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At least 1,567 records · Page 87

Maneuver Design and Calibration for the Genesis Spacecraft

Genesis is the fifth mission selected as part of NASA's Discovery Program. The objective of Genesis is to collect solar wind samples for a period of approximately two years while in a halo orbit about the Earth-Sun L I point. At the end of this period, the samples are to be returned to a specific recovery point on the Earth for subsequent analysis. This goal has never been attempted before and presents a formidable challenge in terms of mission design and operations, particularly planning and execution of propulsive maneuvers. To achieve a level of cost-effectiveness consistent with a Discovery-class mission, the Genesis spacecraft design was adapted to the maximum extent possible from designs used on earlier missions, such as Mars Global Surveyor (MGS) and Stardust, another sample collection mission. The spacecraft design for Genesis is shown. Spin stabilization was chosen for attitude control, in lieu of three-axis stabilization, with neither reaction wheels nor accelerometers included. This precludes closed-loop control of propulsive maneuvers and implies that any attitude changes, including spin changes and precessions, will behave like translational propulsive maneuvers and affect the spacecraft trajectory. Moreover, to minimize contamination risk to the samples collected, all thrusters were placed on the side opposite the sample collection canister. The orientation and characteristics of thrusters are indicated. For large maneuvers (>2.5 m/s), two 5 lbf thrusters will be used for delta v, with precession to the burn attitude, followed by spin-up from 1.6 to 10 rpm before the burn and spin down to 1.6 rpm afterwards, then precession back to the original spin attitude. For small maneuvers (<2.5 m/s), no spin change is needed and four 0.2 lbf thrusters are used for Av. Single or double 360 deg. precession changes are required whenever the desired delta v falls inside the two-way turn circle (about 0.4 m/s) based on the mass properties, spin rate and lever arm lengths based on thruster locations. In such instances, delta v resulting from spacecraft precession cannot be used effectively as a component of the desired delta v, and must therefore be removed by precessing at least one complete revolution around the turn circle. To eliminate cross-track execution errors, a second revolution in the opposite direction would also be performed. This paper will address the design of propulsive maneuvers in light of the aforementioned challenges and other constraints. Maneuver design will be performed jointly by the Navigation Team at JPL and the Spacecraft Team at LMA, based on the process indicated . Typical maneuver timelines will be presented which address considerations introduced by attitude changes. These include nutation, which is introduced by precessing or spinning down and must be given sufficient time to damp out prior to execution of subsequent events, as well as sun and earth pointing constraints, which must be considered to ensure sufficient spacecraft power and to minimize telecommunications interruptions, respectively. The paper will include a description of how individual propulsive maneuvers are resolved into components to account for delta v from translational burns and spacecraft attitude changes required to carry out such maneuvers. Contributions to maneuver delta v arising from attitude changes, based on mass properties for the period just after launch, are indicated. Similar curves will be presented spanning all mission phases from launch through return. A set of closed-form equations for resolving maneuver components, base on a specific delta v required for correction or deterministic changes to the spacecraft trajectory will be presented, as well. In addition to nominal maneuvers, special calibration maneuvers are planned to improve open-loop modeling of maneuvers and to reduce execution errors. Uncalibrated execution errors are indicated. Such errors could be reduced by 50% or more over the course of the mission. Special calibrations are of particular importance for the return leg of the mission, since the sample canister must be returned to a specific location within the Utah Test and Training Range (UTTR) for mid-air retrieval. An entry angle tolerance of no less than +/- 0.08 deg. is required to achieve this objective. Biasing of the final return maneuvers coupled with a specific maneuver mode to use a series of well-characterized spin changes to effect these maneuvers is part of the current Genesis baseline mission plan. Another important objective of calibrations is to better characterize precession maneuvers. Such maneuvers are part of most propulsive maneuvers, but are also required periodically to maintain sun-pointing for power or daily during solar-wind pointing during collection periods. Although relatively small, such maneuvers will have a significant cumulative impact on orbit determination, particularly in the halo portion of the mission. The current mission design also calls for three stationkeeping maneuvers during each halo orbit of approximately six months duration. These stationkeeping maneuvers may be sufficiently small that single or double 360 deg. precession changes may be required. Because there are no accelerometers on board the spacecraft, calibration can only be performed with the aid of ground-based radiometric tracking. To establish a high degree of accuracy in characterizing the magnitude of burns, the spacecraft spin axis should be along the line of sight to the Earth, providing Doppler measurements with <1 mm/sec accuracy in S-Band. Emission constraints allow such alignment only during certain portions of the mission when the Earth-spacecraft-sun geometry is favorable. The impact of precessions, or burns at times when geometry is not favorable, can be assessed by reconstruction of the spacecraft trajectory using tracking arcs of several days before and after the event.

Williams, Kenneth E.↗

Learning Functions Varying along a Central Subspace

Many functions of interest are in a high-dimensional space but exhibit low-dimensional structures. This paper studies regression of an s-Hölder function in $R^D$ which varies along a central subspace of dimension $d$ while $d \ll D$. A direct approximation of $f$ in $R^D$ with an accuracy $\varepsilon$ requires the number of samples in the order of $\varepsilon^{-(2s+D)/s}$. In this paper, we analyze the generalized contour regression (GCR) algorithm for the estimation of the central subspace and use piecewise polynomials for function approximation. GCR is among the best estimators for the central subspace, but its sample complexity is an open question. In this paper, we partially answer this questions by proving that if a variance quantity is exactly known, GCR leads to a mean squared estimation error of $O(n^{-1})$ for the central subspace. The estimation error of this variance quantity is also given in this paper. The mean squared regression error of $f$ is proved to be in the order of $(n/\log n)^{-\frac{2s}{2s+d}}$, where the exponent depends on the dimension of the central subspace instead of the ambient space . This result demonstrates that GCR is effective in learning the low-dimensional central subspace. We also propose a modified GCR with improved efficiency. Here, the convergence rate is validated through several numerical experiments.

97 MATHEMATICS AND COMPUTING↗

Dark Energy Survey Year 3 results: calibration of lens sample redshift distributions using clustering redshifts with BOSS/eBOSS

ABSTRACT We present clustering redshift measurements for Dark Energy Survey (DES) lens sample galaxies used in weak gravitational lensing and galaxy clustering studies. To perform these measurements, we cross-correlate with spectroscopic galaxies from the Baryon Acoustic Oscillation Survey (BOSS) and its extension, eBOSS. We validate our methodology in simulations, including a new technique to calibrate systematic errors that result from the galaxy clustering bias, and we find that our method is generally unbiased in calibrating the mean redshift. We apply our method to the data, and estimate the redshift distribution for 11 different photometrically selected bins. We find general agreement between clustering redshift and photometric redshift estimates, with differences on the inferred mean redshift found to be below |Δz| = 0.01 in most of the bins. We also test a method to calibrate a width parameter for redshift distributions, which we found necessary to use for some of our samples. Our typical uncertainties on the mean redshift ranged from 0.003 to 0.008, while our uncertainties on the width ranged from 4 to 9 per cent. We discuss how these results calibrate the photometric redshift distributions used in companion papers for DES Year 3 results.

79 ASTRONOMY AND ASTROPHYSICS↗

Global Explainability of A Deep Abstaining Classifier for Cancer Pathology Reports

We present a global explainability method to characterize sources of errors in a real-world multitask deep abstaining classifier (DAC), in the context of cancer histology prediction. Our multitask classifier, currently deployed for automated annotation of cancer pathology reports from NCI-SEER registries, was trained and evaluated on 1.04 million hand-annotated samples and makes simultaneous predictions of cancer site, subsite, histology, laterality, and behavior for each report. The DAC framework enables the model to abstain on ambiguous reports and confusing classes to achieve the target accuracy on the retained (non-abstained) samples, but at the cost of decreased coverage. Requiring 97% accuracy on the histology task caused our model to retain only 22% of all samples, mostly the less ambiguous and common classes. Local explainability with the GradInp technique provided a computationally efficient way of obtaining contextual reasoning for hundreds of thousands of individual predictions. Our method, involving dimensionality reduction of approximately 13000 aggregated local explanations (ALE), offers a tractable path to true global explainability. It enabled identification of sources of errors in histology classification, globally, as hierarchical complexity among classes, label noise, insufficient information, and conflicting evidence. This suggests several strategies for iterative improvement of our DAC, including well-designed exclusion criteria, focused annotation, and reduced penalties for errors involving hierarchically related classes.

59 BASIC BIOLOGICAL SCIENCES↗

Dark Energy Survey Year 1 Results: Cross-Correlation Redshifts - Methods and Systematics Characterization

We use numerical simulations to characterize the performance of a clustering-based method to calibrate photometric redshift biases. In particular, we cross-correlate the weak lensing (WL) source galaxies from the Dark Energy Survey Year 1 (DES Y1) sample with redMaGiC galaxies (luminous red galaxies with secure photometric red- shifts) to estimate the redshift distribution of the former sample. The recovered redshift distributions are used to calibrate the photometric redshift bias of standard photo-z methods applied to the same source galaxy sample. We also apply the method to three photo-z codes run in our simulated data: Bayesian Photometric Redshift (BPZ), Directional Neighborhood Fitting (DNF), and Random Forest-based photo-z (RF). We characterize the systematic uncertainties of our calibration procedure, and find that these systematic uncertainties dominate our error budget. The dominant systematics are due to our assumption of unevolving bias and clustering across each redshift bin, and to differences between the shapes of the redshift distributions derived by clustering vs photo-z's. The systematic uncertainty in the mean redshift bias of the source galaxy sample is z ≲ 0.02, though the precise value depends on the redshift bin under consideration. Here, we discuss possible ways to mitigate the impact of our dominant systematics in future analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

Kinematic focus point method for particle mass measurements in missing energy events

We investigate the solvability of the event kinematics in missing energy events at hadron colliders, as a function of the particle mass ansatz. To be specific, we reconstruct the neutrino momenta in dilepton tt¯-like events, without assuming any prior knowledge of the mass spectrum. We identify a class of events, which we call extreme events, with the property that the kinematic boundary of their allowed region in mass parameter space passes through the true mass point. We develop techniques for recognizing extreme events in the data and demonstrate that they are abundant in a realistic data sample, due to expected singularities in phase space. We propose a new method for mass measurement whereby we obtain the true values of the mass parameters as the focus point of the kinematic boundaries for all events in the data sample. Since the masses are determined from a relatively sharp peak structure (the density of kinematic boundary curves), the method avoids some of the systematic errors associated with other techniques. We show that this new approach is complementary to previously considered methods in the literature where one studies the solvability of the kinematic constraints throughout the mass parameter space. In particular, we identify a problematic direction in mass space of nearly 100% solvability, and then show that the focus point method is effective in lifting the degeneracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantifying uncertainty in uranium concentration measurements via K-edge densitometry

This study quantifies the uncertainty in uranium concentration predictions of fluoride and chloride-based salts within a steel pipe using K-edge densitometry. Modeling and simulation was conducted with the Monte Carlo N-Particle Transport (MCNP) code. The quality of of this technique’s prediction in a pipe requires proper characterization of the pipe’s thickness, which is dependent on the source size and axial offset from the pipe centerline. The thickness was determined as either the center-line thickness seen by the X-ray source or an average value determined through random sampling. Generally, the predicted concentrations were slightly better at lower offset with the random sampling thickness and using the center-line thickness for the highest offsets. For a line-beam source and varying axial offsets, the relative error of concentration was within 1% of the true value but uncertainty increased by 2 orders of magnitude. Similarly, for no axial offset, the relative error was significantly less than 1% while no trend for uncertainty was found. However, at the largest possible offset for a given source size, the concentrations become erroneous and greater than the allowable 1% relative error. Furthermore, high offsets tended to increase the variance of the transmission spectra by 3 orders of magnitude.

Characterization and Analytical Technique↗

Thermodynamics of copper‐manganese and copper‐iron spinel solid solutions

Abstract High‐temperature oxide melt solution calorimetry has been performed to investigate the energetics of spinel solid solutions in the Mn 3 O 4 ‐CuMn 2 O 4 and Fe 3 O 4 ‐CuFe 2 O 4 systems. The spinel solid solutions were synthesized by a ceramic route and calcined at appropriate temperatures to obtain single phase samples. The drop solution enthalpies of the solid solutions in the Mn 3 O 4 ‐CuMn 2 O 4 system are the same within experimental error as the enthalpies of drop solution of mechanical mixtures of the end‐members, indicating a zero heat of mixing, i.e., ideal mixing in terms of enthalpy. In Fe 3 O 4 ‐CuFe 2 O 4 , the drop solution enthalpy of the solid solutions shows a positive deviation from those of the mechanical mixture of the end‐members, suggesting negative mixing enthalpy. The formation enthalpies of the spinel solid solutions from their constituent oxides plus oxygen and from the elements were also determined.

Sahu, Sulata K.↗

Deep machine learning-assisted multiphoton microscopy to reduce light exposure and expedite imaging

Two-photon excitation fluorescence (2PEF) allows imaging of tissue up to about one millimeter in thickness. Typically, reducing fluorescence excitation exposure reduces the quality of the image. However, using deep learning super resolution techniques, these low-resolution images can be converted to high-resolution images. This work explores improving human tissue imaging by applying deep learning to maximize image quality while reducing fluorescence excitation exposure. We analyze two methods: a method based on U-Net, and a patch-based regression method. Both methods are evaluated on a skin dataset and an eye dataset. The eye dataset includes 1200 paired high power and low power images of retinal organoids. The skin dataset contains multiple frames of each sample of human skin. High-resolution images were formed by averaging 70 frames for each sample and low-resolution images were formed by averaging the first 7 and 15 frames for each sample. The skin dataset includes 550 images for each of the resolution levels. We track two measures of performance for the two methods: mean squared error (MSE) and structural similarity index measure (SSIM). For the eye dataset, the patches method achieves an average MSE of 27,611 compared to 146,855 for the U-Net method, and an average SSIM of 0.636 compared to 0.607 for the U-Net method. For the skin dataset, the patches method achieves an average MSE of 3.768 compared to 4.032 for the U-Net method, and an average SSIM of 0.824 compared to 0.783 for the U-Net method. Despite better performance on image quality, the patches method is worse than the U-Net method when comparing the speed of prediction, taking 303 seconds to predict one image compared to less than one second for the U-Net method.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

Detecting Arsenic Contamination Using Satellite Imagery and Machine Learning

Arsenic, a potent carcinogen and neurotoxin, affects over 200 million people globally. Current detection methods are laborious, expensive, and unscalable, being difficult to implement in developing regions and during crises such as COVID-19. This study attempts to determine if a relationship exists between soil’s hyperspectral data and arsenic concentration using NASA’s Hyperion satellite. It is the first arsenic study to use satellite-based hyperspectral data and apply a classification approach. Four regression machine learning models are tested to determine this correlation in soil with bare land cover. Raw data are converted to reflectance, problematic atmospheric influences are removed, characteristic wavelengths are selected, and four noise reduction algorithms are tested. The combination of data augmentation, Genetic Algorithm, Second Derivative Transformation, and Random Forest regression (R 2 =0.840 and normalized root mean squared error (re-scaled to [0,1]) = 0.122) shows strong correlation, performing better than past models despite using noisier satellite data (versus lab-processed samples). Three binary classification machine learning models are then applied to identify high-risk shrub-covered regions in ten U.S. states, achieving strong accuracy (=0.693) and F1-score (=0.728). Overall, these results suggest that such a methodology is practical and can provide a sustainable alternative to arsenic contamination detection.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

The Discovery of the Electromagnetic Counterpart of GW170817: Kilonova AT 2017gfo/DLT17ck

During the second observing run of the Laser Interferometer Gravitational-wave Observatory (LIGO) and Virgo Interferometer, a gravitational-wave signal consistent with a binary neutron star coalescence was detected on 2017 August 17th (GW170817), quickly followed by a coincident short gamma-ray burst trigger detected by the Fermi satellite. The Distance Less Than 40 (DLT40) Mpc supernova search performed pointed follow-up observations of a sample of galaxies regularly monitored by the survey that fell within the combined LIGO+Virgo localization region and the larger Fermi gamma-ray burst error box. Here we report the discovery of a new optical transient (DLT17ck, also known as SSS17a; it has also been registered as AT 2017gfo) spatially and temporally coincident with GW170817. The photometric and spectroscopic evolution of DLT17ck is unique, with an absolute peak magnitude of M {sub r} = −15.8 ± 0.1 and an r -band decline rate of 1.1 mag day{sup −1}. This fast evolution is generically consistent with kilonova models, which have been predicted as the optical counterpart to binary neutron star coalescences. Analysis of archival DLT40 data does not show any sign of transient activity at the location of DLT17ck down to r ∼ 19 mag in the time period between 8 months and 21 days prior to GW170817. This discovery represents the beginning of a new era for multi-messenger astronomy, opening a new path by which to study and understand binary neutron star coalescences, short gamma-ray bursts, and their optical counterparts.

79 ASTRONOMY AND ASTROPHYSICS↗

Optimal estimation for discrete time jump processes

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are derived. The approach used is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. Thus a general representation is obtained for optimum estimates, and recursive equations are derived for minimum mean-squared error (MMSE) estimates. In general, MMSE estimates are nonlinear functions of the observations. The problem is considered of estimating the rate of a DTJP when the rate is a random variable with a beta probability density function and the jump amplitudes are binomially distributed. It is shown that the MMSE estimates are linear. The class of beta density functions is rather rich and explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Vaca, M. V.↗

The intercrater plains of Mercury and the Moon: Their nature, origin and role in terrestrial planet evolution. Measurement and errors of crater statistics

Planetary imagery techniques, errors in measurement or degradation assignment, and statistical formulas are presented with respect to cratering data. Base map photograph preparation, measurement of crater diameters and sampled area, and instruments used are discussed. Possible uncertainties, such as Sun angle, scale factors, degradation classification, and biases in crater recognition are discussed. The mathematical formulas used in crater statistics are presented.

Leake, M. A.↗

Rare earth chalcogenide stoichiometry determination

Rare earth chalcogenides, and particularly lanthanum sulfide, are currently explored as candidate materials for thermoelectric applications. Since the electrical properties of LaS(x) are largely determined by its stoichiometry, a simple and accurate method has been developed for determining the value of x. The procedure involves dissolving a weighted sample in acid and measuring the amount of hydrogen evolved by the lanthanum that is in excess of the 1.500 ratio of S/La. The analytical error in the determination of x in LaS(x) is about 0.001.

Lockwood, R. A.↗

The Shane-Wirtanen counts - Plate correction factors and correlation functions

It has recently been argued that the break in the galaxy correlation function observed in the Lick counts of Shane and Wirtanen may be an artifact of plate variations in limiting magnitude. This has stimulated us to generalize our analysis of the effect of errors in the plate depths to include a possible systematic term, and to develop tests for the random and systematic errors. The tests show that neither can have appreciably affected the distinctive feature found in the galaxy two-point correlation function for the Lick sample.

Groth, Edward J.↗

Non-linearity in measurement systems: Evaluation method and application to microwave radiometers

A simple method for determination and correction of nonlinaearity in measurement systems is presented. The technique is applicable to a wide range of measuring systems. The basic concept, an analysis, and a sample application are given. Nonlinearity of the Goldstone DSS 13 low noise HEMT 2.3 GHz (S-band) radiometer system results in noise temperature measurement errors. These errors are successfully correct with this method.

Stelzried, C. T.↗

Laser measurements of ozone absorption cross sections in the Chappuis band

A sensitive spectrometer has been developed that exploits several He-Ne laser transitions in the visible for precise, high resolution measurements of Chappuis band ozone absorption cross sections at room temperature. An overall uncertainty of better than one percent has been achieved through a combination of transducer calibrations and an experimental technique that unambiguously determines the impurity content of each ozone sample. Results compare favorably with those from most previous analyses in the visible range, though some are obviously lower than this consensus due probably to errors in ozone density measurements.

Anderson, Stuart M.↗

Digital visual communications using a Perceptual Components Architecture

The next era of space exploration will generate extraordinary volumes of image data, and management of this image data is beyond current technical capabilities. We propose a strategy for coding visual information that exploits the known properties of early human vision. This Perceptual Components Architecture codes images and image sequences in terms of discrete samples from limited bands of color, spatial frequency, orientation, and temporal frequency. This spatiotemporal pyramid offers efficiency (low bit rate), variable resolution, device independence, error-tolerance, and extensibility.

Watson, Andrew B.↗