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At least 19 records

Radar error statistics for the space shuttle

Radar error statistics of C-band and S-band that are recommended for use with the groundtracking programs to process space shuttle tracking data are presented. The statistics are divided into two parts: bias error statistics, using the subscript B, and high frequency error statistics, using the subscript q. Bias errors may be slowly varying to constant. High frequency random errors (noise) are rapidly varying and may or may not be correlated from sample to sample. Bias errors were mainly due to hardware defects and to errors in correction for atmospheric refraction effects. High frequency noise was mainly due to hardware and due to atmospheric scintillation. Three types of atmospheric scintillation were identified: horizontal, vertical, and line of sight. This was the first time that horizontal and line of sight scintillations were identified.

Lear, W. M.↗

Error statistics and scalability of quantum error mitigation formulas

Quantum computing promises advantages over classical computing in many problems. Nevertheless, noise in quantum devices prevents most quantum algorithms from achieving the quantum advantage. Quantum error mitigation provides a variety of protocols to handle such noise using minimal qubit resources. While some of those protocols have been implemented in experiments for a few qubits, it remains unclear whether error mitigation will be effective in quantum circuits with tens to hundreds of qubits. In this paper, we apply statistics principles to quantum error mitigation and analyse the scaling behaviour of its intrinsic error. We find that the error increases linearly O(ϵN) with the gate number N before mitigation and sublinearly O(ϵ'N γ ) after mitigation, where γ ≈ 0.5, ϵ is the error rate of a quantum gate, and ϵ' is a protocol-dependent factor. The $\sqrt{N}$ scaling is a consequence of the law of large numbers, and it indicates that error mitigation can suppress the error by a larger factor in larger circuits. We propose the importance Clifford sampling as a key technique for error mitigation in large circuits to obtain this result.

97 MATHEMATICS AND COMPUTING↗

Statistical error model for a solar electric propulsion thrust subsystem

The solar electric propulsion thrust subsystem statistical error model was developed as a tool for investigating the effects of thrust subsystem parameter uncertainties on navigation accuracy. The model is currently being used to evaluate the impact of electric engine parameter uncertainties on navigation system performance for a baseline mission to Encke's Comet in the 1980s. The data given represent the next generation in statistical error modeling for low-thrust applications. Principal improvements include the representation of thrust uncertainties and random process modeling in terms of random parametric variations in the thrust vector process for a multi-engine configuration.

Bantell, M. H.↗

Statistical Error Analysis on White-Light Filter Ratio Experiments to Measure Electron Parameters

The Filter ratio technique to remotely measure electron temperature and speed using four color filters in visible light and a polarization camera was described in detail in four articles by Reginald et al., Solar physics, (2018, 2019a, 2019b, 2020). In these four articles we quantified the systematic error associated with using models of symmetric corona to interpret results from asymmetric corona. We also showed the criteria applied to select the bandwidths of filters, and the pros and cons of replacing the traditional linear polarizer with a polarization camera to measure pB. What started in 1990s as ground experiments conducted during total solar eclipses that lasted for a few minutes lead to a balloon borne experiment lasting eight hours in 2019 and will blossom into a space experiment on the International Space Station in 2023. Due to constraints on the bandwidths of the four filters, a successful mission requires quantification of the statistical error using Monte Carlo simulation to generate two feasibility profiles, which are unique to the design parameters of the coronagraph, to comprehend the feasibility to measure temperature and speed within the desired temporal and spatial resolutions. For the statistical error analysis, we use modeled K and F corona profiles, representative theoretical diffraction, scattering, and vignetting profiles, assumed efficiencies for lenses, mirrors, and polarizers, assumed detector properties on quantum efficiency, full well depth, dark noise, and read noise, and assumed instrument properties on aperture diameter, solid angle, and pixel resolution. We hope future white-light coronagraphs will exhibit capabilities to measure electron density, temperature, and speed.

Nelson Reginald↗

A stochastic-dynamic model for the spatial structure of forecast error statistics

The present investigation is concerned with the presentation of a simplified model of the spatial structure of forecast error statistics, a comparison of the model with actual numerical weather prediction results, and the extent to which simplifying assumptions made in the model are justified. A stochastic-dynamic model is derived for the spatial structure of the global atmospheric mass-field forecast error. The model states that the relative potential vorticity of the forecast error is random. The covariance function of the model's solutions is found to be governed by a simple deterministic equation. The agreement between the stochastic model and actual mass-field forecast errors fields for 12-36 h periods validates the assumptions on which the model is derived. Within this period, the difference between the potential voriticity fields of the atmosphere and of the numerical forecasts used in the comparison is well represented by white noise.

Balgovind, R.↗

On the error statistics of Viterbi decoding and the performance of concatenated codes

Computer simulation results are presented on the performance of convolutional codes of constraint lengths 7 and 10 concatenated with the (255, 223) Reed-Solomon code (a proposed NASA standard). These results indicate that as much as 0.8 dB can be gained by concatenating this Reed-Solomon code with a (10, 1/3) convolutional code, instead of the (7, 1/2) code currently used by the DSN. A mathematical model of Viterbi decoder burst-error statistics is developed and is validated through additional computer simulations.

Miller, R. L.↗

Phase error statistics of a phase-locked loop synchronized direct detection optical PPM communication system

Receiver timing synchronization of an optical Pulse-Position Modulation (PPM) communication system can be achieved using a phased-locked loop (PLL), provided the photodetector output is suitably processed. The magnitude of the PLL phase error is a good indicator of the timing error at the receiver decoder. The statistics of the phase error are investigated while varying several key system parameters such as PPM order, signal and background strengths, and PPL bandwidth. A practical optical communication system utilizing a laser diode transmitter and an avalanche photodiode in the receiver is described, and the sampled phase error data are presented. A linear regression analysis is applied to the data to obtain estimates of the relational constants involving the phase error variance and incident signal power.

Natarajan, Suresh↗

The GEOS Ozone Data Assimilation System: Specification of Error Statistics

A global three-dimensional ozone data assimilation system has been developed at the Data Assimilation Office of the NASA/Goddard Space Flight Center. The Total Ozone Mapping Spectrometer (TOMS) total ozone and the Solar Backscatter Ultraviolet (SBUV) or (SBUV/2) partial ozone profile observations are assimilated. The assimilation, into an off-line ozone transport model, is done using the global Physical-space Statistical Analysis Scheme (PSAS). This system became operational in December 1999. A detailed description of the statistical analysis scheme, and in particular, the forecast and observation error covariance models is given. A new global anisotropic horizontal forecast error correlation model accounts for a varying distribution of observations with latitude. Correlations are largest in the zonal direction in the tropics where data is sparse. Forecast error variance model is proportional to the ozone field. The forecast error covariance parameters were determined by maximum likelihood estimation. The error covariance models are validated using x squared statistics. The analyzed ozone fields in the winter 1992 are validated against independent observations from ozone sondes and HALOE. There is better than 10% agreement between mean Halogen Occultation Experiment (HALOE) and analysis fields between 70 and 0.2 hPa. The global root-mean-square (RMS) difference between TOMS observed and forecast values is less than 4%. The global RMS difference between SBUV observed and analyzed ozone between 50 and 3 hPa is less than 15%.

Stajner, Ivanka↗

Statistical error propagation in ab initio no-core full configuration calculations of light nuclei

We propagate the statistical uncertainty of experimental N N scattering data into the binding energy of 3 H and 4 He. Here, we also study the sensitivity of the magnetic moment and proton radius of the 3 H to changes in the N N interaction. The calculations are made with the no-core full configuration method in a sufficiently large harmonic oscillator basis. For those light nuclei we obtain Δ E stat (3H) = 0.015 MeV and Δ E stat ( 4 He) = 0.055 MeV .

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Statistical error analysis in CCD time-resolved photometry with applications to variable stars and quasars

Differential photometric time series obtained from CCD frames are tested for intrinsic variability using a newly developed analysis of variance technique. In general, the objects used for differential photometry will not all be of equal magnitude, so the techniques derived here explicitly correct for differences in the measured variances due to photon statistics. Other random-noise terms are also considered. The technique tests for the presence of intrinsic variability without regard to its random or periodic nature. It is then applied to observations of the variable stars ZZ Ceti and US 943 and the active extragalactic objects OQ 530, US 211, US 844, LB 9743, and OJ 287.

Howell, Steve B.↗

Spatial Variability of Winds and HRRR–NCEP Model Error Statistics at Three Doppler-Lidar Sites in the Wind-Energy Generation Region of the Columbia River Basin

Annually and seasonally averaged wind profiles from three Doppler lidars were gathered from sites in the Columbia River basin of east-central Oregon and Washington, a major region of wind-energy production, for the Second Wind Forecast Improvement Project (WFIP2) experiment. The profile data are used to quantify the spatial variability of wind flows in this area of complex terrain, to assess the HRRR-NCEP model's ability to capture spatial and temporal variability of wind profiles, and to evaluate model errors. Annually averaged measured wind speed differences over the 70-km extent of the lidar measurements reached 1 m s -1 within the wind-turbine rotor layer, and 2 m s -1 for 200-500 m AGL. Stronger wind speeds in the lowest 500 m occurred at sites higher in elevation, farther from the river, and farther west - closer to the Cascade Mountain barrier. Validating against the lidar data, the HRRR model underestimated strong wind speeds (>12 m s -1 ) and, consequently, their frequency of occurrence, especially at the two lowest-elevation sites, producing annual low biases in rotor-layer wind speed of 0.5 m s -1 . The RMSE between measured and modeled winds at all sites was about 3 m s -1 and did not degrade significantly with forecast lead time. The nature of the model errors was different for different seasons. Furthermore, although the three sites were located in the same basin terrain, the nature of the model errors was different at each site. Thus, if only one of the sites had been instrumented, different conclusions would have been drawn as to the major sources of model error, depending on where the measurements were made.

17 WIND ENERGY↗

Quantitative evaluation of statistical errors in small-angle X-ray scattering measurements

A new model is proposed for the measurement errors incurred in typical small-angle X-ray scattering (SAXS) experiments, which takes into account the setup geometry and physics of the measurement process. The model accurately captures the experimentally determined errors from a large range of synchrotron and in-house anode-based measurements. Its most general formulation gives for the variance of the buffer-subtracted SAXS intensity σ 2 ( q ) = [ I ( q ) + const.]/( kq ), where I ( q ) is the scattering intensity as a function of the momentum transfer q ; k and const. are fitting parameters that are characteristic of the experimental setup. The model gives a concrete procedure for calculating realistic measurement errors for simulated SAXS profiles. In addition, the results provide guidelines for optimizing SAXS measurements, which are in line with established procedures for SAXS experiments, and enable a quantitative evaluation of measurement errors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

On the convergence of statistics in simulations of stationary incompressible turbulent flows

When reporting statistics from simulations of statistically stationary chaotic phenomenon, it is important to verify that the simulations are time-converged. This condition is connected with the statistical error or number of digits with which statistics can be reliably reported. In this work we consider numerical experiments of low Reynolds number incompressible homogeneous and isotropic turbulence as a model problem to investigate statistical convergence over finite simulation times. Specifically, we investigate the time integration requirements that allow meaningful reporting of the statistical error associated with finiteness of the temporal domain. We address two key questions: (1) How long should a simulation be performed in terms of large eddy time, and (2) How should the simulation time be divided among temporal windows over which a quantity of interest is estimated so that its statistical error could be reliably reported? We find that reliable reporting of statistical errors requires simulations on the order of 10 4 large eddy times, which is orders of magnitude longer than typically performed. Additionally, data post-processing should employ windows of at least ten times the large eddy time scale, with the most robust computation of statistical error of the mean requiring window sizes of an additional factor of ten. For practical simulations, we demonstrate that it is possible to estimate the statistical error within a factor of two under a less stringent condition in which a minimum of four windows with size at least ten large eddy times are used. In conclusion, our observations for homogeneous isotropic turbulence are also shown to hold in turbulent channel flow.

42 ENGINEERING↗

Numerical error analysis of SOLPS-ITER simulations of EAST

Abstract Plasma edge simulations with codes like SOLPS-ITER are widely employed to interpret fusion experiments. However, numerical errors appearing in such simulations are rarely investigated, despite their potential large impact on simulation results. These errors consist of the statistical error and the bias, both resulting from the finite number of employed EIRENE Monte Carlo particles and incomplete convergence, and the discretization error due to the finite resolution of the computational grids. In this contribution, the resulting numerical errors on simulations of pure deuterium and neon seeded H-mode EAST discharges are examined. The statistical error can be kept small compared to other numerical error contributions by averaging the plasma profiles. This allows investigating the bias and discretization errors using Richardson extrapolation. It is shown that grid refinement and the number of employed Monte Carlo particles have the largest influence on the result, in agreement with similar studies of an ITER deuterium case. For the first time, numerical error bars on the entire simulated target profiles are determined showing that the largest numerical error is 17.9%, mainly due to the plasma grid discretization. On top, also numerical errors on simulated neutral pressures are investigated in detail, for which the statistical error is dominant. The analysis demonstrates which setup is needed to keep numerical errors limited: the SOLPS-ITER averaging procedure should be employed including enough EIRENE particles, and the involved grids should be sufficiently refined to reduce discretization errors.

Boeyaert, Dieter (ORCID:0000000309208660)↗

Overlapped embedded fragment stochastic density functional theory for covalently-bonded materials

The stochastic density functional theory (DFT) is a valuable linear-scaling approach to Kohn-Sham DFT that does not rely on the sparsity of the density matrix. Linear (and often sub-linear) scaling is achieved by introducing a controlled statistical error in the density, energy, and forces. The statistical error (noise) is proportional to the inverse square root of the number of stochastic orbitals and thus decreases slowly; however, by dividing the system into fragments that are embedded stochastically, the statistical error can be reduced significantly. This has been shown to provide remarkable results for non-covalently-bonded systems; however, the application to covalently bonded systems had limited success, particularly for delocalized electrons. Here, we show that the statistical error in the density correlates with both the density and the density matrix of the system and propose a new fragmentation scheme that elegantly interpolates between overlapped fragments. In conclusion, we assess the performance of the approach for bulk silicon of varying supercell sizes (up to N e = 16 384 electrons) and show that overlapped fragments reduce significantly the statistical noise even for systems with a delocalized density matrix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Propagation of statistical uncertainties in covariant density functional theory: Ground state observables and single-particle properties

Statistical errors in ground state observables and single-particle properties of spherical even-even nuclei and their propagation to the limits of nuclear landscape have been investigated in covariant density functional theory (CDFT) for the first time. Here, we consider only covariant energy density functionals with non-linear density dependency. Statistical errors for binding energies and neutron skins significantly increase on approaching two-neutron drip line. On the contrary, such a trend does not exist for statistical errors in charge radii and two-neutron separation energies. The absolute and relative energies of the single-particle states in the vicinity of the Fermi level are characterized by low statistical errors ($\sigma(e_i)\sim 0.1$ MeV). Statistical errors in the predictions of spin-orbit splittings are rather small. Statistical errors in physical observables are substantially smaller than related systematic uncertainties. As a result, at the present level of the development of theory, theoretical uncertainties at nuclear limits are dominated by systematic ones. Statistical errors in the description of physical observables related to the ground state and single-particle degrees of freedom are typically substantially lower in CDFT as compared with Skyrme density functional theory. The correlations between the model parameters are studied in detail. The parametric correlations are especially pronounced for the $g_2$ and $g_3$ parameters which are responsible for the density dependence of the model. The accounting of this fact potentially allows to reduce the number of free parameters of non-linear meson coupling model from six to five.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗