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At least 55 records · Page 3

The Role of GRAIL Orbit Determination in Preprocessing of Gravity Science Measurements

The Gravity Recovery And Interior Laboratory (GRAIL) mission has constructed a lunar gravity field with unprecedented uniform accuracy on the farside and nearside of the Moon. GRAIL lunar gravity field determination begins with preprocessing of the gravity science measurements by applying corrections for time tag error, general relativity, measurement noise and biases. Gravity field determination requires the generation of spacecraft ephemerides of an accuracy not attainable with the pre-GRAIL lunar gravity fields. Therefore, a bootstrapping strategy was developed, iterating between science data preprocessing and lunar gravity field estimation in order to construct sufficiently accurate orbit ephemerides.This paper describes the GRAIL measurements, their dependence on the spacecraft ephemerides and the role of orbit determination in the bootstrapping strategy. Simulation results will be presented that validate the bootstrapping strategy followed by bootstrapping results for flight data, which have led to the latest GRAIL lunar gravity fields.

science preprocessing

On the error probability of general tree and trellis codes with applications to sequential decoding

An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random binary tree codes is derived and shown to be independent of the length of the tree. An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n is derived which separates the effects of the tail length T and the memory length M of the code. It is shown that the bound is independent of the length L of the information sequence. This implication is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication and further suggest an empirical formula for the true undetected decoding error probability with sequential decoding.

Johannesson, R.

On the error probability of general trellis codes with applications to sequential decoding

An upper bound on the average probability of error for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n with distinction between memory length and tail length is given. It is shown that the bound is independent of the length L of the information sequence if the memory length exceeds the tail length by a specified amount that depends on L. Sequential decoding simulations using the stack algorithm were conducted to test the dependence of the undetected error probability on tail length and memory length, and the results corroborated the theory.

Johannesson, R.

Analysis of open-loop conical scan pointing error and variance estimators

General pointing error and variance estimators for an open-loop conical scan (conscan) system are derived and analyzed. The conscan algorithm is modeled as a weighted least-squares estimator whose inputs are samples of receiver carrier power and its associated measurement uncertainty. When the assumptions of constant measurement noise and zero pointing error estimation are applied, the variance equation is then strictly a function of the carrier power to uncertainty ratio and the operator selectable radius and period input to the algorithm. The performance equation is applied to a 34-m mirror-based beam-waveguide conscan system interfaced with the Block V Receiver Subsystem tracking a Ka-band (32-GHz) downlink. It is shown that for a carrier-to-noise power ratio greater than or equal to 30 dB-Hz, the conscan period for Ka-band operation may be chosen well below the current DSN minimum of 32 sec. The analysis presented forms the basis of future conscan work in both research and development as well as for the upcoming DSN antenna controller upgrade for the new DSS-24 34-m beam-waveguide antenna.

Alvarez, L. S.

Computerized Design and Generation of Gear Drives With a Localized Bearing Contact and a Low Level of Transmission Errors

A general approach developed for the computerized simulation of loaded gear drives is presented. In this paper the methodology used to localize the bearing contact, provide a parabolic function of transmission errors, and simulate meshing and contact of unloaded gear drives is developed. The approach developed is applied to spur and helical gears, spiral bevel gears, face-gear drives, and worm-gear drives with cylindrical worms.

Litvin, F.

Dynamical predictability in a simple general circulation model - Average error growth

Average predictability and error growth in a simple realistic two-level general circulation model (GCM) were investigated using a series of Monte Carlo experiments for fixed external forcing (perpetual winter in the Northern Hemisphere). It was found that, for realistic initial errors, the dependence of the limit of dynamic predictability on total wavenumber was similar to that found for the ECMWF model for the 1980/1981 winter conditions, with the lowest wavenumbers showing significant skill for forecast ranges of more than 1 month. On the other hand, for very small amplitude errors distributed according to the climate spectrum, the total error growth was superexponential, reaching a maximum growth rate (2-day doubling time) in about 1 week. A simple empirical model of error variance, which involved two broad wavenumber bands and incorporating a 3/2 power saturation term, was found to provide an excellent fit to the GCM error growth behavior.

Schubert, Siegfried D.

Avoiding Selection Bias in Generating Examples of Plans in the Presence of Heuristic Error

It is generally understood that heuristic error hurts the performance of search algorithms, measured in terms of search effort. Hence there is an interest in understanding how to reduce heuristic error. One way to do this is to learn a heuristic from a set of examples of plans generated offline, e.g. bootstrapping methods. In this paper, we consider how some methods for generating examples of plans may skew the training set in the presence of heuristic errors. Initial theoretical results show that duplicate detection is one source of selection bias in the canonical A* algorithm. We introduce a duplicate selection scheme for A* that avoids selection bias in generating cost-optimal examples, without compromising memory efficiency, and develop ideas in the satisficing setting. We evaluate our approach on n x m grids with multiple cost-optimal solutions and synthetic heuristic error. Finally, we attempt to extend these ideas to the problem of generating extreme examples of plans.

Alison S Paredes

Electron Capture into Rydberg States According to the Born Approximation: Correction of an Error

A general expression is derived for the Born amplitude for electron capture into high principal, and arbitrary angular momentum, quantum numbers, n and l, by bare nuclei from hydrogenic atom targets. Cross sections for capture into high n and l = 0,1 are given in analytic forms. The limiting values of the ratios of the Born over OBK cross sections for n >> 1 and l = 0,1 are found, and shown that they confirm the empirical law of Jackson and Schiff only approximately. For high angular momenta, it is shown that the Born cross section approaches the OBK cross section. An error in a previous publication by the author has been corrected.

Omidvar, Kazem

Combined Uncertainty and A-Posteriori Error Bound Estimates for General CFD Calculations: Theory and Software Implementation

This workshop presentation discusses the design and implementation of numerical methods for the quantification of statistical uncertainty, including a-posteriori error bounds, for output quantities computed using CFD methods. Hydrodynamic realizations often contain numerical error arising from finite-dimensional approximation (e.g. numerical methods using grids, basis functions, particles) and statistical uncertainty arising from incomplete information and/or statistical characterization of model parameters and random fields. The first task at hand is to derive formal error bounds for statistics given realizations containing finite-dimensional numerical error [1]. The error in computed output statistics contains contributions from both realization error and the error resulting from the calculation of statistics integrals using a numerical method. A second task is to devise computable a-posteriori error bounds by numerically approximating all terms arising in the error bound estimates. For the same reason that CFD calculations including error bounds but omitting uncertainty modeling are only of limited value, CFD calculations including uncertainty modeling but omitting error bounds are only of limited value. To gain maximum value from CFD calculations, a general software package for uncertainty quantification with quantified error bounds has been developed at NASA. The package provides implementations for a suite of numerical methods used in uncertainty quantification: Dense tensorization basis methods [3] and a subscale recovery variant [1] for non-smooth data, Sparse tensorization methods[2] utilizing node-nested hierarchies, Sampling methods[4] for high-dimensional random variable spaces.

CFD

Formulation and error analysis for a generalized image point correspondence algorithm

A Generalized Image Point Correspondence (GIPC) algorithm, which enables the determination of 3-D motion parameters of an object in a configuration where both the object and the camera are moving, is discussed. A detailed error analysis of this algorithm has been carried out. Furthermore, the algorithm was tested on both simulated and video-acquired data, and its accuracy was determined.

Shapiro, Linda

A General Framework for Error-controlled Unstructured Scientific Data Compression

Data compression plays a key role in reducing storage and I/O costs. Traditional lossy methods primarily target data on rectilinear grids and cannot leverage the spatial coherence in unstructured mesh data, leading to suboptimal compression ratios. We present a multi-component, error-bounded compression framework designed to enhance the compression of floating-point unstructured mesh data, which is common in scientific applications. Our approach involves interpolating mesh data onto a rectilinear grid and then separately compressing the grid interpolation and the interpolation residuals. This method is general, independent of mesh types and typologies, and can be seamlessly integrated with existing lossy compressors for improved performance. We evaluated our framework across twelve variables from two synthetic datasets and two real-world simulation datasets. The results indicate that the multi-component framework consistently outperforms state-of-the-art lossy compressors on unstructured data, achieving, on average, a 2.3 − 3.5× improvement in compression ratios, with error bounds ranging from 1 × 10 the −6 to 1×10−2. We further investigate impact of hyperparameters, such as grid spacing and error allocation, to deliver optimal compression ratios in diverse datasets.

Gong, Qian

Error analysis of householder transformations as applied to the standard and generalized eigenvalue problems

Backward error analyses of the application of Householder transformations to both the standard and the generalized eigenvalue problems are presented. The analysis for the standard eigenvalue problem determines the error from the application of an exact similarity transformation, and the analysis for the generalized eigenvalue problem determines the error from the application of an exact equivalence transformation. Bounds for the norms of the resulting perturbation matrices are presented and compared with existing bounds when known.

Ward, R. C.

Closed-loop stability of linear quadratic optimal systems in the presence of modeling errors

The well-known stabilizing property of linear quadratic state feedback design is utilized to evaluate the robustness of a linear quadratic feedback design in the presence of modeling errors. Two general conditions are obtained for allowable modeling errors such that the resulting closed-loop system remains stable. One of these conditions is applied to obtain two more particular conditions which are readily applicable to practical situations where a designer has information on the bounds of modeling errors. Relations are established between the allowable parameter uncertainty and the weighting matrices of the quadratic performance index, thereby enabling the designer to select appropriate weighting matrices to attain a robust feedback design.

Toda, M.

On the discretization error of the discrete generalized quantum master equation

The transfer tensor method (TTM) [Cerrillo and Cao, Phys. Rev. Lett. 112 , 110401 (2014)] can be considered a discrete-time formulation of the Nakajima–Zwanzig quantum master equation (NZ-QME) for modeling non-Markovian quantum dynamics. A recent paper [Makri, J. Chem. Theory Comput. 21 , 5037 (2025)] raised concerns regarding the consistency of the TTM discretization, particularly a spurious term at the initial time t = 0. Here, this work presents a detailed analysis of the discretization structure of the TTM, clarifying the origin of the initial-time correction and establishing a consistent relationship between the TTM discrete-time memory kernel K N and the continuous-time NZ-QME kernel $\mathscr{K}$( N Δ t ). This relationship is validated numerically using the spin-boson model, demonstrating convergence of reconstructed memory kernels and accurate dynamical evolution as Δ t → 0. While the TTM provides a consistent discretization, we note that alternative schemes are also viable, such as the midpoint derivative/midpoint integral scheme proposed in Makri’s work. The relative performance of various schemes for either computing accurate $\mathscr{K}$( N Δ t ) from exact dynamics or obtaining accurate dynamics from exact $\mathscr{K}$( N Δ t ) warrants further investigation.

Density-matrix

Evaluation of a surface/vegetation parameterization using satellite measurements of surface temperature

Ground measurements of surface-sensible heat flux and soil moisture for a wheat-growing area of Beauce in France were compared with the values derived by inverting two boundary layer models with a surface/vegetation formulation using surface temperature measurements made from NOAA-AVHRR. The results indicated that the trends in the surface heat fluxes and soil moisture observed during the 5 days of the field experiment were effectively captured by the inversion method using the remotely measured radiative temperatures and either of the two boundary layer methods, both of which contain nearly identical vegetation parameterizations described by Taconet et al. (1986). The sensitivity of the results to errors in the initial sounding values or measured surface temperature was tested by varying the initial sounding temperature, dewpoint, and wind speed and the measured surface temperature by amounts corresponding to typical measurement error. In general, the vegetation component was more sensitive to error than the bare soil model.

Taconet, O.