Distribution of Seed Electron Phase Space Density Minima in Earth's Radiation Belts
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A. Y. Drozdov↗
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Results for “density distribution”
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A catalogue of cataclysmic variables from 20 yr of the Sloan Digital Sky Survey with new classifications, periods, trends, and oddities
ABSTRACT We present a catalogue of 507 cataclysmic variables (CVs) observed in SDSS I to IV including 70 new classifications collated from multiple archival data sets. This represents the largest sample of CVs with high-quality and homogeneous optical spectroscopy. We have used this sample to derive unbiased space densities and period distributions for the major sub-types of CVs. We also report on some peculiar CVs, period bouncers and also CVs exhibiting large changes in accretion rates. We report 70 new CVs, 59 new periods, 178 unpublished spectra, and 262 new or updated classifications. From the SDSS spectroscopy, we also identified 18 systems incorrectly identified as CVs in the literature. We discuss the observed properties of 13 peculiar CVS, and we identify a small set of eight CVs that defy the standard classification scheme. We use this sample to investigate the distribution of different CV sub-types, and we estimate their individual space densities, as well as that of the entire CV population. The SDSS I to IV sample includes 14 period bounce CVs or candidates. We discuss the variability of CVs across the Hertzsprung–Russell diagram, highlighting selection biases of variability-based CV detection. Finally, we searched for, and found eight tertiary companions to the SDSS CVs. We anticipate that this catalogue and the extensive material included in the Supplementary Data will be useful for a range of observational population studies of CVs.
79 ASTRONOMY AND ASTROPHYSICS↗
Resurrecting hot dark matter - Large-scale structure from cosmic strings and massive neutrinos
These are the results of a numerical simulation of the formation of large-scale structure from cosmic-string loops in a universe dominated by massive neutrinos (hot dark matter). This model has several desirable features. The final matter distribution contains isolated density peaks embedded in a smooth background, producing a natural bias in the distribution of luminous matter. Because baryons can accrete onto the cosmic strings before the neutrinos, the galaxies will have baryon cores and dark neutrino halos. Galaxy formation in this model begins much earlier than in random-phase models. On large scales the distribution of clustered matter visually resembles the CfA survey, with large voids and filaments.
Scherrer, Robert J.↗
Measures of distance from a randomly located point to neighboring lattice points for rectangular and hexagonal point lattices Technical report no. 3
Probability density function and distribution function of distance from random point in polygon to the nearest corner in lattice
PROBABILITY DENSITY↗
Experimental plasma studies
The rate coefficients for the reactions C(+) + e(-) + e(-) yields C + e(-) and CO(+) + e(-) yields C + O were measured over the electron temperature range of approximately 1500 deg K to 7000 deg K. The measurements were performed in CO that had expanded from equilibrium reservoir conditions of 7060 deg K at 17.3 atm pressure and from 6260 deg K at 10.0 atm pressure. Two RAM flight probes were used to measure electron density and electron temperature in the expanding flow of a shock tunnel. Experiments were performed in the inviscid flow with both probes and in the nozzle-wall boundary layer with the constant bias-voltage probe. The distributions of electron density and electron temperature were independently measured using voltage-swept thin-wire probes. Thin-wire Langmuir probes were also used to measure the electron-density and electron-temperature distributions in the boundary layer of a sharp flat plate located on the nozzle centerline. Admittance measurements were performed with the RAM C and RAM C-C S-band antennas in the presence of an ionized boundary layer.
Dunn, M. G.↗
Brightness, density, and color profiles of three globular clusters - NGC 6440, 6541, and 7099
Using short-exposure SEC television camera observations, the radial distribution profiles of surface brightness, B-V colors and star densities are determined in three globular clusters, NGC 6440, 6541 and 7099, from about 2-200 arc sec from the cluster centers. Good agreement is found between the surface-brightness profiles and the star-density distributions; both can be fitted well with a King-type curve, and no significant evidence for a presence of cusp at r greater then 3 arc sec is observed. Also determined for the three clusters were central surface brightnesses, core radii, central mass densities, total cluster masses, relaxation times and central escape velocities. In addition, an upper limit of 5000 solar masses is placed on the mass of a possible central black hole in these clusters.
Williams, T. B.↗
Explainable AI classification for parton density theory
Quantitatively connecting properties of parton distribution functions (PDFs, or parton densities) to the theoretical assumptions made within the QCD analyses which produce them has been a longstanding problem in HEP phenomenology. To confront this challenge, we introduce an ML-based explainability framework, XAI4PDF, to classify PDFs by parton flavor or underlying theoretical model using ResNet-like neural networks (NNs). By leveraging the differentiable nature of ResNet models, this approach deploys guided backpropagation to dissect relevant features of fitted PDFs, identifying x-dependent signatures of PDFs important to the ML model classifications. By applying our framework, we are able to sort PDFs according to the analysis which produced them while constructing quantitative, human-readable maps locating the x regions most affected by the internal theory assumptions going into each analysis. This technique expands the toolkit available to PDF analysis and adjacent particle phenomenology while pointing to promising generalizations.
Artificial Intelligence↗
Microwave technique measures plasma characteristics
Plasma electron density and temperature distribution are measured by passing a high frequency millimeter wave through plasma. Variations in density and temperature are determined by measuring insertion loss as the plasma travels between the microwave transmitting and receiving antennas.
Leonard, W. F.↗
Adaptive Sampling for In Situ Cloud Probe (Final Report)
Clouds play a leading role in the Earth's global energy and solar radiation balance and hydrological cycle. Improving cloud models requires detailed information on the cloud microphysical properties, such as droplet size distribution and number density, liquid water content and cloud composition (droplets, ice particles), which can only be provided by aerial in situ measurements. However, for many atmospheric measurement instruments, the lack of flexibility in selecting the operational mode during operation can lead to uncertainties in sampling and measurement characteristics under continuously varying atmospheric conditions. This SBIR project is developing an advanced, compact optical imaging technology for in situ characterization of cloud hydrometeors. The development involves a deep modification of the existing Mesa Photonics’ Cloud Droplet Measurement System (CDMS) in order to implement real-time automatic adaptive sampling based on the acquired in situ data and environmental parameters. The new system, CDMS-2, implements two measurement modes: side-scatter imaging for smaller hydrometeors and direct bright-field-illumination imaging for larger hydrometeors in a significantly larger sample volume. The system measures the droplet size distribution (DSD) and number density with an added capability of discriminating between liquid water and ice hydrometeors (based on polarization-resolved side-scatter imaging). The instrument will implement automatic switching or alternating between the regular side-scatter imaging mode and sparse/large hydrometeor mode (based on the acquired data). Other adaptive sampling capabilities include variable sample volume and dynamic range (based on the measured DSD). The preferred deployment platforms are uncrewed aircraft systems (UAS) and tethered balloon/kite systems (TBS). The Phase I project achieved (or exceeded) the goals listed in the Work Plan. A CDMS-2 laboratory prototype implementing the polarization-resolved side-scatter imaging mode and direct bright-field-illumination imaging mode was designed and built. Additional capabilities included the variable illumination pulse energy and sample volume. The smallest detectable droplet diameter was improved to 3–4 μm (from the nominal 10 μm value specified for the original CDMS). Discrimination between water droplets and ice particles was experimentally demonstrated. The Phase I prototype was extensively tested and calibrated in the laboratory and also tested in the Pi Cloud Chamber at Michigan Technological University (MTU). The two intensive experimental campaigns at MTU provided unique opportunities of testing the CDMS-2 laboratory prototype under realistic warm and mixed-phase cloud conditions (stable for long periods of time), testing different sampling modes and intercomparing the CDMS-2 prototype to other co-located cloud characterization instruments. The Phase I project successfully demonstrated the feasibility of the proposed technology and identified the engineering challenges of designing a field deployable prototype instrument in Phase II. The Phase I study provides a solid basis for development, characterization and field-testing of the proposed advanced cloud probe with adaptive sampling in Phase II followed by commercialization of the technology in Phase III.
47 OTHER INSTRUMENTATION↗
Probabilistic Modeling of the Renal Stone Formation Module
The Integrated Medical Model (IMM) is a probabilistic tool, used in mission planning decision making and medical systems risk assessments. The IMM project maintains a database of over 80 medical conditions that could occur during a spaceflight, documenting an incidence rate and end case scenarios for each. In some cases, where observational data are insufficient to adequately define the inflight medical risk, the IMM utilizes external probabilistic modules to model and estimate the event likelihoods. One such medical event of interest is an unpassed renal stone. Due to a high salt diet and high concentrations of calcium in the blood (due to bone depletion caused by unloading in the microgravity environment) astronauts are at a considerable elevated risk for developing renal calculi (nephrolithiasis) while in space. Lack of observed incidences of nephrolithiasis has led HRP to initiate the development of the Renal Stone Formation Module (RSFM) to create a probabilistic simulator capable of estimating the likelihood of symptomatic renal stone presentation in astronauts on exploration missions. The model consists of two major parts. The first is the probabilistic component, which utilizes probability distributions to assess the range of urine electrolyte parameters and a multivariate regression to transform estimated crystal density and size distributions to the likelihood of the presentation of nephrolithiasis symptoms. The second is a deterministic physical and chemical model of renal stone growth in the kidney developed by Kassemi et al. The probabilistic component of the renal stone model couples the input probability distributions describing the urine chemistry, astronaut physiology, and system parameters with the physical and chemical outputs and inputs to the deterministic stone growth model. These two parts of the model are necessary to capture the uncertainty in the likelihood estimate. The model will be driven by Monte Carlo simulations, continuously randomly sampling the probability distributions of the electrolyte concentrations and system parameters that are inputs into the deterministic model. The total urine chemistry concentrations are used to determine the urine chemistry activity using the Joint Expert Speciation System (JESS), a biochemistry model. Information used from JESS is then fed into the deterministic growth model. Outputs from JESS and the deterministic model are passed back to the probabilistic model where a multivariate regression is used to assess the likelihood of a stone forming and the likelihood of a stone requiring clinical intervention. The parameters used to determine to quantify these risks include: relative supersaturation (RS) of calcium oxalate, citrate/calcium ratio, crystal number density, total urine volume, pH, magnesium excretion, maximum stone width, and ureteral location. Methods and Validation: The RSFM is designed to perform a Monte Carlo simulation to generate probability distributions of clinically significant renal stones, as well as provide an associated uncertainty in the estimate. Initially, early versions will be used to test integration of the components and assess component validation and verification (V&V), with later versions used to address questions regarding design reference mission scenarios. Once integrated with the deterministic component, the credibility assessment of the integrated model will follow NASA STD 7009 requirements.
kidney stones↗
Theory and Simulation of Self- and Mutual-Diffusion of Carrier Density and Temperature in Semiconductor Lasers
Carrier diffusion and thermal conduction play a fundamental role in the operation of high-power, broad-area semiconductor lasers. Restricted geometry, high pumping level and dynamic instability lead to inhomogeneous spatial distribution of plasma density, temperature, as well as light field, due to strong light-matter interaction. Thus, modeling and simulation of such optoelectronic devices rely on detailed descriptions of carrier dynamics and energy transport in the system. A self-consistent description of lasing and heating in large-aperture, inhomogeneous edge- or surface-emitting lasers (VCSELs) require coupled diffusion equations for carrier density and temperature. In this paper, we derive such equations from the Boltzmann transport equation for the carrier distributions. The derived self- and mutual-diffusion coefficients are in general nonlinear functions of carrier density and temperature including many-body interactions. We study the effects of many-body interactions on these coefficients, as well as the nonlinearity of these coefficients for large-area VCSELs. The effects of mutual diffusions on carrier and temperature distributions in gain-guided VCSELs will be also presented.
Li, Jian-Zhong↗
Atomistic Insight into Cation Effects on Binding Energies in Cu-Catalyzed Carbon Dioxide Reduction
Electrolyte properties in general and electrolyte ions in particular have been shown to have significant effects on the kinetics of electrochemical CO 2 and CO reduction at metal electrodes, but these effects have not yet been fully understood. Here, we investigate the effects of cations at the aqueous electrolyte–Cu(211) interface on adsorbate binding energies and the electrolyte structure using density functional theory (DFT). Charging the interface via explicit Na + has systematic effects on adsorbate–electrolyte interactions and conformations. We describe specific local adsorbate–ion interactions, including direct alkali ion–adsorbate coordination and hydrogen bonding via ion-coordinated water molecules. The relative importance of these specific interactions and purely electrostatic field–adsorbate interactions is investigated by comparing the DFT-calculated ion effects to those predicted by purely electrostatic models of the interface and the adsorbates. We find that the trend in ion effects among different adsorbates at constant surface charge density is well explained by a purely electrostatic interaction model. The binding energy of OCCHO is found to depend strongly on the surface charge density as well as the spatial distribution of ions at constant surface charge density. These effects are also explained by a purely electrostatic local electrostatic field–adsorbate model. This indicates that alkali ion effects can be mainly attributed to purely electrostatic field interactions and that the local field at ion-stabilized active sites can depend significantly on both the overall charge density and on the spatial distribution of ions at constant charge density. This work provides new insight on alkali ion effects on a variety of adsorbates relevant to the CO 2 and CO reduction reactions by describing specific local ion–adsorbate interactions, systematic changes in adsorbate–electrolyte interactions induced by explicit surface charge, and comparisons of the calculated effects on binding energies to simple electrostatic field–adsorbate models to explain trends among various adsorbates and at varying surface charge densities and supercell configurations.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
The global wind system in the thermosphere.
The upper atmosphere wind distribution is calculated by solving the Navier-Stokes equations with models of upper atmospheric densities and ion distribution. All non-linear terms and viscous terms are included. It is found that the velocities from the non-linear solutions are smaller than those obtained from a linear treatment and that in the equatorial region the magnitude of the average meridional velocity is strongly dependent upon the latitudinal coupling. No appreciable super-rotation is obtained by the inclusion of the nonlinear terms; the small value of the average zonal velocity is mainly due to the ion distribution.
Blum, P. W.↗
A model for the spatial and energy distributions of energetic neutral atoms produced within the Saturn/Titan plasma system
A model for the production of energetic neutral atoms (ENAs) in the Saturn/Titan system, that takes into account existing data on the spatial distribution of the background neutral density, the energy and spatial distributions of the energetic ions, and the energy dependence of the charge-exchange cross sections, is presented. Hydrogen production via H(+), H is presented in detail. The extended Saturn/Titan system is 'imaged' in energetic neutral H at 66 R(s) and 25-deg latitude. From this vantage point, the energetic H flux is 6 + or - 1 H/sq cm per sec between 10 and 100 keV. Comparing the predicted H spectrum with that observed by Kirsch et al. (1981), the production of neutral O is estimated, and it is concluded that O(+), H charge exchange in the inner magnetosphere is sufficient to account for all the ENA O production.
Hsieh, K. C.↗
Electron-impact vibrational relaxation in high-temperature nitrogen
Vibrational relaxation process of N2 molecules by electron-impact is examined for the future planetary entry environments. Multiple-quantum transitions from excited states to higher/lower states are considered for the electronic ground state of the nitrogen molecule N2 (X 1Sigma-g(+)). Vibrational excitation and deexcitation rate coefficients obtained by computational quantum chemistry are incorporated into the 'diffusion model' to evaluate the time variations of vibrational number densities of each energy state and total vibrational energy. Results show a non-Boltzmann distribution of number densities at the earlier stage of relaxation, which in turn suppresses the equilibrium process but affects little the time variation of total vibrational energy. An approximate rate equation and a corresponding relaxation time from the excited states, compatible with the system of flow conservation equations, are derived. The relaxation time from the excited states indicates the weak dependency of the initial vibrational temperature. The empirical curve-fit formula for the improved e-V relaxation time is obtained.
Lee, Jong-Hun↗
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations
Cloud microphysics are inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensemble (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e.,pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bin model explicitly calculates and allows for the examination of both the mass and number concentration of species in each size categor, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fewer droplets, larger sized develop due to the greater condensational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.
Tao, Wei-Kuo↗
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-Resolving Model Simulations
Cloud microphysics are inevitable affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distribution parameterized as spectral bin microphysics are needed to explicitly study the effect of atmospheric aerosol concentration on cloud development, rainfall production, and rainfall rates convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembel (GCE) model. The formulation for the explicit spectral-bim microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e., pristine ice crystals (columnar and plate-like), snow (dendrites and aggregates), groupel and frozen drops/hall] Each type is described by a special size distribution function containing many categories (i.e., 33 bins). Atmospheric aerosols are also described using number density size-distribution functions.A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep cloud systems in the west Pacific warm pool region and in the mid-latitude using identical thermodynamic conditions but with different concentrations of CCN: a low "clean" concentration and a high "dirty" concentration. Besides the initial differences in aerosol concentration, preliminary results indicate that the low CCN concentration case produces rainfall at the surface sooner than the high CCN case but has less cloud water mass aloft. Because the spectral-bim model explicitly calculates and allows for the examination of both the mass and number concentration of cpecies in each size category, a detailed analysis of the instantaneous size spectrum can be obtained for the two cases. It is shown that since the low CCN case produces fever droplets, larger size develop due to greater condencational and collectional growth, leading to a broader size spectrum in comparison to the high CCN case.
Tao, Wei-Kuo↗
The Impact of Aerosols on Cloud and Precipitation Processes: Cloud-resolving Model Simulations
Cloud microphysics is inevitably affected by the smoke particle (CCN, cloud condensation nuclei) size distributions below the clouds. Therefore, size distributions parameterized as spectral bin microphysics are needed to explicitly study the effects of atmospheric aerosol concentration on cloud development, r d a U production, and rainfall rates for convective clouds. Recently, two detailed spectral-bin microphysical schemes were implemented into the Goddard Cumulus Ensembe1 (GCE) model. The formulation for the explicit spectral-bin microphysical processes is based on solving stochastic kinetic equations for the size distribution functions of water droplets (i.e., cloud droplets and raindrops), and several types of ice particles [i.e. pristine ice crystals (columnar and platelike), snow (dendrites and aggregates), graupel and frozen drops/hail]. Each type is described by a special size distribution function containing many categories (i.e. 33 bins). Atmospheric aerosols are also described using number density size-distribution functions. A spectral-bin microphysical model is very expensive from a computational point of view and has only been implemented into the 2D version of the GCE at the present time. The model is tested by studying the evolution of deep tropical clouds in the west Pacific warm pool region and in the mid-latitude continent with different concentrations of CCN: a low "c1ean"concentration and a high "dirty" concentration. In addition, differences and similarities between bulk microphysics and spectral-bin microphysical schemes will be examined and discussed.
Tao, Wei-Kuo↗