergence was generated at the interface between the easterly upslope winds and westerly winds. During stage II, the convergence line subsequently propagated down the slopes of the Mosquito Range, and was the main forcing mechanism for the development of updraft on the west flank of the storm. The formation of downdraft on the eastern side of updraft blacked surface inflow, and created a detectable gust front. As the original downdraft intensified, the accumulation of evaporatively-chilled air caused the intensification of the mesohigh, which likely destroyed the earlier convergence line and created a stronger convergence line to the east, which forced up-lifting of the moist, westerly inflow and caused the formation of updraft to the east. An organized downdraft circulation, apparently maintained by precipitation drag and evaporational cooling, was responsible in sustaining a well-defined gust front. The storm attained its highest intensity as a consequence of merging with a neighboring cloud. The interaction of downdrafts or gust fronts from two intense cells appeared to be the primary mechanism of this merging process as suggested by Simpson et al. (1980). The merging process coincided with more rain than occurred in unmerged echoes.

Motallebi, N.↗

Enabling dynamic 3D coherent diffraction imaging via adaptive latent space tuning of generative autoencoders

Abstract Coherent diffraction imaging (CDI) is an advanced non-destructive 3D X-ray imaging technique for measuring a sample’s electron density. The main challenge of CDI is loss of phase information in diffraction intensity measurements, resulting in lengthy iterative reconstruction processes that can return non-unique solutions, which pose challenges for experiments attempting to track dynamic sample evolution through multiple states. As the increased brightness of fourth-generation light sources enables faster sample measurements and drives operando experiments with Bragg CDI, there is a growing need for faster reconstruction techniques that can keep pace. We have developed an adaptive generative autoencoder approach for uniquely tracking a sample’s electron density as it dynamically evolves. Our approach adaptively tunes the low-dimensional latent embedding of a generative autoencoder, enabling a computationally efficient manner to account for time-varying shifting distributions in real-time. Analytic proof of convergence is provided as well as numerical demonstration of sample tracking with noisy measurements.

97 MATHEMATICS AND COMPUTING↗

Machine learning models for PDE constrained optimization

Partial differential equation (PDE)-constrained optimization problems arise in a variety of scientific and engineering applications, such as topology optimization, electrodynamics, fluid dynamics, and structural dynamics. However, these problems are often challenging and computationally expensive to solve, due to the need to solve the PDEs within the optimization loop. One approach to reducing the computational cost of these methods while providing convergence guarantees is through inexact trust region methods; this method uses lower fidelity solutions of the PDE at early stages of the optimization and adjusts the required accuracy of inexact PDE solvers as the optimization progresses. In this work, we explore the use of machine learning based surrogate models with these inexact trust region methods. We first demonstrate the potential of this approach by using Gaussian processes as the surrogate model and test this on a simple PDE-constrained optimization problem. We then document explorations into improving the computational costs of evolutional deep neural network / neural Galerkin methods, with the eventual goal of using these methods with the inexact trust region algorithms. We are able to speed up these approaches, albeit at the cost of lower accuracy.

97 MATHEMATICS AND COMPUTING↗

Domain decomposition: A bridge between nature and parallel computers

Domain decomposition is an intuitive organizing principle for a partial differential equation (PDE) computation, both physically and architecturally. However, its significance extends beyond the readily apparent issues of geometry and discretization, on one hand, and of modular software and distributed hardware, on the other. Engineering and computer science aspects are bridged by an old but recently enriched mathematical theory that offers the subject not only unity, but also tools for analysis and generalization. Domain decomposition induces function-space and operator decompositions with valuable properties. Function-space bases and operator splittings that are not derived from domain decompositions generally lack one or more of these properties. The evolution of domain decomposition methods for elliptically dominated problems has linked two major algorithmic developments of the last 15 years: multilevel and Krylov methods. Domain decomposition methods may be considered descendants of both classes with an inheritance from each: they are nearly optimal and at the same time efficiently parallelizable. Many computationally driven application areas are ripe for these developments. A progression is made from a mathematically informal motivation for domain decomposition methods to a specific focus on fluid dynamics applications. To be introductory rather than comprehensive, simple examples are provided while convergence proofs and algorithmic details are left to the original references; however, an attempt is made to convey their most salient features, especially where this leads to algorithmic insight.

Keyes, David E.↗

Torque Balances on the Taylor Cylinders in the Geomagnetic Data Assimilation

In this presentation we report on our continuing effort in geomagnetic data assimilation, aiming at understanding and predicting geomagnetic secular variation on decadal time scales. In particular, we focus on the effect of the torque balances on the cylindrical surfaces in the core co-axial with the Earth's rotation axis (the Taylor cylinders) on the time evolution of assimilated solutions. We use our MoSST core dynamics,model and observed geomagnetic field at the Earth's surface derived via Comprehensive Field Model (CFM) for the geomagnetic data assimilation. In our earlier studies, a model solution is selected randomly from our numerical database. It is then assimilated with the observations such that the poloidal field possesses the same field tomography on the core-mantel boundary (CMB) continued downward from surface observations. This tomography change is assumed to be effective through out the outer core. While this approach allows rapid convergence between model solutions and the observations, it also generates sevee numerical instabilities: the delicate balance between weak fluid inertia and the magnetic torques on the Taylor cylinders are completely altered. Consequently, the assimilated solution diverges quickly (in approximately 10% of the magnetic free-decay time in the core). To improve the assimilation, we propose a partial penetration of the assimilation from the CMB: The full-scale modification at the CMB decreases linearly and vanish at an interior radius r(sub a). We shall examine from our assimilation tests possible relationships between the convergence rate of the model solutions to observations and the cut-off radius r(sub a). A better assimilation shall serve our nudging tests in near future.

Kuang, Weijia↗

Integrating Intermediate Traits in Phylogenetic Genotype-to-Phenotype Studies

A major goal of research in evolution and genetics is linking genotype to phenotype. This work could be direct, such as determining the genetic basis of a phenotype by leveraging genetic variation or divergence in a developmental, physiological, or behavioral trait. The work could also involve studying the evolutionary phenomena (e.g., reproductive isolation, adaptation, sexual dimorphism, behavior) that reveal an indirect link between genotype and a trait of interest. When the phenotype diverges across evolutionarily distinct lineages, this genotype-to-phenotype problem can be addressed using phylogenetic genotype-to-phenotype (PhyloG2P) mapping, which uses genetic signatures and convergent phenotypes on a phylogeny to infer the genetic bases of traits. The PhyloG2P approach has proven powerful in revealing key genetic changes associated with diverse traits, including the mammalian transition to marine environments and transitions between major mechanisms of photosynthesis. However, there are several intermediate traits layered in between genotype and the phenotype of interest, including but not limited to transcriptional profiles, chromatin states, protein abundances, structures, modifications, metabolites, and physiological parameters. Each intermediate trait is interesting and informative in its own right, but synthesis across data types has great promise for providing a deep, integrated, and predictive understanding of how genotypes drive phenotypic differences and convergence. We argue that an expanded PhyloG2P framework (the PhyloG2P matrix) that explicitly considers intermediate traits, and imputes those that are prohibitive to obtain, will allow a better mechanistic understanding of any trait of interest. Furthermore, this approach provides a proxy for functional validation and mechanistic understanding in organisms where laboratory manipulation is impractical.

59 BASIC BIOLOGICAL SCIENCES↗

Observations of X-ray Afterglows

Discussion of X-ray studies of the environs of Gamma Ray Burst (GRB) associated Supernovae using the Chandra and XMM X-Ray Observatories, in particular the long term evolution of their X-ray afterglow lightcurves. For SN 1998bw, we have combined all available observations and derived a smooth X-ray light curve spanning -1300 days, assuming that GRB 980425 and SN 1998bw were coincident at 35.6 Mpc. Perform comparison of this X-ray light curve with those of the X-ray afterglows of ordinary GRBs, X-ray Flashes, and ordinary supernovae, and discuss the emerging evidence for at least two classes of lightcurves, perhaps bounding a continuum. By three to ten years, all these phenomena seem to converge on a common X-ray luminosity, possibly indicative of the supernova underlying them all. One possible explanation for the two classes is a (nearly) standard GRB observed at different angles. If this interpretation is correct, X-ray afterglows with intermediate luminosities should eventually be discovered; GRB 03 1203 maybe just such a case.

Kouveliotou, Chryssa↗

The evolution of convective storms from their footprints on the sea as viewed by synthetic aperture radar from space

SEASAT synthetic aperture radar (SAR) echoes from the sea have previously been shown to be the result of rain and winds produced by convective stroms; rain damps the surface waves and causes ech-free holes, while the diverging winds associated with downdraft generate waves and associated echoes surrounding the holes. Gust fronts are also evident. Such a snapshot from 8 July 1978 has been examined in conjunction with ground-based radar. This leads to the conclusion that the SAR storm footprints resulted from storm processes that occurred up to an hour or more prior to the snapshot. A sequence of events is discerned from the SAR imagery in which new cell growth is triggered in between the converging outflows of two preexisting cells. In turn, the new cell generates a mini-squall line along its expanding gust front. While such phenomena are well known over land, the spaceborne SAR now allows important inferences to be made about the nature and frequency of convective storms over the oceans. The storm effects on the sea have significant implications for spaceborne wind scatterometry and rainfall measurements. Some of the findings herein remain speculative because of the great distance to the Miami weather radar-the only source of corroborative data.

Atlas, David↗

Gravity field determination for Mars Observer

Mars Observer will be the first near circular, low altitude and short-periodic orbiter of Mars. From previous Mars orbiters, such as Mariner 9 and Vikings 1 and 2, a large gravitational oblateness and in general a gravity field ten times stronger than the earth's field have been determined. Because of these, the gravity field will dominate the evolution of the spacecraft's orbital motion and is the principal error source for reconstructing the spacecraft's motion. Thus a gravity calibration (GC) period has been established prior to the mapping phase in order to refine the gravitational field model. This paper describes the plan being made by Navigation to implement the GC strategy. By analyzing simulated Doppler data acquired during the seven day GC period, we give (1) the expected improvement in the gravity field model and (2) the resulting improvement in reconstructed spacecraft orbital motion. In addition, we have developed a strategy for converging the GC gravity model.

Esposito, Pasquale B.↗

Exploring the non-Gaussianity of the cosmic infrared background and its weak gravitational lensing

ABSTRACT Gravitational lensing deflects the paths of photons, altering the statistics of cosmic backgrounds and distorting their information content. We take the cosmic infrared background (CIB), which provides plentiful information about galaxy formation and evolution, as an example to probe the effect of lensing on non-Gaussian statistics. Using the Websky simulations, we first quantify the non-Gaussianity of the CIB, revealing additional detail on top of its well-measured power spectrum. To achieve this, we use needlet-like multipole-band filters to calculate the variance and higher-point correlations. Using our simulations, we show the two-, three- and four-point spectra, and compare our calculated power spectra and bispectra to Planck values. We then lens the CIB, shell-by-shell with corresponding convergence maps, to capture the broad redshift extent of both the CIB and its lensing convergence. The lensing of the CIB changes the three- and four-point functions by a few tens of per cent at large scales, unlike with the power spectrum, which changes by less than two per cent. We expand our analyses to encompass the full intensity probability distribution functions (PDFs) involving all n-point correlations as a function of scale. In particular, we use the relative entropy between lensed and unlensed PDFs to create a spectrum of templates that can allow estimation of lensing. The underlying CIB model is missing the important role of star bursting, which we test by adding a stochastic lognormal term to the intensity distributions. The novel aspects of our filtering and lensing pipeline should prove useful for any radiant background, including line intensity maps.

79 ASTRONOMY AND ASTROPHYSICS↗

Stochastic Mixing Model with Power Law Decay of Variance

Here we present a simple stochastic mixing model based on the law of large numbers (LLN). The reason why the LLN is involved in our formulation of the mixing problem is that the random conserved scalar c = c(t,x(t)) appears to behave as a sample mean. It converges to the mean value mu, while the variance sigma(sup 2)(sub c) (t) decays approximately as t(exp -1). Since the variance of the scalar decays faster than a sample mean (typically is greater than unity), we will introduce some non-linear modifications into the corresponding pdf-equation. The main idea is to develop a robust model which is independent from restrictive assumptions about the shape of the pdf. The remainder of this paper is organized as follows. In Section 2 we derive the integral equation from a stochastic difference equation describing the evolution of the pdf of a passive scalar in time. The stochastic difference equation introduces an exchange rate gamma(sub n) which we model in a first step as a deterministic function. In a second step, we generalize gamma(sub n) as a stochastic variable taking fluctuations in the inhomogeneous environment into account. In Section 3 we solve the non-linear integral equation numerically and analyze the influence of the different parameters on the decay rate. The paper finishes with a conclusion.

Fedotov, S.↗

Microchannel-based Membrane-less Extraction of Li from Unconventional Lithium Sources & the Separation of REE

This final report provides an overview of the Project's entire duration, covering July 1, 2021 to December 31, 2023. It primarily focuses on the achievements, technological developments, and unique challenges the team faced while working on separating and extracting Lithium from produced waters. The project's primary aim was to create an integrated, high-throughput, membrane-less, and modular microfluidic platform that could extract Lithium from unconventional sources. We have successfully met all goals and milestones envisioned in the SOPO document. The most critical primary milestones, including the Go-No-Go milestone (refer to the Gantt chart in the Appendices), were successfully accomplished. We demonstrated phase separation (>90%) and extraction (>85%) performance in the MPSE using synthetic, and representative produced water composition feed at 50 ml/min total flow through MPSE 36. We have also performed a parametric study of the MPSE operations, beyond the scope of SOPO, exploring operating conditions of current and broader interest. The extended investigation of operational parameters is concurrent with our efforts to seek further development of the MPSE technology beyond the scope of the Project. Along these lines of development, we have made efforts to be responsive to DOE calls for technological developments of other types of resources (beyond PW) for the recovery of Critical Materials and higher TRL development (beyond TRL 4). During the work on this Project, we developed and implemented three innovative technical approaches that emerged from our efforts to successfully meet the Project milestones. The innovative & original technical approaches developed and implemented in this Project are now the contributions to process engineering that could be clearly credited to the Project. First, Convergent Design Approach is a comprehensive feedforward & feedback loop of four design phases: i) design for functionality, ii) design for manufacturing, iii) design for sustainability, and iv) design for market. Next was Process Intensification. A major aim of this Project was to create an innovative phase separation & extraction microscale-based technology for Li separation – thus the words microchannel-based in the Project title. A microscale-based technology is intrinsically in the center of the Process Intensification domain as defined by its unique principles. Therefore, Process Intensification was implicitly envisioned in the Project’s SOPO. Lastly, Time Scale Analysis is a novel tool for discovering the needs and directions of Process Intensification implementations in any process technology. This Project is fully credited for developing and implementing the three novel technical approaches mentioned above. These are general contributions to process engineering that emerged from this Project. Beyond the original SOPO scope, the OSU-U.Pitt research group utilized a Convergent Design methodology, integrating first-principles mathematical modeling with experimental validation on the Minimum Development Vehicle. By creating these Digital Twins, the team rapidly assessed manufacturing iterations to support TEA analysis. This framework further enabled the development of advanced Surface Modification Techniques, where hydrophobic and oleophobic coating strategies were optimized via Digital Twin tools and validated through rigorous 100-hour longevity testing. TEA Analysis: The closing efforts of this Project were focused on the TEA analysis. TEA analysis had two primary functions: i) enabling critical assessments of design variations withing 10 the Concurrent Design Approach, thus enabling evolution of the MPSE design to reach faster- better-cheaper alternatives; and ii) to create a bridge between the accomplishments of this Project and future projects of higher TRL, beyond TRL 6 level. It is important to note that the TEA model created in the Project stirred the technological solutions for the recovery of critical materials toward a vision of a very profitable modular plant that has unique zero-waste water discharge signature. More importantly, thanks to our experimental performance data and conservative assumptions, the TEA model predicts minimal technological and investment risks. Low cost of a modular unit of a nominal capacity of [1000 tons of Li 2 CO 3 /year] positions the MPSE based technology within the reach of community investors, thus offering a paradigm shift in the development of critical technologies. The project successfully navigated two primary challenges: solvent selection and manufacturing adaptation. Restricted by the SOPO to existing literature for lithium recovery, the team identified a critical need for a "material excellence program" to develop next-generation solvents, eventually concluding with a preliminary investigation into promising Ionic Liquids (ILs). Simultaneously, COVID-19 supply chain disruptions forced a pivot from traditional manufacturing to advanced additive methods at ATAMI-OSU. By transitioning from stainless steel to 3D-printed polymer substrates, the team achieved a transformative three-order-of- magnitude reduction in manufacturing costs and compressed prototyping timelines from several months to just two days. The MPSE technology offers significant energy, environmental, and economic advantages by overcoming the traditional bottlenecks of phase-separation hardware and contactor size. Unlike conventional mixer-settlers or membrane-based systems, MPSE operates without moving parts or fouling-prone membranes, achieving robust performance even with challenging, viscous, or particulate-heavy feeds. Key performance metrics include an energy intensity reduction of 5–50x (3–40 kJ/m 3 ) compared to incumbent technologies and a dramatic reduction of processing time to under 60 seconds, which drastically reduces the physical plant footprint. These technical efficiencies translate into superior economic outcomes; for a 100 t/year Li 2 CO 3 facility, implementing MPSE is projected to nearly halve contactor CAPEX (from $\$$6.08M to $\$$3.01M) and significantly increase the project's Net Present Value (NPV), derisking new investment and enabling distributed critical-mineral processing configurations. The commercialization of MPSE technology is being spearheaded by Vigsur Dynamics Inc., which has adopted a structured, parallel approach to technical and business development since its formation in January 2026. Following extensive customer discovery and engagement with the Oregon State University accelerator, Vigsur Dynamics is working to establish a business model that transitions from pilot demonstrations to modular hardware sales, ultimately aiming for a "build-own-operate" service strategy. Current technical milestones—including 100 hours of continuous operation, superior energy efficiency, and successful 6-unit modular scale-up— provide a foundation for this transition. Backed by ongoing IP licensing and a growing network of industrial and venture advisors, the company is actively de-risking the platform to replace conventional mixer-settler systems in the critical minerals market.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Influence of the drive design on ablation front hydrodynamic instability growth in a capsule implosion at the National Ignition Facility

A critical aspect of inertial confinement fusion experiments lies in the control of ablation front instabilities during the implosion process. The growth of Rayleigh–Taylor and Richtmyer–Meshkov instabilities, seeded by target defects, can significantly degrade the performance of the implosion. Here, this study explores the influence of drive design on ablation front stability using the hydro-growth radiography platform at the National Ignition Facility. This platform allows the measurement of the ablation front hydrodynamic instability growth. Because these measurements are restricted to early convergence, their primary role is to constrain the initial instability growth and benchmark the simulations used to infer shell integrity and performance at peak velocity and ignition. Three ignition designs, Hybrid-E (HyE), SQ-n (“S” for scaling and “Q” for quality), and High temperature, High thickness (HiT) were analyzed. The results demonstrated a high dependence of the growth factor on the choice of design, capsule scale as well as the hohlraum conditions, mainly the radiative temperature and the gold M-band emission. HyE and SQ-n display a similar growth factor range, but their evolution is different due to the design differences in hohlraum conditions. HiT has the lowest growth factor of the studied designs, which is a result of a higher radiative temperature. These results highlight the importance of design choices in controlling instability dynamics. These insights inform future drive design strategies to enhance stability and efficiency in fusion ignition experiments.

Physics↗

Uncovering heterogeneous intercommunity disease transmission from neutral allele frequency time series

The COVID-19 pandemic has underscored the need for accurate epidemic forecasting to predict pathogen spread, evolution, and evaluate intervention strategies. Forecast reliability hinges on detailed knowledge of disease transmission across population segments, which may be inferred from contact surveys or mobility data. However, these indirect approaches make it difficult to estimate rare transmissions between socially or geographically distant communities. We show that the steep ramp-up of genome sequencing surveillance during the pandemic can be leveraged to directly identify transmission patterns between geographically defined communities. Our approach uses a hidden Markov model to infer the fraction of infections a community imports from others based on how rapidly allele frequencies in the focal community converge to those in the donor communities. Applying this method to SARS-CoV-2 sequencing data from England and the United States, we uncover networks of intercommunity transmission that reflect geographical relationships while exposing significant long-range interactions. The scaling of importation rate with distance is consistent across both countries, yet weaker than expected based on mobility data, highlighting limitations of indirect inference. We show that transmission patterns can change between waves of variants of concern and analyze how the inferred heterogeneity in intercommunity transmission impacts evolutionary forecasts. While applied here to geographically defined communities, our approach could be applied to those defined by other traits (e.g., age, socioeconomic status), provided time-series data can be stratified accordingly. Overall, our study highlights population genomic time series data as a crucial record of epidemiological interactions, which can be deciphered using tree-free inference methods.

Okada, Takashi [Department of Physics; University ↗