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At least 1,333 records · Page 74

Magnetohydrodynamic simulations preliminarily predict the habitability and radio emission of TRAPPIST-1e

TRAPPIST-1e, an Earth-sized exoplanet in the habitable zone of the nearby M dwarf TRAPPIST-1, may experience magnetospheric responses that vary with stellar space weather, which could potentially influence both its habitability and radio emissions. Our objective is to investigate how different Earth-like magnetospheric configurations of TRAPPIST-1e – specifically variations in dipolar magnetic field strength and axial tilt – respond to diverse stellar space weather conditions, including events analogous to coronal mass ejections (CMEs), and to assess their implications for potential habitability and expected radio emissions. We conducted 3D magnetohydrodynamic simulations of the TRAPPIST-1e system using the PLUTO code in spherical coordinates. The planetary magnetic field was modelled as dipolar, with equatorial strengths from Earth-like to several times stronger. The dipole axis spans a representative range of axial tilts. We investigate four stellar wind environments, from sub-Alfvénic flow to CME-like disturbances. Planetary shielding was quantified based on the magnetopause standoff distance, and radio powers were estimated via empirical scaling laws. Our simulations show that both shielding and radio power depend strongly on the magnetic configuration. Stronger fields increase protection, while larger tilts reduce it. Radio power increases with both field strength and tilt across all wind regimes. An Earth-like magnetic field can provide effective shielding even under intense CMEs, whereas high tilts require stronger fields. Predicted radio powers reach ~10 20 erg s −1 during CMEs, making bursts from close-in, magnetised planets more detectable. However, for TRAPPIST-1e, the maximum cyclotron frequency lies below the Earth’s ionospheric cutoff (~10 MHz), making ground-based detection currently infeasible.

Sun: magnetic fields↗

Convolutional Non-Homogeneous Poisson Process and its Application to Wildfire Ignition Risk Quantification for Power Delivery Networks

To quantify wildfire ignition risks on power delivery networks, the current practice predominantly relies on the empirically calculated fire danger indices, which may not well capture the effects of dynamically changing environmental factors. This article proposes a spatio-temporal point process model, known as the Convolutional Non-homogeneous Poisson Process (cNHPP), and applies the model to quantify wildfire ignition risks for power delivery networks. The proposed model captures both the current (i.e., instantaneous) and cumulative (i.e., historical) effects of key environmental processes (i.e., covariates) on wildfire risks, as well as the spatio-temporal dependency among different segments of the power delivery network. The computation and interpretation of the intensity function are thoroughly investigated. We apply the proposed approach to estimate wildfire ignition risks on major transmission lines in California, using historical fire data, meteorological and vegetation data obtained from the National Oceanic and Atmospheric Administration and National Aeronautics and Space Administration. Here, a comprehensive comparison study is performed to show the applicability and predictive capability of the proposed approach.

Non-homogeneous Poisson Process↗

Towards fully predictive gyrokinetic full- f simulations: validation and triangularity studies in TCV

Designing economical magnetic confinement fusion power plants motivates computational tools that can estimate plasma behavior from engineering parameters without direct reliance on experimental measurement of the plasma profiles. In this work, we present full-f global long-wavelength gyrokinetic simulations of edge and scrape-off layer turbulence in tokamaks that use only magnetic geometry, heating power, and particle inventory as inputs. Unlike many modeling approaches that employ free parameters fitted to experimental data, raising uncertainties when extrapolating to reactor scales. This approach directly simulates turbulence and resulting profiles through gyrokinetics without such empirical adjustments. This is achieved via an adaptive sourcing algorithm in Gkeyll that strictly controls energy injection and emulates particle sourcing due to neutral recycling. We show that the simulated kinetic profiles compare reasonably well with Thomson scattering and Langmuir probe data for Tokamak á Configuration Variable (TCV) discharge #65125, and that the simulations reproduce characteristic features such as blob transport and self-organized electric fields. Applying the same framework to study triangularity effects suggests mechanisms contributing to the improved confinement reported for negative triangularity (NT). Simulations of TCV discharges #65125 and #65130 indicate that NT increases the E x B flow shear (by about 20% in these cases), which correlates with reduced turbulent losses and a modest change in the distribution of power exhaust to the vessel wall. While the physical models contain approximations that can be refined in future work, the predictive capability demonstrated here, evolving multiple profile relaxation times with kinetic electron and ion models in hundreds of GPU hours, indicates the feasibility of using Gkeyll to support design studies of fusion devices.

Hoffmann, Antoine Cyril David [Princeton Plasma Ph↗

Hybrid Oscillator-Qubit Quantum Processors: Instruction Set Architectures, Abstract Machine Models, and Applications

This tutorial offers a pedagogical guide to hybrid quantum processors that integrate discrete-variable (DV) qubits and continuous-variable (CV) oscillators. Aimed at computer scientists, engineers, and physicists, it provides an overview of the experimental, algorithmic, and architectural aspects of this novel and rapidly developing hardware model. Experimental realizations of this model include superconducting, trapped-ion, and neutral-atom platforms. By combining DV and CV components, hybrid oscillator-qubit processors enable a powerful new paradigm that offers complementary strengths for quantum control, error correction, computation, and simulation. Working toward the goal of a full-stack system connecting applications to CV-DV hardware, we define and formulate abstract machine models and instruction set architectures. These essential abstractions enable codesign of hardware and software, and resource estimation for exploring the potential of current and future hardware for computational and simulation tasks. Using these abstractions, we present both new and existing examples that illustrate the benefits of hybrid CV-DV processors relative to traditional DV-only hardware in computation as well as quantum simulation of physical models. Examples include algorithms for transferring states between DV and CV systems, performing the quantum Fourier transform, and simulation of lattice gauge theories. Relative to qubit-only hardware, the bosonic degrees of freedom natively available in hybrid architectures can substantially reduce the circuit complexity of simulations for physical models containing bosons. A key technique is the extension of quantum signal processing ideas to CV-DV systems. This work is intended to serve as a timely and comprehensive guide to this relatively unexplored yet promising approach to quantum computation and to provide a road map to guide future development.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Blinded challenge for precision cosmology with large-scale structure: Results from effective field theory for the redshift-space galaxy power spectrum

An accurate theoretical template for the galaxy power spectrum is key for the success of ongoing and future spectroscopic surveys. We examine to what extent the effective field theory (EFT) of large-scale structure is able to provide such a template and correctly estimate cosmological parameters. To that end, we initiate a blinded challenge to infer cosmological parameters from the redshift-space power spectrum of high-resolution mock catalogs mimicking the BOSS galaxy sample but covering a 100 times larger cumulative volume. This gigantic simulation volume allows us to separate systematic bias due to theoretical modeling from the statistical error due to sample variance. The challenge is to measure three unknown input parameters used in the simulation: the Hubble constant, the matter density fraction, and the clustering amplitude. We present analyses done by two independent teams, who have fitted the mock simulation data generated by yet another independent group. This allows us to avoid any confirmation bias by analyzers and to pin down possible tuning of the specific EFT implementations. Both independent teams have recovered the true values of the input parameters within subpercent statistical errors corresponding to the total simulation volume.

79 ASTRONOMY AND ASTROPHYSICS↗

Improving Signal-to-Noise Ratio (SNR) for Readout Signals Using Adaptive Filters on Reconfigurable Controls Hardware

This study investigates the optimization of Signal-to-Noise Ratio (SNR) in superconducting quantum computing readout signals through adaptive filtering. Quantum computing technology has the potential to revolutionize various fields by delivering exponential speedup in solving certain computational problems. However, the technology's practical implementation is hindered by the difficulty of extracting clean, reliable signals during the readout phase, with various sources of noise presenting a significant barrier to clean signals. This noise, often present in readout profiles due to imperfect isolation, degrades the system's overall SNR, thus impeding the ability to extract the quantum state accurately. The research leverages the power of adaptive filtering to improve the SNR of quantum computing readout signals. Specifically, an adaptive filter is implemented in a PYNQ overlay on an FPGA, and eventually will be connected to a quantum computing system. The system models the n oise with a Least Mean Squares (LMS) adaptive filter, and then subtracts the estimated noise from the received signal to improve the SNR. A Direct Memory Access (DMA) channel is used to handle the signal processing, delivering efficient, high-speed data transfer between the PYNQ system and the hardware. The study explores the benefits of this adaptive filtering technique, potentially providing a significant contribution to practical and fast quantum computing.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

System Study: High-Pressure Core Spray 1998-2022

This report presents an unreliability evaluation of the high-pressure core spray (HPCS) at eight U.S. commercial operating boiling water reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10-year period while yearly estimates for system unreliability are provided for the entire active period. Statistically significant increasing trends were identified in both the HPCS system start-only unreliability and 8-hour mission unreliability.

99 GENERAL AND MISCELLANEOUS↗

System Study: High-Pressure Coolant Injection 1998-2022

This report presents an unreliability evaluation of the high-pressure coolant injection (HPCI) system at 22 U.S. commercial operating boiling water reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the HPCI results.

99 GENERAL AND MISCELLANEOUS↗

System Study: Emergency Power System 1998-2022

This report presents an unreliability evaluation of the emergency power system (EPS) at 93 U.S. commercial operating nuclear reactors. New Standardized Plant Analysis Risk (SPAR) models with the most recent SPAR parameter update results were used in this report. Demand, run hour, and failure data from 1998–2022 for selected components were obtained from the Institute of Nuclear Power Operations Industry Reporting and Information System. The unreliability results are trended for the most recent 10 year period while yearly estimates for system unreliability are provided for the entire active period. No statistically significant increasing or decreasing trends were identified in the industry-wide estimates of EPS system start-only unreliability, but a highly statistically significant decreasing trend was identified in the industry-wide estimates of EPS system 8-hour mission unreliability.

99 GENERAL AND MISCELLANEOUS↗

General-Purpose Bayesian Tensor Learning With Automatic Rank Determination and Uncertainty Quantification

A major challenge in many machine learning tasks is that the model expressive power depends on model size. Low-rank tensor methods are an efficient tool for handling the curse of dimensionality in many large-scale machine learning models. The major challenges in training a tensor learning model include how to process the high-volume data, how to determine the tensor rank automatically, and how to estimate the uncertainty of the results. While existing tensor learning focuses on a specific task, this paper proposes a generic Bayesian framework that can be employed to solve a broad class of tensor learning problems such as tensor completion, tensor regression, and tensorized neural networks. We develop a low-rank tensor prior for automatic rank determination in nonlinear problems. Our method is implemented with both stochastic gradient Hamiltonian Monte Carlo (SGHMC) and Stein Variational Gradient Descent (SVGD). We compare the automatic rank determination and uncertainty quantification of these two solvers. We demonstrate that our proposed method can determine the tensor rank automatically and can quantify the uncertainty of the obtained results. We validate our framework on tensor completion tasks and tensorized neural network training tasks.

Bayesian inference↗

Modeling, Load Profile Validation, and Assessment of Solar-Rooftop Energy Potential for Low-and-Moderate-Income Communities in the Caribbean

This document presents the modeling of load profile consumption for Low-and-Moderate-Income (LMI) communities in the Caribbean Islands, as well as an assessment of the solar-rooftop energy potential. In this work, real data, together with synthetic and electricity bill data, were collected to validate and improve the load profile models. The solar-rooftop energy potential was obtained through a National Renewable Energy Laboratory (NREL) software called the PVWatts calculator, and mathematical analysis. The analysis of rooftop solar energy potential was conducted to enable the minimum size of solar power systems to fit the energy demand in the community. The results obtained allow estimation of the capacity of the energy system for each house or an entire community.

14 SOLAR ENERGY↗

Relationships between the Stellar, Gaseous, and Star Formation Disks in LITTLE THINGS Dwarf Irregular Galaxies: Indirect Evidence for Substantial Fractions of Dark Molecular Gas

The stellar, gaseous and young stellar disks in the LITTLE THINGS sample of nearby dwarf irregular galaxies are fitted with functions to search for correlations between the parameters. We find that the H i radial profiles are generally flatter in the center and fall faster in the outer regions than the V-band profiles, while young stars are more centrally concentrated, especially if the H i is more centrally flat. This pattern suggests that the H i is turning into molecules in the center, and the molecular clouds are forming stars and FUV. A model that assumes the molecular surface density is proportional to the total gas surface density to a power of 1.5 or 2, in analogy with the Kennicutt–Schmidt relation, reproduces the relationship between the ratio of the visible to the H i scale length and the H i Sérsic index. The molecular fraction is estimated as a function of radius for each galaxy by converting the FUV to a molecular surface density using conventional calibrations. The average molecular fraction inside 3R {sub D} is 23% ± 17%. However, the break in the stellar surface brightness profile has no unified tracer related to star formation.

74 ATOMIC AND MOLECULAR PHYSICS↗

Ionosphere total electron measurements as extracted from satellite tracking data

The Goddard Range and Range Rate System (GRARR) determines the range of a spacecraft by measuring the group delay of a modulated wave and the range rate by measuring the Doppler phase shift of the carrier. An analytical technique is presented for obtaining corrections and equivalent total electron content along the vertical, using VHF GRARR data and a radial model of the ionosphere. The results of computation for a representative pass are given, and estimated accuracy is discussed from a statistical view point. Using VHF GRARR data and a radial model of the ionosphere. The results of computation for a representative pass are given, and estimated accuracy is discussed from a statistical view point. Using GRARR range, range rate, and angle tracking data from Explorer 41, values of total electron content on the order of 10 to the 17th to 10 to the 18th power (electrons/sq m) were obtained. These values agree with estimates of the total electron content from ionospheric profiles using f sub o F sub 2 predict data.

Murray, C. W., Jr.↗

Laser Doppler systems in atmospheric turbulence

The loss of heterodyne signal power for the Marshall Space Flight Center laser Doppler system due to the random changes in the atmospheric index of refraction is investigated. The current status in the physics of low energy laser propagation through turbulent atmosphere is presented. The analysis and approximate evaluation of the loss of the heterodyne signal power due to the atmospheric absorption, scattering, and turbulence are estimated for the conditions of the January 1973 flight tests. Theoretical and experimental signal to noise values are compared. Maximum and minimum values of the atmospheric attenuation over a two way path of 20 km range are calculated as a function of altitude using models of atmosphere, aerosol concentration, and turbulence.

Murty, S. S. R.↗

X-ray satellite (Rosat)

An overview of the current status of the ROSAT X-Ray satellite project is given. Areas discussed include an overview of problem areas, systems and mechanical subsystems, the electrical subsystem, power supply, data processing and transmission, the wide field camera, ground support equipment and the production scheduling. It is shown that the project is proceeding according to schedule, including the hardware production and costs. However, it is stated that estimated additional costs will exceed the plan. The previous schedule for production of the flight model will no longer be met. A modified milestone plan has been worked out with Dornier Systems. The current working schedule calls for a launch data of December 21, 1987; however, this does not take into account a 4-week buffer prior to transporting the flight model to the launch site. As of the date of this report, milestone M5 has been met. Previous problems with the gold vapor deposition on the flight model mirror due to contamination have been eliminated.

Source record↗

Microtopographic evolution of lava flows at Cima volcanic field, Mojave Desert, California

Microtopographic profiles were measured and power spectra calculated for dated lava flow surfaces at Cima volcanic field in the eastern Mojave Desert of California in order to quantify changes in centimeter- to meter-scale roughness as a function of age. For lava flows younger than about 0.8 m.y., roughness over all spatial scales decreases with age, with meter-scale roughness decreasing slightly more than centimeter scales. Flows older than about 0.8 m.y. show a reversal of this trend, becoming as rough as young flows at these scales. Modeling indicates that eolian deposition can explain most of the change observed in the offset, or roughness amplitude, of power spectra of flow surface profiles up to 0.8 m.y. Other processes, such as rubbing and stone pavement development, appear to have a minor effect in this age range. Changes in power spectra of surfaces older than about 0.8 m.y. are consistent with roughening due to fluvial dissection. These results agree qualitatively with a process-response model that attributes systematic changes in flow surface morphology to cyclic changes in the rates of eolian, soil formation, and fluvial processes. Identification of active surficial processes and estimation of the extent of their effects, or stage of surficial evolution, through measurement of surface roughness will help put the correlation of surficial units on a quantitative basis. This may form the basis for the use of radar remote sensing data to help in regional correlations of surficial units.

Farr, Tom G.↗

Time-dependent reliability analysis of ceramic engine components

The computer program CARES/LIFE calculates the time-dependent reliability of monolithic ceramic components subjected to thermomechanical and/or proof test loading. This program is an extension of the CARES (Ceramics Analysis and Reliability Evaluation of Structures) computer program. CARES/LIFE accounts for the phenomenon of subcritical crack growth (SCG) by utilizing either the power or Paris law relations. The two-parameter Weibull cumulative distribution function is used to characterize the variation in component strength. The effects of multiaxial stresses are modeled using either the principle of independent action (PIA), the Weibull normal stress averaging method (NSA), or the Batdorf theory. Inert strength and fatigue parameters are estimated from rupture strength data of naturally flawed specimens loaded in static, dynamic, or cyclic fatigue. Two example problems demonstrating proof testing and fatigue parameter estimation are given.

Nemeth, Noel N.↗

ROSAT HRI and ASCA Observations of the Spiral Galaxy NGC 6946 and its Northeast Complex of Luminous Supernova Remnants

Analysis of 80 ks ASCA (Advanced Satellite for Cosmology and Astrophysics) and 60 ks ROSAT HRI (High Resolution Image) observations of the face-on spiral galaxy NGC 6946 are presented. The ASCA image is the first observation of this galaxy above approximately 2 keV. Diffuse emission may be present in the inner approximately 4' extending to energies above approximately 2-3 keV. In the HRI data, 14 pointlike sources are detected, the brightest two being a source very close to the nucleus and a source to the northeast that corresponds to a luminous complex of interacting supernova remnants (SNRs). We detect a point source that lies approximately 30" west of the SNR complex but with a luminosity -1115 of the SNR complex. None of the point sources show evidence of strong variability; weak variability would escape our detection. The ASCA spectrum of the SNR complex shows evidence for an emission line at approximately 0.9 keV that could be either Ne IX at approximately 0.915 keV or a blend of ion stages of Fe L-shell emission if the continuum is fitted with a power law. However, a two-component, Raymond-Smith thermal spectrum with no lines gives an equally valid continuum fit and may be more physically plausible given the observed spectrum below 3 keV. Adopting this latter model, we derive a density for the SNR complex of 10-35 cm(exp -3), consistent with estimates inferred from optical emission-line ratios. The complex's extraordinary X-ray luminosity may be related more to the high density of the surrounding medium than to a small but intense interaction region where two of the complex's SNRs are apparently colliding.

Schlegel, E.↗