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At least 1,747 records · Page 97

Killing the cMSSM softly

We investigate the constrained Minimal Supersymmetric Standard Model (cMSSM) in the light of constraining experimental and observational data from precision measurements, astrophysics, direct supersymmetry searches at the LHC and measurements of the properties of the Higgs boson, by means of a global fit using the program Fittino. As in previous studies, we find rather poor agreement of the best fit point with the global data. We also investigate the stability of the electro-weak vacuum in the preferred region of parameter space around the best fit point.We find that the vacuum is metastable, with a lifetime significantly longer than the age of the Universe. For the first time in a global fit of supersymmetry, we employ a consistent methodology to evaluate the goodness-of-fit of the cMSSM in a frequentist approach by deriving p values from large sets of toy experiments. We analyse analytically and quantitatively the impact of the choice of the observable set on the p value, and in particular its dilution when confronting the model with a large number of barely constraining measurements. Lastly, for the preferred sets of observables, we obtain p values for the cMSSM below 10 %, i.e. we exclude the cMSSM as a model at the 90 % confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Extraterrestrial halogen and sulfur contents of the stratosphere

Interplanetary dust represents a potential source of environmentally important chemical species in the earth's atmosphere. Previous studies have used computational models of atmospheric evolution of meteor debris to conclude that the steady-state stratospheric component of extraterrestrial matter is a small fraction of the total aerosol load. Observational data suggest such calculations may underestimate stratospheric residence times and, thus, concentrations. Two computational methods were employed here to obtain reasonable limits for the stratospheric contents of halogens and sulfur from extraterrestrial sources. The lower limit was based on the total stratospheric aerosol load and the relative influxes from interplanetary dust and tropospheric sources. The upper limit was obtained using a viscous settling method. These results suggest that the steady-state extraterrestrial influxes of halogens are minor compared to tropospheric sources but the sulfur input may be comparable to the present observed stratospheric content. Temporal enhancements in the meteoroid flux, such as passage through comet debris lanes or impact by large bodies, may produce significant chemical perturbations in the atmosphere.

Sutton, S. R.↗

Shock heating of the solar wind plasma

The role played by shocks in heating solar-wind plasma is investigated using data on 413 shocks which were identified from the plasma and magnetic-field data collected between 1973 and 1982 by Pioneer and Voyager spacecraft. It is found that the average shock strength increased with the heliocentric distance outside 1 AU, reaching a maximum near 5 AU, after which the shock strength decreased with the distance; the entropy of the solar wind protons also reached a maximum at 5 AU. An MHD simulation model in which shock heating is the only heating mechanism available was used to calculate the entropy changes for the November 1977 event. The calculated entropy agreed well with the value calculated from observational data, suggesting that shocks are chiefly responsible for heating solar wind plasma between 1 and 15 AU.

Whang, Y. C.↗

Radio emission from coronal and interplanetary shocks

Observational data on coronal and interplanetary (IP) type II burst events associated with shock-wave propagation are reviewed, with a focus on the past and potential future contributions of space-based observatories. The evidence presented by Cane (1983 and 1984) in support of the hypothesis that the coronal (metric) and IP (kilometric) bursts are due to different shocks is summarized, and the fast-drift kilometric events seen at the same time as metric type II bursts (and designated shock-accelerated or shock-associated events) are characterized. The need for further observations at 0.5-20 MHz is indicated.

Cane, H. V.↗

COOL CORE CLUSTERS FROM COSMOLOGICAL SIMULATIONS

We present results obtained from a set of cosmological hydrodynamic simulations of galaxy clusters, aimed at comparing predictions with observational data on the diversity between cool-core (CC) and non-cool-core (NCC) clusters. Our simulations include the effects of stellar and active galactic nucleus (AGN) feedback and are based on an improved version of the smoothed particle hydrodynamics code GADGET-3, which ameliorates gas mixing and better captures gas-dynamical instabilities by including a suitable artificial thermal diffusion. In this Letter, we focus our analysis on the entropy profiles, the primary diagnostic we used to classify the degree of cool-coreness of clusters, and the iron profiles. In keeping with observations, our simulated clusters display a variety of behaviors in entropy profiles: they range from steadily decreasing profiles at small radii, characteristic of CC systems, to nearly flat core isentropic profiles, characteristic of NCC systems. Using observational criteria to distinguish between the two classes of objects, we find that they occur in similar proportions in both simulations and observations. Furthermore, we also find that simulated CC clusters have profiles of iron abundance that are steeper than those of NCC clusters, which is also in agreement with observational results. We show that the capability of our simulations to generate a realistic CC structure in the cluster population is due to AGN feedback and artificial thermal diffusion: their combined action allows us to naturally distribute the energy extracted from super-massive black holes and to compensate for the radiative losses of low-entropy gas with short cooling time residing in the cluster core.

79 ASTRONOMY AND ASTROPHYSICS↗

Local density maxima - Progenitors of structure

Beginning with a short review of the observational data and of some previous theoretical ideas and numerical simulations, the question is addressed of how the large-scale structure that emerges around local density maxima depends on the nature of the primordial density perturbations field. The density contrast profile around local maxima is given, to a good approximation, by the primordial two-point correlation function. The mean number density of objects of a given core mass is calculated as a function of the primordial power spectrum, p(k). In an open universe, rich clusters should have halos steeper than galactic haloes. The observed structure is found to be consistent with omega-sub-zero less than 1.0 and n = -1.

Hoffman, Y.↗

Observation and theory of the barium releases from the CRRES satellite

The relationship between releases of barium from the NASA Combined Release and Radiation Effects Satellite (CRRES) and enhanced auroral activity is discussed with reference to observational data. Barium releases were conducted at a variety of altitudes and injection velocities, and plasma irregularities are reported as a result of the interactions. Auroral activity increased within 5 min of each release, and references are made to the effects on diamagnetic cavities, bulk ion motion, and stimulated electron and ion precipitation. Artificially created structured diamagnetic cavities are noted for each release, plasma waves are generated by the high-speed ion clouds, and enhanced ionization is found in the critical ionization-velocity process. Barium releases are effective in stimulating electron precipitation, and the observed irregularities are related to cycloid bunching of the initial ion distributions.

Bernhardt, P. A.↗

High-z objects and cold dark matter cosmogonies - Constraints on the primordial power spectrum on small scales

Modified cold dark matter (CDM) models were recently suggested to account for large-scale optical data, which fix the power spectrum on large scales, and the COBE results, which would then fix the bias parameter, b. We point out that all such models have deficit of small-scale power where density fluctuations are presently nonlinear, and should then lead to late epochs of collapse of scales M between 10 exp 9 - 10 exp 10 solar masses and (1-5) x 10 exp 14 solar masses. We compute the probabilities and comoving space densities of various scale objects at high redshifts according to the CDM models and compare these with observations of high-z QSOs, high-z galaxies and the protocluster-size object found recently by Uson et al. (1992) at z = 3.4. We show that the modified CDM models are inconsistent with the observational data on these objects. We thus suggest that in order to account for the high-z objects, as well as the large-scale and COBE data, one needs a power spectrum with more power on small scales than CDM models allow and an open universe.

Kashlinsky, A.↗

Buoyancy Effects on Concurrent Flame Spread Over Thick PMMA

The flammability of combustible materials in a spacecraft is important for fire safety applications because the conditions in spacecraft environments differ from those on earth. Experimental testing in space is difficult and expensive. However, reducing buoyancy by decreasing ambient pressure is a possible approach to simulate on-earth the burning behavior inside spacecraft environments. The objective of this work is to determine that possibility by studying the effect of pressure on concurrent flame spread, and by comparison with microgravity data, observe up to what point low-pressure can be used to replicate flame spread characteristics observed in microgravity. Specifically, this work studies the effect of pressure and microgravity on upward/concurrent flame spread over 10 mm thick polymethyl methacrylate (PMMA) slabs. Experiments in normal gravity were conducted over pressures ranging between 100 and 40 kPa and a forced flow velocity of 200 mm/s. Microgravity experiments were conducted during NASA’s Spacecraft Fire Experiment (Saffire II), on board the Cygnus spacecraft at 100 kPa with an air flow velocity of 200 mm/s. Results show that reductions of pressure slow down the flame spread over the PMMA surface approaching that in microgravity. The data is correlated in terms of a non-dimensional mixed convection analysis that describes the convective heat transferred from the flame to the solid, and the primary mechanism controlling the spread of the flame. The extrapolation of the correlation to low pressures predicts well the flame spread rate obtained in microgravity in the Saffire II experiments. Similar results were obtained by the authors with similar experiments with a thin composite cotton/fiberglass fabric (published elsewhere). Both results suggest that reduced pressure can be used to approximately replicate flame behavior of untested gravity conditions for the burning of thick and thin solids. This work could provide guidance for potential ground-based testing for fire safety design in spacecraft and space habitats.

Environmental conditions↗

Modeling of streamflow in a 30 km long reach spanning 5 years using OpenFOAM 5.x

Abstract. Developing accurate and efficient modeling techniques for streamflow at the tens-of-kilometers spatial scale and multi-year temporal scale is critical for evaluating and predicting the impact of climate- and human-induced discharge variations on river hydrodynamics. However, achieving such a goal is challenging because of limited surveys of streambed hydraulic roughness, uncertain boundary condition specifications, and high computational costs. We demonstrate that accurate and efficient three-dimensional (3-D) hydrodynamic modeling of natural rivers at 30 km and 5-year scales is feasible using the following three techniques within OpenFOAM, an open-source computational fluid dynamics platform: (1) generating a distributed hydraulic roughness field for the streambed by integrating water-stage observation data, a rough wall theory, and a local roughness optimization and adjustment strategy; (2) prescribing the boundary condition for the inflow and outflow by integrating precomputed results of a one-dimensional (1-D) hydraulic model with the 3-D model; and (3) reducing computational time using multiple parallel runs constrained by 1-D inflow and outflow boundary conditions. Streamflow modeling for a 30 km long reach in the Columbia River (CR) over 58 months can be achieved in less than 6 d using 1.1 million CPU hours. The mean error between the modeled and the observed water stages for our simulated CR reach ranges from −16 to 9 cm (equivalent to approximately ±7 % relative to the average water depth) at seven locations during most of the years between 2011 and 2019. We can reproduce the velocity distribution measured by the acoustic Doppler current profiler (ADCP). The correlation coefficients of the depth-averaged velocity between the model and ADCP measurements are in the range between 0.71 and 0.83 at 75 % of the survey cross sections. With the validated model, we further show that the relative importance of dynamic pressure versus hydrostatic pressure varies with discharge variations and topography heterogeneity. Given the model's high accuracy and computational efficiency, the model framework provides a generic approach to evaluate and predict the impacts of climate- and human-induced discharge variations on river hydrodynamics at tens-of-kilometers and decadal scales.

58 GEOSCIENCES↗

Propagation mechanism of daytime Pc 3-4 pulsations observed at synchronous orbit and multiple ground-based stations

Observational data obtained during the last two decades show that the amplitude of daytime Pc 3-4 magnetic pulsations is controlled by the solar wind conditions. The high degree of correlation between the solar wind parameters and Pc 3-4 pulsations in the dayside magnetosphere suggests that the ultimate cause of the daytime Pc 3-4 pulsations must be the interaction of the solar wind with the earth's magnetosphere. The present paper is concerned with details regarding the control of the properties of the Pc 3-4 pulsations by the solar wind parameters, taking into account observations made at multiple ground-based stations. It is attempted to establish the relation between the daytime Pc 3-4 pulsations at the ground stations and the compressional Pc 3-4 waves in the magnetosphere. Attention is given to the most probable propagation mechanism of the daytime Pc 3-4 pulsations in the magnetosphere.

Yumoto, K.↗

Fast and Scalable FFT-Based GPU-Accelerated Algorithms for Block-Triangular Toeplitz Matrices with Application to Linear Inverse Problems Governed by Autonomous Dynamical Systems

In this work, we present an efficient and scalable algorithm for performing matrix-vector multiplications (matvecs) for block Toeplitz matrices. Such matrices, which are shift-invariant with respect to their blocks, arise in the context of solving inverse problems governed by autonomous systems, and time-invariant systems in particular. In this article, we consider inverse problems that infer unknown parameters from observational data of a linear time-invariant dynamical system given in the form of partial differential equations (PDEs). Matrix-free Newton-conjugate-gradient methods are often the gold standard for solving these inverse problems, but they require numerous actions of the Hessian on a vector. Matrix-free adjoint-based Hessian matvecs require solution of a pair of linearized forward/adjoint PDE solves per Hessian action, which may be prohibitive for large-scale inverse problems. Time invariance of the forward PDE problem leads to a block Toeplitz structure of the discretized parameter-to-observable (p2o) map defining the mapping from inputs (parameters) to outputs (observables) of the PDEs. This block Toeplitz structure enables us to exploit two key properties: (1) compact storage of the p2o map and its adjoint, and (2) efficient fast Fourier transform–based Hessian matvecs. The proposed algorithm is mapped onto large multi-GPU clusters and achieves more than 80% of peak bandwidth on NVIDIA A100 GPUs. Excellent weak scaling is shown for up to 48 A100 GPUs. For the targeted problems, the implementation executes Hessian matvecs within fractions of a second, which is orders of magnitude faster than can be achieved by conventional matrix-free Hessian matvecs via forward/adjoint PDE solves.

97 MATHEMATICS AND COMPUTING↗

Heating the sun's lower transition region with fine-scale electric currents

Analytical and observational data are presented to show that the lower transition zone, a 100 km thick region at 10,000-200,000 K between the solar chromosphere and corona, is heated by local electric currents. The study was spurred by correlations between the enhanced atmospheric heating and magnetospheric flux in the chromospheric network and active regions. Field aligned current heated flux loops are asserted to mainly reside in and make up most of the transition region. It is shown that thermal conduction from the sides of hot gas columns generated by the current dissipation is the source of the observed temperature distribution in the transition regions.

Rabin, D.↗

Attributing Historical Changes in Probabilities of Record-Breaking Daily Temperature and Precipitation Extreme Events

Here, we describe two unprecedented large (100-member), longterm (61-year) ensembles based on MRI-AGCM3.2, which were driven by historical and non-warming climate forcing. These ensembles comprise the "Database for Policy Decision making for Future climate change (d4PDF)". We compare these ensembles to large ensembles based on another climate model, as well as to observed data, to investigate the influence of anthropogenic activities on historical changes in the numbers of record-breaking events, including: the annual coldest daily minimum temperature (TNn), the annual warmest daily maximum temperature (TXx) and the annual most intense daily precipitation event (Rx1day). These two climate model ensembles indicate that human activity has already had statistically significant impacts on the number of record-breaking extreme events worldwide mainly in the Northern Hemisphere land. Specifically, human activities have altered the likelihood that a wider area globally would suffer record-breaking TNn, TXx and Rx1day events than that observed over the 2001- 2010 period by a factor of at least 0.6, 5.4 and 1.3, respectively. However, we also find that the estimated spatial patterns and amplitudes of anthropogenic impacts on the probabilities of record-breaking events are sensitive to the climate model and/or natural-world boundary conditions used in the attribution studies.

54 ENVIRONMENTAL SCIENCES↗

Assessing shellfish water exposure to fecal bacteria pollution in Salish Sea: three-dimensional modeling and implications for monitoring

Fecal bacteria (FB) contamination poses significant risks to shellfish safety and management in coastal and estuarine waters. Despite extensive pollution identification and correction efforts, FB contamination in shellfish-growing areas persists in the Salish Sea, highlighting the need to identify overlooked sources and better understand FB transport from riverine and shoreline inputs to shellfish beds. To address this, a high-resolution three-dimensional hydrodynamic model coupled with FB kinetics was developed and applied to a case study site in Salish Sea—Portage Bay—to simulate freshwater plume circulation, flushing dynamics, and bacterial transport. Daily FB loading from the major freshwater inflow—Nooksack River was generated by both linear interpolation and integrating a machine learning approach (XGBoost), trained on historical hydrological and meteorological data. The model successfully reproduced both the magnitude and seasonal variation of FB concentrations in Portage Bay for the year of 2021, demonstrating that simplified FB kinetics with first-order decay due to mortality was effective in this dynamic coastal environment with short flushing time. Model results identified the Nooksack River as the dominant far-field FB source, while scenario simulations showed that near-field coastal stormwater outfalls elevated local FB levels following rainfall, particularly under low-flow conditions. The XGBoost prediction provided comparable or superior accuracy to linear interpolation, particularly during periods of missing observational data, by capturing short-term variability and event-driven loading more effectively. Integrating data-driven riverine FB inputs with mechanistic coastal numerical modeling provides a robust framework for operational forecasting of shellfish bed exposure risk and supports adaptive monitoring and management of shellfish growing areas in the Salish Sea and similar coastal systems.

Salish Sea↗

The role of the dark matter distribution in the structure formation

We review the most important ingredients that compose the halo model of structure formation, emphasizing on the role played by the density profile of dark matter (DM). The theoretical predictions of the so-called warm DM (WDM) and cold DM (CDM) cosmologies at small scales are discussed in terms of recent numerical simulations and current observational data coming from rotation curves of galaxies. We elaborate on the recently introduced Ruffini-Argüelles-Rueda (RAR) DM profile, which is obtained from the configuration of equilibrium of a self-gravitating system of massive fermions, hereafter “inos”, and show that it can be a good candidate for WDM. A significant insight for this model might be inferred based on the analytical approach of the halo model, pointing out that there might have signals of quantum cores of galaxies on the non-linear matter power spectrum at small scales, which are however unfortunately inaccessible today with the current observational instruments. Upcoming surveys could test in the future the quantum features of galactic cores.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantifying the Dynamics of Protein Self-Organization Using Deep Learning Analysis of Atomic Force Microscopy Data

The dynamics of protein self-assembly on the inorganic surface and the resultant geometric patterns are visualized using high-speed atomic force microscopy. The time dynamics of the classical macroscopic descriptors such as 2D fast Fourier transforms, correlation, and pair distribution functions are explored using the unsupervised linear unmixing, demonstrating the presence of static ordered and dynamic disordered phases and establishing their time dynamics. Here, the deep learning (DL)-based workflow is developed to analyze detailed particle dynamics and explore the evolution of local geometries. Finally, we use a combination of DL feature extraction and mixture modeling to define particle neighborhoods free of physics constraints, allowing for a separation of possible classes of particle behavior and identification of the associated transitions. Overall, this work establishes the workflow for the analysis of the self-organization processes in complex systems from observational data and provides insight into the fundamental mechanisms.

36 MATERIALS SCIENCE↗

Estimation of hydraulic conductivity in a watershed using sparse multi-source data via Gaussian process regression and Bayesian experimental design

Enhanced water management systems depend on accurate estimation of subsurface hydraulic properties. However, geologic formations can vary significantly, so information from a single source (e.g., widely spaced boreholes) is insufficient in characterizing subsurface aquifer properties. Therefore, multiple sources of information are needed to complement the hydrogeology understanding of a region. Here, this study presents a numerical framework in which information from different measurement sources is combined to characterize the 3D random field in a multi-fidelity prediction model. Coupled with the model, a Bayesian experimental design was used to determine the best future sampling locations. The Upper Sangamon watershed in east-central Illinois was selected as the case study site, where the multi-fidelity Gaussian process model was used to estimate the hydraulic conductivity in the region of interest. Multi-source observation data were obtained from electrical resistivity and borehole pumping tests. The accuracy of the model prediction is dependent on the locations and the distribution of both high- and low-fidelity data. Furthermore, the multi-fidelity model was compared with the single-fidelity model. The uncertainties and confidence in the measurements and parameter estimates were quantified and used to design future cycles of data collection to further improve the confidence intervals.

54 ENVIRONMENTAL SCIENCES↗