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At least 199 records · Page 11

Logical quantum processor based on reconfigurable atom arrays

Suppressing errors is the central challenge for useful quantum computing, requiring quantum error correction (QEC) for large-scale processing. However, the overhead in the realization of error-corrected ‘logical’ qubits, in which information is encoded across many physical qubits for redundancy, poses substantial challenges to large-scale logical quantum computing. Here we report the realization of a programmable quantum processor based on encoded logical qubits operating with up to 280 physical qubits. Using logical-level control and a zoned architecture in reconfigurable neutral-atom arrays, our system combines high two-qubit gate fidelities, arbitrary connectivity, as well as fully programmable single-qubit rotations and mid-circuit readout. Operating this logical processor with various types of encoding, we demonstrate improvement of a two-qubit logic gate by scaling surface-code distance from d = 3 to d = 7, preparation of colour-code qubits with break-even fidelities, fault-tolerant creation of logical Greenberger–Horne–Zeilinger (GHZ) states and feedforward entanglement teleportation, as well as operation of 40 colour-code qubits. Finally, using 3D [[8,3,2]] code blocks, we realize computationally complex sampling circuits with up to 48 logical qubits entangled with hypercube connectivity with 228 logical two-qubit gates and 48 logical CCZ gates. We find that this logical encoding substantially improves algorithmic performance with error detection, outperforming physical-qubit fidelities at both cross-entropy benchmarking and quantum simulations of fast scrambling. These results herald the advent of early error-corrected quantum computation and chart a path towards large-scale logical processors.

74 ATOMIC AND MOLECULAR PHYSICS↗

Processing Full-Scale Square Kilometre Array Data on the Summit Supercomputer

This work presents a workflow for simulating and processing the full-scale low-frequency telescope data of the Square Kilometre Array (SKA) Phase 1. The SKA project will enter the construction phase soon, and once completed, it will be the world’s largest radio telescope and one of the world’s largest data generators. The authors used Summit to mimic an endto-end SKA workflow, simulating a dataset of a typical 6 hour observation and then processing that dataset with an imaging pipeline. This workflow was deployed and run on 4,560 compute nodes, and used 27,360 GPUs to generate 2.6 PB of data. This was the first time that radio astronomical data were processed at this scale. Results show that the workflow has the capability to process one of the key SKA science cases, an Epoch of Reionization observation. This analysis also helps reveal critical design factors for the next-generation radio telescopes and the required dedicated processing facilities.

Wang, Ruonan↗

The mechanics of brittle granular materials with coevolving grain size and shape

The influence of particle shape on the mechanics of sand is widely recognized, especially in mineral processing and geomechanics. However, most existing continuum theories for engineering applications do not encompass the morphology of the grains and its evolution during comminution. Similarly, the relatively few engineering models accounting for grain-scale processes tend to idealize particles as spheres, with their diameters considered as the primary and sole geometric descriptor. This paper inspires a new generation of constitutive laws for crushable granular continua with arbitrary, yet evolving, particle morphology. We explore the idea of introducing multiple grain shape descriptors into Continuum Breakage Mechanics (CBM), a theory originally designed to track changes in particle size distributions during confined comminution. We incorporate the influence of these descriptors on the elastic strain energy potential and treat them as dissipative state variables. In analogy with the original CBM, and in light of evidence from extreme fragmentation in nature, the evolution of the additional shape descriptors is postulated to converge towards an attractor. Comparisons with laboratory experiments, discrete element analyses and particle-scale fracture models illustrate the encouraging performance of the theory. The theory provides insights into the feedback among particle shape, compressive yielding and inelastic deformation in crushable granular continua. These results inspire new questions that should guide future research into crushable granular systems using particle-scale imaging and computations.

36 MATERIALS SCIENCE↗

Asbestos Free Insulation Development for the Space Shuttle Solid Propellant Rocket Motor (RSRM)

Asbestos has been used for many years as an ablation inhibitor in insulating materials. It has been a constituent of the AS/NBR insulation used to protect the steel case of the RSRM (Reusable Solid Rocket Motor) since its inception. This paper discusses the development of a potential replacement RSRM insulation design, several of the numerous design issues that were worked and processing problems that were resolved. The earlier design demonstration on FSM-5 (Flight Support Motor) of the selected 7% and 11% Kevlar(registered) filled EPDM (KF/EPDM) candidate materials was expanded. Full-scale process simulation articles were built and FSM-8 was manufactured using multiple Asbestos Free (AF) components and materials. Two major problems had to be overcome in developing the AF design. First, bondline corrosion, which occurred in the double-cured region of the aft dome, had to be eliminated. Second, KF/EPDM creates high levels of electrostatic energy (ESE), which does not readily dissipate from the insulation surface. An uncontrolled electrostatic discharge (ESD) of this surface energy during many phases of production could create serious safety hazards. Numerous processing changes were implemented and a conductive paint was developed to prevent exposed external insulation surfaces from generating ESE/ESD. Additionally, special internal instrumentation was incorporated into FSM-8 to record real-time internal motor environment data. These data included inhibitor insulation erosion rates and internal thermal environments. The FSM-8 static test was successfully conducted in February 2000 and much valuable data were obtained to characterize the AF insulation design.

Allred, Larry D.↗

From pattern to process: The strategy of the Earth Observing System: Volume 2: EOS Science Steering Committee report

The Earth Observing System (EOS) represents a new approach to the study of the Earth. It consists of remotely sensed and correlative in situ observations designed to address important, interrelated global-scale processes. There is an urgent need to study the Earth as a complete, integrated system in order to understand and predict changes caused by human activities and natural processes. The EOS approach is based on an information system concept and designed to provide a long-term study of the Earth using a variety of measurement methods from both operational and research satellite payloads and continuing ground-based Earth science studies. The EOS concept builds on the foundation of the earlier, single-discipline space missions designed for relatively short observation periods. Continued progress in our understanding of the Earth as a system will come from EOS observations spanning several decades using a variety of contemporaneous measurements.

Source record↗

Nonidealities in Rotating Detonation Engines

A rotating detonation engine (RDE) is a realization of pressure-gain combustion, wherein a traveling detonation wave confined in a chamber provides shock-based compression along with chemical heat release. Due to the high wave speeds, such devices can process high mass flow rates in small volumes, leading to compact and unconventional designs. RDEs involve unsteady and multiscale physics, and their operational characteristics are determined by an equilibrium between large- and small-scale processes. While RDEs can provide a significant theoretical gain in efficiency, achieving this improvement requires an understanding of the multiscale coupling. Specifically, unavoidable nonidealities, such as unsteady mixing, secondary combustion, and multiple competing waves associated with practical designs, need to be understood and managed. The secondary combustion processes arise from fuel/air injection and unsteady and incomplete mixing, and can create spurious losses. In addition, a combination of multiple detonation and secondary waves compete and define the dynamical behavior of mixing, heat release distribution, and the overall mode of operation of the device. This review discusses the current understanding of such nonidealities and describes the tools and techniques used to gain insight into the extreme unsteady environment in such combustors.

33 ADVANCED PROPULSION SYSTEMS↗

Silicon nitride stress-optic microresonator modulator for optical control applications

Modulation-based control and locking of lasers, filters and other photonic components is a ubiquitous function across many applications that span the visible to infrared (IR), including atomic, molecular and optical (AMO), quantum sciences, fiber communications, metrology, and microwave photonics. Today, modulators used to realize these control functions consist of high-power bulk-optic components for tuning, sideband modulation, and phase and frequency shifting, while providing low optical insertion loss and operation from DC to 10s of MHz. In order to reduce the size, weight and cost of these applications and improve their scalability and reliability, modulation control functions need to be implemented in a low loss, wafer-scale CMOS-compatible photonic integration platform. The silicon nitride integration platform has been successful at realizing extremely low waveguide losses across the visible to infrared and components including high performance lasers, filters, resonators, stabilization cavities, and optical frequency combs. Yet, progress towards implementing low loss, low power modulators in the silicon nitride platform, while maintaining wafer-scale process compatibility has been limited. Here we report a significant advance in integration of a piezo-electric (PZT, lead zirconate titanate) actuated micro-ring modulation in a fully-planar, wafer-scale silicon nitride platform, that maintains low optical loss (0.03 dB/cm in a 625 µm resonator) at 1550 nm, with an order of magnitude increase in bandwidth (DC - 15 MHz 3-dB and DC - 25 MHz 6-dB) and order of magnitude lower power consumption of 20 nW improvement over prior PZT modulators. The modulator provides a >14 dB extinction ratio (ER) and 7.1 million quality-factor (Q) over the entire 4 GHz tuning range, a tuning efficiency of 162 MHz/V, and delivers the linearity required for control applications with 65.1 dB·Hz 2/3 and 73.8 dB·Hz 2/3 third-order intermodulation distortion (IMD3) spurious free dynamic range (SFDR) at 1 MHz and 10 MHz respectively. We demonstrate two control applications, laser stabilization in a Pound-Drever Hall (PDH) lock loop, reducing laser frequency noise by 40 dB, and as a laser carrier tracking filter. This PZT modulator design can be extended to the visible in the ultra-low loss silicon nitride platform with minor waveguide design changes. This integration of PZT modulation in the ultra-low loss silicon nitride waveguide platform enables modulator control functions in a wide range of visible to IR applications such as atomic and molecular transition locking for cooling, trapping and probing, controllable optical frequency combs, low-power external cavity tunable lasers, quantum computers, sensors and communications, atomic clocks, and tunable ultra-low linewidth lasers and ultra-low phase noise microwave synthesizers.

Wang, Jiawei (ORCID:0000000257965220)↗

Multiscale Modeling Framework Using Element‐Based Galerkin Methods for Moist Atmospheric Limited‐Area Simulations

This paper presents a multiscale modeling framework (MMF) to model moist atmospheric limited-area weather. The MMF resolves large-scale convection using a coarse grid while simultaneously resolving local features through numerous fine local grids and coupling them seamlessly. Both large- and small-scale processes are modeled using the compressible Navier-Stokes equations within the Nonhydrostatic Unified Model of the Atmosphere (NUMA), and are discretized using a continuous element-based Galerkin method (spectral elements) with high-order basis functions. Consequently, the large-scale and small-scale models share the same dynamical core but have the flexibility to be adjusted individually. The proposed MMF method is tested in 2D and 3D idealized limited-area weather problems involving storm clouds produced by squall line and supercell simulations. Numerical results from the MMF showed enhanced representation of cloud processes compared to the coarse model.

Kang, Soonpil [Naval Postgraduate School, Monterey↗

Solar Activity Modeling: From Subgranular Dynamical Scales to the Solar Cycles

Dynamical effects of solar magnetoconvection span a wide range spatial and temporal scales that extends from the interior to the corona and from fast turbulent motions to the global-Sun magnetic activity. To study the solar activity on short temporal scales (from minutes to hours), we use 3D radiative MHD simulations that allow us to investigate complex turbulent interactions that drive various phenomena, such as plasma eruptions, spontaneous formation of magnetic structures, funnel-like structures and magnetic loops in the corona, and others. In particular, we focus on multi-scale processes of energy exchange across the different layers, which contribute to the corona heating and eruptive dynamics, as well as interlinks between different layers of the solar interior and atmosphere. For modeling the global-scale activity we use the data assimilation approach that has demonstrated great potential for building reliable long-term forecasts of solar activity. In particular, it has been shown that the Ensemble Kalman Filter (EnKF) method applied to the Parker-Kleeorin-Ruzmakin dynamo model is capable of predicting solar activity up to one sunspot cycle ahead in time, as well as estimating the properties of the next cycle a few years before it begins. In this presentation, using the available magnetogram data, we discuss development of the methodology and forecast quality criteria (including forecast uncertainties and sources of errors). We demonstrate the influence of observational limitation on the prediction accuracy. We present the EnKF predictions of the upcoming Solar Cycle 25 based on both the sunspot number series and observed magnetic fields, and discuss the uncertainties and potential of the data assimilation approach for modeling and forecasting the solar activity.

Kitiashvili, I. N.↗

Preliminary simulations of the large-scale environment during the FIRE cirrus IFO

Large scale forcing (scales greater than 500 km) is the dominant factor in the generation, maintenance, and dissipation of cirrus cloud systems. However, the analyses of data acquired during the first Cirrus IFO have highlighted the importance of mesoscale processes (scales of 20 to 500 km) to the development of cirrus cloud systems. Unfortunately, Starr and Wylie found that the temporal and spatial resolution of the standard and supplemental rawinsonde data were insufficient to allow an explanation of all of the mesoscale cloud features that were present on the 27 to 28 Oct. 1986. It is described how dynamic initialization, or 4-D data assimilation (FDDA) can provide a method to address this problem. The first steps towards application of FDDA to FIRE are also described.

Westphal, Douglas L.↗

Remote Sensing from Geostationary Orbit: GEO TROPSAT, A New Concept for Atmospheric Remote Sensing

The Geostationary Tropospheric Pollution Satellite (GEO TROPSAT) mission is a new approach to measuring the critical constituents of tropospheric ozone chemistry: ozone, carbon monoxide, nitrogen dioxide, and aerosols. The GEO TROPSAT mission comprises a constellation of three instruments flying as secondary payloads on geostationary communications satellites around the world. This proposed approach can significantly reduce the cost of getting a science payload to geostationary orbit and also generates revenue for the satellite owners. The geostationary vantage point enables simultaneous high temporal and spatial resolution measurement of tropospheric trace gases, leading to greatly improved atmospheric ozone chemistry knowledge. The science data processing, conducted as a research (not operational) activity, will provide atmospheric trace gas data many times per day over the same region at better than 25 km ground footprint. The high temporal resolution identifies short time scale processes, diurnal variations, seasonal trends, and interannual variation.

Little, Alan D.↗

Acid Exfoliation of Imine‐linked Covalent Organic Frameworks Enables Solution Processing into Crystalline Thin Films

Abstract Covalent organic frameworks (COFs) are highly modular porous crystalline polymers that are of interest for applications such as charge‐storage devices, nanofiltration membranes, and optoelectronic devices. COFs are typically synthesized as microcrystalline powders, which limits their performance in these applications, and their limited solubility precludes large‐scale processing into more useful morphologies and devices. We report a general, scalable method to exfoliate two‐dimensional imine‐linked COF powders by temporarily protonating their linkages. The resulting suspensions were cast into continuous crystalline COF films up to 10 cm in diameter, with thicknesses ranging from 50 nm to 20 μm depending on the suspension composition, concentration, and casting protocol. Furthermore, we demonstrate that the film fabrication process proceeds through a partial depolymerization/repolymerization mechanism, providing mechanically robust films that can be easily separated from their substrates.

Burke, David W.↗

Predicting Antarctic Net Snow Accumulation at the Kilometer Scale and Its Impact on Observed Height Changes

Sub-grid-scale processes occurring at or near the surface of an ice sheet have a potentially large impact on local and integrated net accumulation of snow via redistribution and sublimation. Given observational complexity, they are either ignored or parameterized over large-length scales. Here, we train random forest (RF) models to predict variability in net accumulation over the Antarctic Ice Sheet using atmospheric variables and topographic characteristics as predictors at 1 km resolution. Observations of net snow accumulation from both in situ and airborne radar data provide the input observable targets needed to train the RF models. We find that local net accumulation deviates by as much as 172% of the atmospheric model mean. The correlation in space between the predicted net accumulation variability and satellite-derived surface-height change indicates that surface processes operate differently through time, driven largely by the seasonal anomalies in snow accumulation.

Antarctic↗

Predicting the Evolution of Shallow Cumulus Clouds With a Lotka‐Volterra Like Model

Abstract In numerical weather prediction and climate models, boundary‐layer clouds are controlled by a wide range of subgrid‐scale processes. However, understanding the nature of these processes and their role in the evolution of the cloud size distribution as a whole has been elusive. To address this issue, we adopt a novel empirical framework from the field of population dynamics to model the evolution of cloud size statistics by using the shallow cumulus properties obtained from a large‐eddy simulation (LES). Our approach involves representing the cloud size distribution and the total cloud area using a revised Lotka‐Volterra model and ridge linear model, respectively. The physical interpretation of the total cloud area and coefficients obtained from the optimization of the models reveals three stages probably interpreted by dominant processes: the formation of new clouds, the growth of single clouds, and a steady state with organized transitions involving the growth and decay of multiple clouds. Furthermore, we showcase the potential of this framework to serve as a component of scale‐aware parameterizations of shallow‐convective clouds in atmospheric models.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity of Fine‐Resolution Urban Heat Island Simulations to Soil Moisture Parameterization

ABSTRACT Urban areas experience the impact of natural disasters, such as heatwaves and flash floods, disparately in different neighbourhoods across a city. The demand for precise urban hydrometeorological and hydroclimatological modelling to examine this disparity, and the interacting challenges posed by climate change and urbanisation, has thus surged. The Weather Research and Forecasting (WRF) model has served such operational and research purposes for decades. Recent advancements in WRF, including enhanced numerical schemes and sophisticated urban atmospheric‐hydrological parameterizations, have empowered the simulation of urban geophysical processes at high resolution (~1 km), but even this resolution misses significant urban microclimate variability. This study applies the large‐eddy simulations (LES) mode within WRF, coupled with single‐layer urban canopy models (SLUCM), to enable even finer‐scale modelling (150 m) of the Urban Heat Island (UHI) effect in the Baltimore metropolitan area. We run nine scenarios to evaluate various methods of initializing soil moisture and various spinup lead times, and to assess the impact of WRF's Mosaic approach in depicting subgrid‐scale processes. We evaluate the scenarios by comparing the WRF simulated land surface temperature (LST) against Landsat LST and the WRF simulated hourly 2‐m air temperatures (AT) with observations from eight weather stations across the domain. Results underscore the paramount influence of the lead spinup time on the spatiotemporal distribution of simulated soil moisture, consequently shaping WRF's efficacy in predicting the UHI. Furthermore, interpolating soil moisture‐related parameters from the parent for child domain initialization yields a notable reduction in mean and root‐mean‐squared errors. This improvement was particularly evident in simulations with the longest spinup time, affirming the importance of carefully designing the initialization of soil moisture for improved urban temperature predictions.

Talebpour, Mahdad↗

A Computational Workflow of Elucidating Viral Impact on Mediating Microbial Response to In-situ Experimental Warming: Bridging microbial modeling to carbon and mineral modeling

Viruses are abundant in soils and shape microbial communities in ways that can potentially influence ecosystem processes, yet their contributions to carbon cycling and mineral transformations remain poorly understood. Here we present a multi-phase framework that links virus-host interactions to soil biogeochemistry by combining ecological simulations, genome- and community-scale metabolic modeling, and statistical and machine-learning analyses. We first calibrated microbial abundance profiles under explicit infection scenarios to capture how viral pressure alters community structure, then explored alternative interaction strategies, including kill-the-winner, piggyback-the-winner, and mixed lytic-lysogenic modes, through forward simulations. These ecological shifts were translated into metabolic consequences using exchange fluxes summarized into biologically meaningful categories, while integrated statistical and machine-learning screens elevated subtle but consistent signals. Application of this framework revealed that viral infections shift the balance between organic and inorganic fluxes, redirecting metabolism from diffuse organic transformations toward inorganic pools such as protons and CO 2 , directly linking viral regulation to respiration and soil carbon balance. The roll-up analysis also isolated perturbations in critical mineral ions, including magnesium, manganese, zinc, and copper, which serve as essential enzymatic cofactors. In piggyback-the-winner scenarios, uptake of these ions was strongly suppressed. Contrasting viral strategies produced distinct community structures and metabolic outcomes, from broad suppression under kill-the-winner dynamics to dramatic redistributions under high-lytic and high-gain lysogenic regimes that collapsed vulnerable microbial populations while promoting opportunists. Together, these results provide a tractable path to trace viral perturbations from host abundance shifts to metabolic flux adjustments and ecosystem-scale processes, offering a practical way to include viruses in earth system models.

54 ENVIRONMENTAL SCIENCES↗

Lidar analysis techniques for use in the atmospheric boundary layer

There is a growing body of observational and theoretical evidence which suggests that local climate characteristics are associated with variations in the earth's surface. The link between surface variability and local-scale processes must be made if we are to improve our understanding of the feedback mechanisms involved in surface-atmosphere dynamics. However, to understand these interactions, the surface-atmosphere interface must be studied as a large-scale spatial system. Lidars are ideal tools to study the spatial properties of the atmosphere. The described techniques were developed for use with the Los Alamos Water Raman-Lidar, but are applicable to many other types of lidar. The methodology of the analysis of lidar data is summarized in order to determine meteorological parameters in the atmospheric boundary layer. The techniques are not exhaustive but are intended to show the depth and breadth of the information which can be obtained from lidars. Two methods for the computation of water-vapor fluxes were developed. The first uses the fact that the water vapor concentration in the vertical direction follows a logarithmic profile when corrected for atmospheric stability. The second method involves using inertial dissipation techniques in which lidar-derived spatial and temporal power spectra are used to determine the flux.

Eichinger, William E.↗

WaterTAP 0.3 Release

The Water treatment Technoeconomic Assessment Platform (WaterTAP) is an open-source Python-based software package that supports the simulation and optimization of process-scale water treatment trains. WaterTAP seeks to provide the broader water research community with an integrated modeling capability to evaluate cost, energy, and environmental tradeoffs across water treatment options and identify high impact opportunities for innovation including novel materials, processes, and systems. An updated version of WaterTAP is released quarterly and each includes documentation and release notes.

IDAES↗