Self-Correction from Higher-Form Symmetry Protection on a Boundary
Not Available
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
SEARCH · Engineering Papers
Results for “error correction.”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Erratum: “Adiabatic matching of particle bunches in a plasma-based accelerator in the presence of ion motion” [Phys. Plasmas 28 , 053102 (2021)]
We would like to correct an error affecting the horizontal scale of panels (c) and (d) of Fig. 4 in Ref. 1. A scale factor of k p was neglected when generating the plots. The correct figure is shown below. Further, the authors would like to thank Yujian Zhao for pointing out this issue. We would also like to correct a typo introduced during the preparation of the proofs and affecting Eq. (25); the correct equation reads. (Formula presented). All the conclusions of the paper are unaffected.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Efficient bit-error detecting code
Two highly reliable codes termed "Modified b-adjacent interleaving codes" provide fail-safe operation of launch processing and control system in which common memory is coordination point for interconnection of up to 64 minicomputers. Codes detect and correct bit errors in computer data transmission.
Hockenberger, R. W.↗
Image Guidance During Head-and-Neck Cancer Radiation Therapy: Analysis of Alignment Trends With In-Room Cone-Beam Computed Tomography Scans
Purpose: On-board cone-beam computed tomography (CBCT) is currently available for alignment of patients with head-and-neck cancer before radiotherapy. However, daily CBCT is time intensive and increases the overall radiation dose. We assessed the feasibility of using the average couch shifts from the first several CBCTs to estimate and correct for the presumed systematic setup error. Methods and Materials: 56 patients with head-and-neck cancer who received daily CBCT before intensity-modulated radiation therapy had recorded shift values in the medial-lateral, superior-inferior, and anterior-posterior dimensions. The average displacements in each direction were calculated for each patient based on the first five or 10 CBCT shifts and were presumed to represent the systematic setup error. The residual error after this correction was determined by subtracting the calculated shifts from the shifts obtained using daily CBCT. Results: The magnitude of the average daily residual three-dimensional (3D) error was 4.8 {+-} 1.4 mm, 3.9 {+-} 1.3 mm, and 3.7 {+-} 1.1 mm for uncorrected, five CBCT corrected, and 10 CBCT corrected protocols, respectively. With no image guidance, 40.8% of fractions would have been >5 mm off target. Using the first five CBCT shifts to correct subsequent fractions, this percentage decreased to 19.0% of all fractions delivered and decreased the percentage of patients with average daily 3D errors >5 mm from 35.7% to 14.3% vs. no image guidance. Using an average of the first 10 CBCT shifts did not significantly improve this outcome. Conclusions: Using the first five CBCT shift measurements as an estimation of the systematic setup error improves daily setup accuracy for a subset of patients with head-and-neck cancer receiving intensity-modulated radiation therapy and primarily benefited those with large 3D correction vectors (>5 mm). Daily CBCT is still necessary until methods are developed that more accurately determine which patients may benefit from alternative imaging strategies.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Fabrication-conscious neural network based inverse design of single-material variable-index multilayer films
Multilayer films with continuously varying indices for each layer have attracted great deal of attention due to their superior optical, mechanical, and thermal properties. However, difficulties in fabrication have limited their application and study in scientific literature compared to multilayer films with fixed index layers. In this work we propose a neural network based inverse design technique enabled by a differentiable analytical solver for realistic design and fabrication of single material variable-index multilayer films. This approach generates multilayer films with excellent performance under ideal conditions. We furthermore address the issue of how to translate these ideal designs into practical useful devices which will naturally suffer from growth imperfections. By integrating simulated systematic and random errors just as a deposition tool would into the optimization process, we demonstrated that the same neural network that produced the ideal device can be retrained to produce designs compensating for systematic deposition errors. Furthermore, the proposed approach corrects for systematic errors even in the presence of random fabrication imperfections. The results outlined in this paper provide a practical and experimentally viable approach for the design of single material multilayer film stacks for an extremely wide variety of practical applications with high performance.
36 MATERIALS SCIENCE↗
An investigation of the energy balance of solar active regions using the ACRIM irradiance data
The detection of a significant correlation between the solar irradiance, corrected for flux deficit due to sunspots, and both the 205 nm flux and a photometric facular index were examined. A detailed analysis supports facular emission as the more likely source of correlation with the corrected radiance, rather then the error in sunspot correction. A computer program which simulates two dimensional convection in a compressible, stratified medium was investigated. Subroutines to calculate ionization and other thermodynamic variables were also completed.
Petro, L. D.↗
Heterogeneous reactions of HNO3(g) + NaCl(s) yields HCl(g) + NaNO3(s) and N2O5(g) + NaCl(s) yields ClNO2(g) + NaNO3(s)
The heterogeneous reactions of HNO3(g) + NaCl(s) yields HCl(g) + NaNO3(s) (eq 1) and N2O5(g) + NaCl(s) yields ClNO2(g) + NaNO3(S) (eq 2) were investigated over the temperature range 223-296 K in a flow-tube reactor coupled to a quadrupole mass spectrometer. Either a chemical ionization mass spectrometer (CIMS) or an electron-impact ionization mass spectrometer (EIMS) was used to provide suitable detection sensitivity and selectivity. In order to mimic atmospheric conditions, partial pressures of HNO3 and N2O5 in the range 6 x 10(exp -8) - 2 x 10(exp -6) Torr were used. Granule sizes and surface roughness of the solid NaCl substrates were determined by using a scanning electron microscope. For dry NaCl substrates, decay rates of HNO3 were used to obtain gamma(1) = 0.013 +/- 0.004 (1sigma) at 296 K and > 0.008 at 223 K, respectively. The error quoted is the statistical error. After all corrections were made, the overall error, including systematic error, was estimated to be about a factor of 2. HCl was found to be the sole gas-phase product of reaction 1. The mechanism changed from heterogeneous reaction to predominantly physical adsorption when the reactor was cooled from 296 to 223 K. For reaction 2 using dry salts, gamma(2) was found to be less than 1.0 x 10(exp -4) at both 223 and 296 K. The gas-phase reaction product was identified as ClNO2 in previous studies using an infrared spectrometer. An enhancement in reaction probability was observed if water was not completely removed from salt surfaces, probably due to the reaction of N2O5(g) + H2O(s) yields 2HNO3(g). Our results are compared with previous literature values obtained using different experimental techniques and conditions. The implications of the present results for the enhancement of the hydrogen chloride column density in the lower stratosphere after the El Chichon volcanic eruption and for the chemistry of HCl and HNO3 in the marine troposphere are discussed.
Leu, Ming-Taun↗
Characterization of the Impact of Soft Errors on Iterative Methods
Soft errors caused by transient bit flips have the potential to significantly impact an application’s behavior. This has motivated the design of an array of techniques to detect, isolate, and correct soft errors using microarchitectural, architectural, compilation-based, or application-level techniques to minimize their impact on the executing application. The first step towards the design of good error detection/correction techniques involves an understanding of an application’s vulnerability to soft errors. In this paper, we present the first comprehensive characterization of the impact of soft errors on the convergence characteristics of six iterative methods using application-level fault injection. In particular, we consider the use of iterative methods to incrementally solve a linear systems of equations, which constitutes the core kernel in many scientific applications. We analyze the impact of soft errors in terms of the type of error (single- vs multi-bit), the distribution and location of bits affected, the data structure and the statement impacted, and variation with time. In addition to understanding the vulnerability of iterative solvers to soft errors, this characterization can aid the design of fault injection campaigns that ensure systematic coverage.
fault injection, iterative methods, Silent data co↗
The impact of detection rate changes and correlations on random-coincidence background measurements
Coincidence detection of multiple particles emitted during an experiment can yield a new depth of understanding of the underlying process under study. However, the probability of detecting particles that are generated from the same physical event within a given coincidence time window is generally much lower than that of detecting particles that appear in the same coincidence time window, but were not created from the same physical event, and are therefore detected randomly in coincidence with each other. Thus, accurate and precise methods of measuring this random-coincidence background are essential for a wide variety of fields of science. A method to determine this background directly using the data themselves without any additional experimental run time or fake signals introduced in the data was recently established (O’Donnell, 2016). This method yields a statistical uncertainty on the random-coincidence background that is orders of magnitude smaller than that of the true coincidence data, though the potential for systematic errors of backgrounds from this method was never explored. In this work, we discuss common varieties of correlated and uncorrelated changes in the detection rates of each particle detected in an experiment. Here we demonstrate here that a correlation between particle detection rates from, for example, an incident particle beam that initiates a physical process of interest, creates systematic errors in the random-coincidence background measurement. We also discuss the impact of a variety of other realistic scenarios for rate changes in experiments. Lastly, a method is introduced to correct for errors in the random-coincidence background from any source, yielding an optimization between statistical precision and eliminating potential lingering systematic errors.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Effect of rawinsonde errors on rocketsonde density and pressure profiles: An error analysis of the Rawinsonde System
An initial value of pressure is required to derive the density and pressure profiles of the rocketborne rocketsonde sensor. This tie-on pressure value is obtained from the nearest rawinsonde launch at an altitude where overlapping rawinsonde and rocketsonde measurements occur. An error analysis was performed of the error sources in these sensors that contribute to the error in the tie-on pressure. It was determined that significant tie-on pressure errors result from radiation errors in the rawinsonde rod thermistor, and temperature calibration bias errors. To minimize the effect of these errors radiation corrections should be made to the rawinsonde temperature and the tie-on altitude should be chosen at the lowest altitude of overlapping data. Under these conditions the tie-on error, and consequently the resulting error in the Datasonde pressure and density profiles is less tha 1%. The effect of rawinsonde pressure and temperature errors on the wind and temperature versus height profiles of the rawinsonde was also determined.
Luers, J. K.↗
Analysis of a Coded, M-ary Orthogonal Input Optical Channel with Random-gain Photomultiplier Detection
Performance of two coding systems is analyzed for a noisy optical channel with M(=2(L)-ary orthogonal signaling and random gain photomultiplier detection. The considered coding systems are the Reed Solomon (RS) coding with error only correction decoding and the interleaved binary convolutional system with soft decision Viterbi decoding. The required average number of received signal photons per information bit, N sub b, for a desired bit error of 0.000001 is found for a set of commonly used parameters and with a high background noise level. We find that the interleaved binary convolutional coding system is preferable to the RS coding system in performance complexity tradeoffs.
Lee, P. J.↗
Note: Derivation of two-photon circular dichroism—Addendum to “Two-photon circular dichroism” [J. Chem. Phys. 62, 1006 (1975)]
This addendum shows the detailed derivation of the fundamental equations for two-photon circular dichroism which are given in a very condensed form in the original publication [I. Tinoco, J. Chem. Phys. 62, 1006 (1975)]. In addition, some minor errors are corrected and some of the derivations in the original publication are commented.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
ELLIPTICAL WEIGHTED HOLICs FOR WEAK LENSING SHEAR MEASUREMENT. III. THE EFFECT OF RANDOM COUNT NOISE ON IMAGE MOMENTS IN WEAK LENSING ANALYSIS
This is the third paper on the improvement of systematic errors in weak lensing analysis using an elliptical weight function, referred to as E-HOLICs. In previous papers, we succeeded in avoiding errors that depend on the ellipticity of the background image. In this paper, we investigate the systematic error that depends on the signal-to-noise ratio of the background image. We find that the origin of this error is the random count noise that comes from the Poisson noise of sky counts. The random count noise makes additional moments and centroid shift error, and those first-order effects are canceled in averaging, but the second-order effects are not canceled. We derive the formulae that correct this systematic error due to the random count noise in measuring the moments and ellipticity of the background image. The correction formulae obtained are expressed as combinations of complex moments of the image, and thus can correct the systematic errors caused by each object. We test their validity using a simulated image and find that the systematic error becomes less than 1% in the measured ellipticity for objects with an IMCAT significance threshold of {nu} {approx} 11.7.
79 ASTRONOMY AND ASTROPHYSICS↗
Airplane wing vibrations due to atmospheric turbulence
The magnitude of error introduced due to wing vibration when measuring atmospheric turbulence with a wind probe mounted at the wing tip was studied. It was also determined whether accelerometers mounted on the wing tip are needed to correct this error. A spectrum analysis approach is used to determine the error. Estimates of the B-57 wing characteristics are used to simulate the airplane wing, and von Karman's cross spectrum function is used to simulate atmospheric turbulence. It was found that wing vibration introduces large error in measured spectra of turbulence in the frequency's range close to the natural frequencies of the wing.
Pastel, R. L.↗
Error Reduction Methods for Integrated-path Differential-absorption Lidar Measurements
We report new modeling and error reduction methods for differential-absorption optical-depth (DAOD) measurements of atmospheric constituents using direct-detection integrated-path differential-absorption lidars. Errors from laser frequency noise are quantified in terms of the line center fluctuation and spectral line shape of the laser pulses, revealing relationships verified experimentally. A significant DAOD bias is removed by introducing a correction factor. Errors from surface height and reflectance variations can be reduced to tolerable levels by incorporating altimetry knowledge and "log after averaging", or by pointing the laser and receiver to a fixed surface spot during each wavelength cycle to shorten the time of "averaging before log".
averging before log↗
SU-E-J-15: A Patient-Centered Scheme to Mitigate Impacts of Treatment Setup Error
Purpose: Current Intensity Modulated Radiation Therapy (IMRT) is plan-centered. At each treatment fraction, we position the patient to match the setup in treatment plan. Inaccurate setup can compromise delivered dose distribution, and hence leading to suboptimal treatments. Moreover, current setup approach via couch shift under image guidance can correct translational errors, while rotational and deformation errors are hard to address. To overcome these problems, we propose in this abstract a patient-centered scheme to mitigate impacts of treatment setup errors. Methods: In the patient-centered scheme, we first position the patient on the couch approximately matching the planned-setup. Our Supercomputing Online Replanning Environment (SCORE) is then employed to design an optimal treatment plan based on the daily patient geometry. It hence mitigates the impacts of treatment setup error and reduces the requirements on setup accuracy. We have conducted simulations studies in 10 head-and-neck (HN) patients to investigate the feasibility of this scheme. Rotational and deformation setup errors were simulated. Specifically, 1, 3, 5, 7 degrees of rotations were put on pitch, roll, and yaw directions; deformation errors were simulated by splitting neck movements into four basic types: rotation, lateral bending, flexion and extension. Setup variation ranges are based on observed numbers in previous studies. Dosimetric impacts of our scheme were evaluated on PTVs and OARs in comparison with original plan dose with original geometry and original plan recalculated dose with new setup geometries. Results: With conventional plan-centered approach, setup error could lead to significant PTV D99 decrease (−0.25∼+32.42%) and contralateral-parotid Dmean increase (−35.09∼+42.90%). The patientcentered approach is effective in mitigating such impacts to 0∼+0.20% and −0.03∼+5.01%, respectively. Computation time is <128 s. Conclusion: Patient-centered scheme is proposed to mitigate setup error impacts using replanning. Its superiority in terms of dosimetric impacts and feasibility has been shown through simulation studies on HN cases.
60 APPLIED LIFE SCIENCES↗
Improved Use of Satellite Imagery to Forecast Hurricanes
This project tested a novel method that uses satellite imagery to correct phase errors in the initial state for numerical weather prediction, applied to hurricane forecasts. The system was tested on hurricanes Guillermo (1997), Felicia (1997) and Iniki (1992). We compared the performance of the system with and without phase correction to a procedure that uses bogus data in the initial state, similar to current operational procedures. The phase correction keeps the hurricane on track in the analysis and is far superior to a system without phase correction. Compared to operational procedure, phase correction generates somewhat worse 3-day forecast of the hurricane track, but better forecast of intensity. It is believed that the phase correction module would work best in the context of 4-dimensional variational data assimilation. Very little modification to 4DVar would be required.
Louis, Jean-Francois↗
A machine learning approach for efficient multi-dimensional integration
Many physics problems involve integration in multi-dimensional space whose analytic solution is not available. The integrals can be evaluated using numerical integration methods, but it requires a large computational cost in some cases, so an efficient algorithm plays an important role in solving the physics problems. We propose a novel numerical multi-dimensional integration algorithm using machine learning (ML). After training a ML regression model to mimic a target integrand, the regression model is used to evaluate an approximation of the integral. Then, the difference between the approximation and the true answer is calculated to correct the bias in the approximation of the integral induced by ML prediction errors. Because of the bias correction, the final estimate of the integral is unbiased and has a statistically correct error estimation. Three ML models of multi-layer perceptron, gradient boosting decision tree, and Gaussian process regression algorithms are investigated. The performance of the proposed algorithm is demonstrated on six different families of integrands that typically appear in physics problems at various dimensions and integrand difficulties. The results show that, for the same total number of integrand evaluations, the new algorithm provides integral estimates with more than an order of magnitude smaller uncertainties than those of the VEGAS algorithm in most of the test cases.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗