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At least 1,729 records · Page 96

Short-term cyclic variations and diurnal variations of the Venus upper atmosphere

The vertical structure of the nighttime thermosphere and exosphere of Venus was discussed. A comparison of the day and nighttime profiles indicates, contrary to the model of Dickinson and Riley (1977), that densities (principally atomic oxygen) dropped sharply from day to night. It was suggested either that the lower estimates were related to cooler exospheric temperatures at night or that the atomic bulge was flatter than expected at lower altitudes. Large periodic oscillations, in both density and inferred exospheric temperatures, were detected with periods of 5 to 6 days. The possibility that cyclic variations in the thermosphere and stratosphere were caused by planetary-scale waves, propagated upward from the lower atmosphere, was investigated using simultaneous temperature measurements obtained by the Venus radiometric temperature experiment (VORTEX). Inferred exospheric temperatures in the morning were found to be lower than in the evening as if the atmosphere rotated in the direction of the planet's rotation, similar to that of earth. Superrotation of the thermosphere and exosphere was discussed as a possible extension of the 4-day cyclic atmospheric rotation near the cloud tops.

Keating, G. M.↗

Physics consistent machine learning framework for inverse modeling with applications to ICF capsule implosions

In high energy density physics (HEDP) and inertial confinement fusion (ICF), predictive modeling is complicated by uncertainty in parameters that characterize various aspects of the modeled system, such as those characterizing material properties, equation of state (EOS), opacities, and initial conditions. Typically, however, these parameters are not directly observable. What is observed instead is a time sequence of radiographic projections using X-rays. In this work, we define a set of sparse hydrodynamic features derived from the outgoing shock profile and outer material edge, which can be obtained from radiographic measurements, to directly infer such parameters. Our machine learning (ML)-based methodology involves a pipeline of two architectures, a radiograph-to-features network (R2FNet) and a features-to-parameters network (F2PNet), that are trained independently and later combined to approximate a posterior distribution for the parameters from radiographs. We show that the machine learning architectures are able to accurately infer initial conditions and EOS parameters, and that the estimated parameters can be used in a hydrodynamics code to obtain density fields, shocks, and material interfaces that satisfy thermodynamic and hydrodynamic consistency. Finally, we demonstrate that features resulting from an unknown EOS model can be successfully mapped onto parameters of a chosen analytical EOS model, implying that network predictions are learning physics, with a degree of invariance to the underlying choice of EOS model. To the best of our knowledge, our framework is the first demonstration of recovering both thermodynamic and hydrodynamic consistent density fields from noisy radiographs.

97 MATHEMATICS AND COMPUTING↗

A structure function representation theorem with applications to frequency stability estimation

Random processes with stationary nth differences serve as models for oscillator phase noise. A theorem which obtains the structure function (covariance of the nth differences) of such a process in terms of the differences of a single function of one time variable is proven. In turn, this function can easily be obtained from the spectral density of the process. The theorem is used for computing the variance of two estimators of frequency stability.

Greenhall, C. A.↗

A structure function representation theorem with applications to frequency stability estimation

Random processes with stationary nth differences serve as models for oscillator phase noise. The theorem proved here allows one to obtain the structure function (covariances of the nth differences) of such a process in terms of the differences of a single function of one time variable. In turn, this function can easily be obtained from the spectral density of the process. The theorem is used for computing the variance of two estimators of frequency stability.

Greenhall, C. A.↗

Near-infrared observations of IRAS sources in and near dense cores

We report 0.4 to 20 micron photometry of 27 Infrared Astronomy Satellite (IRAS) point sources associated with dense cores in nearby dark clouds. It is found that these objects have a bimodal distribution of spectral slopes. The objects in the group with steep spectral slopes are typically within one half power radius of the core peak and are not visible on the POSS. The remainder of the objects are typically further from their cores, are optically visible and have shallow spectral slopes (s is approximately 0.6). Most of the sources in this group which have been previously identified are T Tauri stars. Both the groups of objects have essentially the same luminosity function with median luminosity of 1 to 2 L(solar), which is similiar to the luminosity function for T Tauri stars. The near-infrared (J,H,K,L) colors of the objects have been used to estimate the visual extinction to the stars. This indicates that the typical steep spectrum source has extinction A(upsilon) of approximately 30 magnitudes, which is larger by a factor of 3 to 4 than a uniform core can provide, thus the density must rise steeply in the vicinity of the star. For those objects where optical estimates of the extinction are available the optical estimates are typically smaller than our IR estimates by a factor of 1.6. For multiple scattering by grains that scatter primarily in the forward direction, this implies a grain albedo of 0.4 at V, consistent with theoretical predictions for bare grains. Using this derived extinction, the FIR emission from a spherical shell with an inverse power law density which contributes the correct amount of extinction has been modelled. It is shown that to be consistent with both the observations of the density of the core at a scale of 1.5 x 10(17) cm and the extinction derived from the near-IR colors there must be a circumstellar hole of radius 10-100 A.U. for all density laws with exponents greater than 1.2. It is also shown that a component in addition to the star and circumstellar shell is necessary to match the observed spectrum of steep spectrum sources.

Fuller, G. A.↗

MME-based attitude dynamics identification and estimation for SAMPEX

A method is described for obtaining optimal attitude estimation algorithms for spacecraft lacking attitude rate measurement devices (rate gyros), and then demonstrated using actual flight data from the Solar, Anomalous, and Magnetospheric Particle Explorer (SAMPEX) spacecraft. SAMPEX does not have on-board rate sensing, and relies on sun sensors and a three-axis magnetometer for attitude determination. Problems arise since typical attitude estimation is accomplished by filtering measurements of both attitude and attitude rates. Rates are nearly always sampled much more densely than are attitudes. Thus, the absence/loss of rate data normally reduces both the total amount of data available and the sampling density (in time) by a substantial fraction. As a result, the sensitivity of the estimates to model uncertainty and to measurement noise increases. In order to maintain accuracy in the attitude estimates, there is increased need for accurate models of the rotational dynamics. The proposed approach is based on the minimum model error (MME) optimal estimation strategy, which has been successfully applied to estimation of poorly modeled dynamic systems which are relatively sparsely and/or noisily measured. The MME estimates may be used to construct accurate models of the system dynamics (i.e. perform system model identification). Thus, an MME-based approach directly addresses the problems created by absence of attitude rate measurements.

Depena, Juan↗

Systematic Effects in Galaxy-Galaxy Lensing with DESI

The Dark Energy Spectroscopic Instrument (DESI) survey will measure spectroscopic redshifts for millions of galaxies across roughly $14,000 \, \mathrm{deg}^2$ of the sky. Cross-correlating targets in the DESI survey with complementary imaging surveys allows us to measure and analyze shear distortions caused by gravitational lensing in unprecedented detail. In this work, we analyze a series of mock catalogs with ray-traced gravitational lensing and increasing sophistication to estimate systematic effects on galaxy-galaxy lensing estimators such as the tangential shear $\gamma_{\mathrm{t}}$ and the excess surface density $\Delta\Sigma$ . We employ mock catalogs tailored to the specific imaging surveys overlapping with the DESI survey: the Dark Energy Survey (DES), the Hyper Suprime-Cam (HSC) survey, and the Kilo-Degree Survey (KiDS). Among others, we find that fiber incompleteness can have significant effects on galaxy-galaxy lensing estimators but can be corrected effectively by up-weighting DESI targets with fibers by the inverse of the fiber assignment probability. Similarly, we show that intrinsic alignment and lens magnification are expected to be statistically significant given the precision forecasted for the DESI year-1 data set. Our study informs several analysis choices for upcoming cross-correlation studies of DESI with DES, HSC, and KiDS.

79 ASTRONOMY AND ASTROPHYSICS↗

Dense clumps of ionized gas near Pi Scorpii, as revealed by the fine-structure excitation of N II

The column density and the emission of the ionized gas along the line of sight toward the B1 V + B2 V binary star Pi Sco are measured on the basis of the fine-structure absorption lines of the ground state N II. It is found that the bulk of this ionized gas must be clumped on a length scale of 0.025 pc, which is far smaller than the observed size of the diffuse H II region surrounding Pi Sco of about 6 pc. The observed column density of S III toward Pi Sco yields an upper limit on the distance of the absorbing, clumped gas from the star of less than about 0.02 pc, assuming that both the N II and S III absorption arise from the same gas. The possibility that the ionized gas originates from a photoevaporating circumstellar disk directly surrounding Pi Sco is excluded, since such a disk would have an unusual size of order 0.025 pc and would have had to survive for the estimated age of Pi Sco of 5-8 Myr. The derived mean density of the clumped gas is of order 40/cu cm, so that the gas is at a pressure that far exceeds the mean pressure in the H II region. It is concluded that the ionized gas could originate from evaporation flows off a cluster of compact neutral objects that evaporate due to the ionizing radiation of Pi Sco.

Bertoldi, Frank↗

The kinetic temperature and CH3CCH column density profiles in SGR B2, Orion, and Dr 21

Kinetic temperatures, T(kin), are presently estimated by means of a technique employing the intensities of the adjacent rotational transitions of symmetric top molecules, under the assumptions that the metastable levels are thermalized, and that the excitation temperature connecting the upper level of the observed transition to the lowest level in the K ladder is the same for the both adjacent transitions. The method is applied to observations of the J = 5-4 and J = 6-5 transitions of CH3CCH obtained at 1-arcmin intervals along a NS-EW cross that centered on Orion KL, Sgr B2, and Dr 21. The technique's application to CH3CN lines from the central positions of Sgr B2 and Orion produces T(kin) values that are in good agreement with other determinations. The fact that these lines are broader than those of CH3CCH is interpreted in terms of a model in which CH3CN emission is confined to small and warm core region while CH3CCH emission is dominated by a more extensive, almost isothermal and cooler halo region in Orion KL and Sgr B2.

Churchwell, E.↗

K-shell radiation and bright spot characteristics of high-energy-density Fe-Cr-Ni plasmas influenced by X-pinch load geometry

K-shell radiation is diagnostically advantageous for the study of high-energy-density plasmas. Here, the current work investigates the influence of load geometry on K-shell x-rays in Z-pinch plasmas produced on the 1-MA Zebra generator. Stainless steel (Fe: 69%, Cr: 20%, Ni: 9%) X-pinch wire loads are fielded with an interwire angle of 31° (small-angle) or 62.5° (large-angle), respectively and studied using various x-ray diode, imaging, and spectroscopic diagnostics. The large-angle geometry produced large, individual x-ray-emitting bright spots (> 3 keV) at the wire cross-point averaging areas ≥ 1 mm 2 , with noteworthy soft x-ray (> 0.75 keV) bursts and radiation yields ≤ 14.6 kJ. The small-angle geometry produced multiple x-ray-emitting bright spots extending the pinch axis with smaller average sizes (≤ 0.5 mm 2 ), consistent with stronger current, increased radiation yield (≥ 15.5 kJ), and notable hard x-ray (> 9 keV) bursts, which peak with largest cumulative bright spot size. Spectroscopic analysis is performed with non-LTE collisional-radiative modeling, indicating a cold, nonthermal plasma region radiating from neutral to Ne-like ions, a hot, thermal region radiating from Fe and Cr He- and Li-like ions, and an intermediate region radiating Kα satellites from Li-like to O-like ions. Modeling of the nonthermal and satellite features imply a fractional hot electron abundance ~0.1% and ~0.5% for large- and small-angle geometries, respectively. Relative intensity analysis is performed on Heα and Kα lines, revealing intensity ratios that deviate from the original wire composition. Optical depth estimates allude to optically thick, thermal K-shell plasmas with densities consistent with non-LTE modeling.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Logical shadow tomography: Efficient estimation of error-mitigated observables

We introduce a technique to estimate error-mitigated expectation values on noisy quantum computers. Our technique performs shadow tomography on a logical state to produce a memory-efficient classical reconstruction of the noisy density matrix. Using efficient classical post-processing, one can mitigate errors by projecting into the codespace as in subspace expansion and taking powers of the density matrix as in virtual distillation. Relative to subspace expansion which requires Ω (2^((n-1)k) samples to estimate a Pauli observable with an [[n; k]] stabilizer code, our technique requires only Ө(2^k) samples. Relative to virtual distillation, our technique can compute powers of the density matrix without implementing additional copies of quantum states the quantum computer. We present numerical results using logical states encoded with up to sixty physical qubits and show fast convergence to error-free expectation values with only 10^5 samples under 1% depolarizing noise.

quantum computing↗

Ultraviolet observations of cool stars. VII - Local interstellar hydrogen and deuterium Lyman-alpha

High-resolution Copernicus spectra of Epsilon Eri and Epsilon Ind containing interstellar hydrogen and deuterium L-alpha absorption lines are presented, reduced, and analyzed. Parameters of the interstellar hydrogen and deuterium toward these two stars are derived independently, without any assumptions concerning the D/H ratio. Copernicus spectra of Alpha Aur and Alpha Cen A are reanalyzed, and limits on the D/H number-density ratio consistent with the data for all four stars are considered. A comparison of the present estimates for the parameters of the local interstellar medium with those obtained by other techniques shows that there is no compelling evidence for significant variations in the hydrogen density and D/H ratio in the local interstellar medium. On this basis the hypothesis of an approaching local interstellar cloud proposed by Vidal-Madjar et al. (1978) is rejected

Mcclintock, W.↗

Spatial Correlation Structures in SMAP Near-Surface Soil Moisture (How Spatially Correlated are the Temporal Variations of Soil Moisture at Different Locations? and Why Is This of Interest?)

Spatial correlation structures can describe the degree to which soil moisture at a specified location co-varies in time with that at other, remote locations. Using four years of warm season SMAP Level 2 near-surface soil moisture data, we compute these spatial correlation structures for points across North America. The character of these structures is seen to differ geographically; the structures found for the west-central US, for example, are significantly more spatially extensive. We then demonstrate how these structures can potentially be used to reconstruct soil moisture fields during the pre-SMAP era. In this exercise, we consider as "truth" the soil moistures produced in a long-term offline land surface model simulation (1980-2014) that utilizes precipitation forcing based on a high density of precipitation gauges. Then, for a given location within the continent, we construct an"estimated" soil moisture time series based solely on historical soil moisture information simulated at least 300 km distant from the location, using the SMAP-based spatial correlation structures to determine how to make best use of the remote information. The reconstructed soil moistures are found to have significant skill relative to the assumed truth, suggesting that the same approach, when applied in areas of low rain gauge density (i.e., in areas for which historically simulated soil moistures are necessarily inaccurate), could provide useful historical soil moisture estimates through the SMAP-guided extraction of relevant information from neighboring gauged regions.

Koster, Randal↗

Studies of laser stimulated photodetachment from nanoparticles for particle charge measurements

Determining nanoparticle charge is more challenging than that for microparticles due to change in the particle size during the synthesis substantial plasma property variations, and difficulties in visualizing individual particles, rendering conventional microparticle charge diagnostics ineffective in dusty plasma. In this work, we utilized laser-stimulated photodetachment (LSPD) to deduce the mean charge of nanoparticles. Nanoparticles were grown in an Ar/C 2 H 2 mixture using a capacitively coupled RF discharge and the LSPD induced changes in the electron current monitored by a cylindrical Langmuir probe. LSPD signals were obtained and analyzed across different dust growth phases. The prolonged decay of electron current pulses was attributed to the presence of residual negative ions, caused by the effective electrostatic trapping of these ions and the potential post—LSPD re-formation of new ones. The particle charge was estimated by combining the laser-stimulated photodetachment signal from the probe with the dust density obtained from laser-light extinction using the measured nanoparticle size distribution. For a nanoparticles size range of approximately 100–250 nm and mean diameter of $d$ p ∼154.37 nm, the effective mean charge was estimated to be $\langle$$Q$$\rangle$ d $≈$ 37 elementary charge units. The measured charge values are lower than those predicted by orbital motion limited theory, which may be attributed to significant electron depletion in the nanodusty plasma. LSPD results in Ar/C 2 H 2 nano-dusty plasma confirm the applicability of this method for estimating individual nanoparticle charges. However, it has also been demonstrated that electron detachment from residual background negative ions can influence the detachment current decay and must be carefully considered.

dust particle charge↗

Development of a Model for the Small-Particle Orbital Debris Population Based on the STS Impact Record

In preparation for the release of the Orbital Debris Engineering Model (ORDEM) version 3.1, the NASA Orbital Debris Program Office (ODPO) revisited how orbiting debris populations of characteristic sizes smaller than 1 cm were modeled. The primary contributor to the population of sub-centimeter debris particles is the surface deterioration or erosion of spacecraft materials exposed to the outer-space environment. Because small particulates are not directly trackable by remote sensing, the primary means of detection is via historical counts of small impact features on flown radiator and window surfaces of the U.S. Space Transportation System (STS, also known as the Space Shuttle) from 1995-2011. Historic NASA studies of high-velocity impact tests have related impact-feature size to particle mass and velocity for certain STS surfaces, so that a corresponding particle size may be inferred from each small-impact feature observed. Micro-debris populations are then estimated by modeling the path and orientation of an STS mission through a simulated debris environment, and the densities of this simulated environment are rescaled to approximate the number of observed STS impact features. Monte-Carlo methods are further employed to gauge the estimation uncertainty of the rescaled environment. A description of the chosen methodologies for estimating and adjusting the micro-debris population model, and the results, are presented.

Seago, J..↗

Primordial non-Gaussianity from the completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey – I: Catalogue preparation and systematic mitigation

ABSTRACT We investigate the large-scale clustering of the final spectroscopic sample of quasars from the recently completed extended Baryon Oscillation Spectroscopic Survey (eBOSS). The sample contains 343 708 objects in the redshift range 0.8 < z < 2.2 and 72 667 objects with redshifts 2.2 < z < 3.5, covering an effective area of $4699\, {\rm deg}^{2}$. We develop a neural network-based approach to mitigate spurious fluctuations in the density field caused by spatial variations in the quality of the imaging data used to select targets for follow-up spectroscopy. Simulations are used with the same angular and radial distributions as the real data to estimate covariance matrices, perform error analyses, and assess residual systematic uncertainties. We measure the mean density contrast and cross-correlations of the eBOSS quasars against maps of potential sources of imaging systematics to address algorithm effectiveness, finding that the neural network-based approach outperforms standard linear regression. Stellar density is one of the most important sources of spurious fluctuations, and a new template constructed using data from the Gaia spacecraft provides the best match to the observed quasar clustering. The end-product from this work is a new value-added quasar catalogue with the improved weights to correct for non-linear imaging systematic effects, which will be made public. Our quasar catalogue is used to measure the local-type primordial non-Gaussianity in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗

A Hyperspectral Inversion Framework for Estimating Absorbing Inherent Optical Properties and Biogeochemical Parameters in Inland and Coastal Waters

The simultaneous remote estimation of biogeochemical parameters (BPs) and inherent optical properties (IOPs) from hyperspectral satellite imagery of globally distributed optically distinct inland and coastal waters is a complex, unsolved, non-unique inverse problem. To tackle this problem, we leverage a machine-learning model termed Mixture Density Networks (MDNs). MDNs outperform operational algorithms by calculating the covariance between the simultaneously estimated products. We train the MDNs on a large ( N = 8237) dataset of co-aligned, in situ measured, hyperspectral remote sensing reflectance (R rs ), BPs, and absorbing IOPs from globally representative optically distinct inland and coastal waters. The estimated IOPs include absorption due to phytoplankton (a ph ), chromophoric dissolved organic matter (a cdom ), and non-algal particles (a nap ). The estimated BPs include chlorophyll-a, total suspended solids, and phycocyanin (PC). MDNs dramatically reduce uncertainty in the retrievals, relative to operational algorithms, when using a 50/50 dataset split, where the MDNs are trained on a randomly selected half of the in situ dataset and validated on the other half. Our model is shown to have higher, or equivalent, generalization performance than the calculated operational algorithms available for all BPs and IOPs (except PC) via a leave-one-out cross-validation assessment. The MDNs are sensitive to uncertainties in the hyperspectral satellite R rs , resulting from instrument noise and atmospheric correction; there is a difference of ~37.4–62.8% (using median symmetric accuracy) between the MDNs’ estimates derived from co-located satellite-derived R rs and in situ R rs . Of the IOPs, a cdom and a nap are less sensitive to uncertainties in hyperspectral satellite imagery relative to a ph , with remote estimates of a ph exhibiting incorrect spectral shape and magnitude relative to in situ measured IOPs. Despite the uncertainties in satellite derived R rs , the spatial distributions of BPs and IOPs in MDN-derived product maps of Lake Erie and the Curonian Lagoon, based on imagery taken with the Hyperspectral Imager for the Coastal Ocean (HICO) and PRecursore Iper-Spettrale della Missione Applicativa (PRISMA), are confirmed via co-aligned in situ measurements and agree with the literature’s understanding of these well-studied regions. The consistency and accuracy of the model on HICO and PRISMA imagery, despite radiometric uncertainties, demonstrate its applicability to future hyperspectral missions, such as the Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, where the simultaneous estimation model will serve as a key part of phytoplankton community composition analysis.

Ryan E. O'Shea↗

TRINIDI: Time-of-Flight Resonance Imaging With Neutrons for Isotopic Density Inference

Accurate reconstruction of 2D and 3D isotope densities is a desired capability with great potential impact in applications such as evaluation and development of next-generation nuclear fuels. Neutron time-of-flight (TOF) resonance imaging offers a potential approach by exploiting the characteristic neutron absorption spectra of each isotope. However, it is a major challenge to compute quantitatively accurate images due to a variety of confounding effects such as severe Poisson noise, background scatter, beam non-uniformity, absorption non-linearity, and extended source pulse duration. We present the TRINIDI algorithm which is based on a two-step process in which we first estimate the neutron flux and background counts, and then reconstruct the areal densities of each isotope and pixel. Both components are based on the inversion of a forward model that accounts for the highly non-linear absorption, energy-dependent emission profile, and Poisson noise, while also modeling the substantial spatio-temporal variation of the background and flux. Further, to do this, we formulate the non-linear inverse problem as two optimization problems that are solved in sequence. We demonstrate on both synthetic and measured data that TRINIDI can reconstruct quantitatively accurate 2D views of isotopic areal density that can then be reconstructed into quantitatively accurate 3D volumes of isotopic volumetric density.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗