Tools for Quantum Algorithms, Protocols, Benchmarking, Architectural Design and Co-Design
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Quantum computing↗
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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.
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Error and Uncertainty Degrade Topographic Corrections of Remotely Sensed Data
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Jeff Dozier↗
Error and Uncertainty Degrade Topographic Corrections of Remotely Sensed Data
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Jeff Dozier↗
Error and Uncertainty Degrade Topographic Corrections of Remotely Sensed Data
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Jeff Dozier↗
Permanent Magnet Dipole-Quadrupole and Correcto-Tuner for Small Bore Accelerators
Electromagnets are used to bend electron beams and generate X-ray light. Permanent magnets have many advantages over electromagnets and are being studied as an alternative for small bore accelerators. This paper focuses on the mechanical design of two holders. First, a holder for the corrector and tuner permanent magnet assembly, which aims to correct the errors in the permanent magnetic field strength and orientation. Second, a holder for the dipole-quadrupole magnet assembly, which aims to provide the required magnetic strength to steer the electrons. Prototypes for the corrector, tuner and dipole-quadrupole holders were designed and tested to validate conceptual design. Results show that the corrector magnets can be oriented into a prescribed configuration, the tuner magnets can be oriented simultaneously regardless of the magnetic forces involved, and the dipole-quadrupole magnets can provide the magnetic strength required to steer electrons.
Huschke, Christopher↗
Enforcing constraints for time series prediction in supervised, unsupervised and reinforcement learning
We assume that we are given a time series of data from a dynamical system and our task is to learn the flow map of the dynamical system. We present a collection of results on how to enforce constraints coming from the dynamical system in order to accelerate the training of deep neural networks to represent the flow map of the system as well as increase their predictive ability. In particular, we provide ways to enforce constraints during training for all three major modes of learning, namely supervised, unsupervised and reinforcement learning. In general, the dynamic constraints need to include terms which are analogous to memory terms in model reduction formalisms. Such memory terms act as a restoring force which corrects the errors committed by the learned flow map during prediction. For supervised learning, the constraints are added to the objective function. For the case of unsupervised learning, in particular generative adversarial networks, the constraints are introduced by augmenting the input of the discriminator. Finally, for the case of reinforcement learning and in particular actor-critic methods, the constraints are added to the reward function. In addition, for the reinforcement learning case, we present a novel approach based on homotopy of the action-value function in order to stabilize and accelerate training. We use numerical results for the Lorenz system to illustrate the various constructions.
Stinis, Panagiotis↗
Error Transport using the Defect Correction Equations with Summation By Parts Operators.
Abstract not provided.
Logemann, Caleb↗
Radioactive Source Localization via Bayesian Particle Filter
In the event of a misplaced radioactive source or other emergency situation, measuring a radiation field, mapping its distribution, and determining a source location are essential tasks to ameliorating the situation. However, radiation fields may be extremely hazardous to human surveyors and minimizing received radiation doses is just as essential. Robots appear to be a potential solution to these problems. Beyond simply measuring radiation, the robot's computer processing capabilities offer a way to apply complex data analysis methods to radiation measurements in real-time. Methods which predict likely source locations can then feed this information into other processes, potentially improving path planning and enabling more efficient measurements. Given a robot mounted with a gamma-ray detector, can we: develop a methodology to account for detector performance across a wide range of source angles, distances, and photon energies? operate an autonomously navigating robot to effectively survey and characterize an area of interest? implement a data analysis method, conventionally used in measurements of motion, for source localization purposes? An open-source TurtleBot 3 robot, running Robot Operating System (ROS) on Ubuntu 16.04 LTS, was fitted with a Kromek GR1{sup R} Cadmium Zinc Telluride (CZT) solid-state gamma-ray detector. As a part of ROS, the packages OpenSlam, gmapping, and amcl were used to perform Simultaneous Localization and Mapping (SLAM), determining the robot's position and mapping the surrounding area. Data was acquired via Lidar mounted on top the TurtleBot 3. Detector Calibration Fit: The equation was fit to 365 counts of various energies, distances, and angles. A MATLAB{sup R} program was written to simulate measurements taken a robot on a random walk, with count data and positions discretized into finite element pixels. Using this program, a sample of 100 runs was performed on a map with a simulated source at the center, with a total of 200 of 2 pixels each. Similarly, multiple runs of the filter were performed on recorded robot measurement data. In both simulation and real tests, when corrected for errors (particles placed outside of bounds or on the robot, and simulation-specific errors), corresponding t-tests of predicted x and y-coordinates were within a 95% confidence interval of the actual position. For the real trial, these positions are slightly skewed right in the x-axis as the robot remained mainly to the left side of the source within the sample area. These simulations demonstrate potential validity for the usage of a particle filter as method of radioactive source localization. In the future, true real-time implementation and data fusion may further augment the performance of the robot to localize lost sources. Additionally, identification of multiple sources, determination of source types, and usage of a collimator are areas to potentially be explored.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
The Single Event Error (SEE) test and analysis of the CMS Endcap Timing Layer readout chip
The ETROC2, the first full size and full functionality prototype chip for the CMS Endcap Timing Layer readout, is strategically designed to meet the SEE immunity requirements of detector operation with the low power constraint. The triplicated periphery and pixel I2C configuration registers are designed with self-correction feature. The pixel readout control is centralized in the global readout and fully triplicated. The pixel readout is not triplicated, instead protected with power-efficient one-bit correction Hamming code. The TMR protection of the on-pixel threshold calibration can be turned off allowing the detection of the beam spot during the beam test by checking the bit-flips of the internal memory cells. In the initial proton beam test in January 2024, the chip readout process did not hang throughout the tests. The Hamming code correction strategy works because the error corrected TDC data were observed in the data frames. The error-injection simulation is performed to analy ze the small number of bit-flips in the configuration registers. We also performed SEE testing with a heavy ion beam in April and the data analysis is ongoing. The detailed design on the SEE immunity and the testing as well as simulation results will be presented, including follow-up SEE testing results in May and June 2024.
Gong, Datao↗
Improved Understanding of Coupled Water and Carbon Cycle Processes through Machine Learning Approaches
Focal Area(s): This white paper addresses how explainable machine learning (ML) algorithms can improve insights gained from complex data (Focal Area 3). We will also address how ML approaches related to sensor compression and low energy AI hardware can be used for efficient data acquisition (Focal Area 1). Science Challenge: We will focus on the coupled water cycle and carbon cycle processes in terrestrial ecosystems and terrestrial-aquatic interfaces. Thus, our approaches will be centered around several data-model integration challenges indicated in EESD strategic plans for two science focus areas: Terrestrial Ecosystem Science and Hydrobiogeochemistry. We can use AI to correct systematic model errors due to biases in either data or model structure/processes. Error patterns in model predictions usually vary by region, model, season etc. But there are systematic patterns in them. e.g., soil moisture tends to be overestimated in the arid western continental United States underestimated in wetter eastern USA; some land surface models tend to underestimate moisture in wet seasons and overestimate in dry seasons. Moreover, the consequences of extreme events (e.g., drought, extreme flooding, storm surges associated with tropical storms, hurricanes) on carbon cycle processes are not well represented in ecosystem and Earth system models. Redox-sensitive processes (e.g., rapid oxidation/reduction of iron and other redox-sensitive elements in soil microsites subjected to fluctuated hydrology) in terrestrial-aquatic interfaces further challenge model predictions of hot-spots (and hot-moments) due to poor understanding of underlying mechanisms. Thus, AI/ML approaches can be used to learn patterns in the data and model errors and use them to build model equations and correct process-based model errors.
54 ENVIRONMENTAL SCIENCES↗
Analysis of Long-Term Quality Control Data for a 137 Cs Dosimetry Calibration Source
Strict quality assurance programs are required for many radiological applications, but these seldom exist for verifying dosimetry calibration sources. After initial characterization of a dosimetry calibration facility, quality control procedures are recommended to ensure the early detection of any changes or malfunctions. These also result in refined knowledge about average dose rate and experimental variations in dose delivery. This paper describes the implementation of a phase I quality control protocol for a 137 Cs dosimetry calibration source and includes an analysis of the resulting data collected over a 24-mo period. During this time, substantial data was collected to establish trial control limits. Air kerma rate measurements were obtained using an ion chamber and were adjusted for decay, corrected for ambient temperature, pressure and humidity, and then analyzed using quality control charts. Three variations of rational subgrouping methods were used in order to find assignable causes of error, and Nelson's Rules were followed to detect any non-random statistical variations. Measurements were subgrouped according to same-day measurements in order to detect positional errors as well as atmospheric correction errors. Additionally, measurements were subgrouped according to analogous experimental setups in order to detect failure in equipment or incorrect settings. Both were analyzed using the X-bar and R chart method. Similarly, individuals and moving ranges charts were used to carefully examine each position in order to observe any situational errors that may occur which include timing, positional, or interference errors. Each method was successful in identifying unique out-of-control data points that occurred during the phase I application of forming control limits. Furthermore, over the 24-mo period, enough data points were deemed in-control to establish reliable trial limits. Future experiments will include the phase II application of gaining more reliable measurements in order to fine-tune the limits, as well as performing a designed experiment, where variables are purposefully changed in order to test the variation of the data.
61 RADIATION PROTECTION AND DOSIMETRY↗
Non-empirical, low-cost recovery of exact conditions with model-Hamiltonian inspired expressions in jmDFT
Density functional theory (DFT) is widely applied to both molecules and materials, but well known energetic delocalization and static correlation errors in practical exchange-correlation approximations limit quantitative accuracy. Common methods that correct energetic delocalization errors, such as the Hubbard U correction in DFT+U or Hartree-Fock exchange in global hybrids, do so at the cost of worsening static correlation errors. We recently introduced an alternate approach [Bajaj et al., J. Chem. Phys. 147, 191101 (2017)] known as judiciously modified DFT (jmDFT), wherein the deviation from exact behavior of semilocal functionals over both fractional spin and charge, i.e., the so-called flat plane, was used to motivate functional forms of second order analytic corrections. In this work, we introduce fully nonempirical expressions for all four coefficients in a DFT+U+J-inspired form of jmDFT, where all coefficients are obtained only from energies and eigenvalues of the integer-electron systems. We show good agreement for U and J coefficients obtained nonempirically as compared with the results of numerical fitting in a jmDFT U+J/J' correction. Incorporating the fully nonempirical jmDFT correction reduces and even eliminates the fractional spin error at the same time as eliminating the energetic delocalization error. We show that this approach extends beyond s-electron systems to higher angular momentum cases including p- and d-electrons. Finally, we diagnose some shortcomings of the current jmDFT approach that limit its ability to improve upon DFT results for cases such as weakly bound anions due to poor underlying semilocal functional behavior.
Delocalization↗
Stereoscopic distance perception
Limited cue, open-loop tasks in which a human observer indicates distances or relations among distances are discussed. By open-loop tasks, it is meant tasks in which the observer gets no feedback as to the accuracy of the responses. What happens when cues are added and when the loop is closed are considered. The implications of this research for the effectiveness of visual displays is discussed. Errors in visual distance tasks do not necessarily mean that the percept is in error. The error could arise in transformations that intervene between the percept and the response. It is argued that the percept is in error. It is also argued that there exist post-perceptual transformations that may contribute to the error or be modified by feedback to correct for the error.
Foley, John M.↗
Bio-Optics of the Chesapeake Bay from Measurements and Radiative Transfer Calculations
We combined detailed bio-optical measurements and radiative transfer (RT) modeling to perform an optical closure experiment for optically complex and biologically productive Chesapeake Bay waters. We used this experiment to evaluate certain assumptions commonly used when modeling bio-optical processes, and to investigate the relative importance of several optical characteristics needed to accurately model and interpret remote sensing ocean-color observations in these Case 2 waters. Direct measurements were made of the magnitude, variability, and spectral characteristics of backscattering and absorption that are critical for accurate parameterizations in satellite bio-optical algorithms and underwater RT simulations. We found that the ratio of backscattering to total scattering in the mid-mesohaline Chesapeake Bay varied considerably depending on particulate loading, distance from land, and mixing processes, and had an average value of 0.0128 at 530 nm. Incorporating information on the magnitude, variability, and spectral characteristics of particulate backscattering into the RT model, rather than using a volume scattering function commonly assumed for turbid waters, was critical to obtaining agreement between RT calculations and measured radiometric quantities. In situ measurements of absorption coefficients need to be corrected for systematic overestimation due to scattering errors, and this correction commonly employs the assumption that absorption by particulate matter at near infrared wavelengths is zero.
Tzortziou, Maria↗
Evaluation of the TOPEX/POSEIDON altimeter system over the Great Lakes
The TOPEX/POSEIDON altimeter measurment system is evaluated for the first 46 repeat cycles (September 23, 1992-December 23, 1992) using tracks over the Great Lakes. The temporal variations in lake level are removed from the altimeter measurements using in-situ lake level measurements, thus permitting the performance of the altimeter system to be assessed. For the NASA altimeter, the root-mean-square (RMS) scatter of the residuals is 3.95 cm using all the tracks over the lakes. However, some of the scatter in this result is probably due to lake tides or seiche, which can amount to a few centimeters amplitude near the ends of the lakes. When the seven best tracks are used, which cross the center of the lakes where tides/seiche effects are minimal, the RMS error is included to either 2.9 or 3.0 cm, depending on whether the Centre National d'Etudes Spatiales (CNES) or NASA orbit is used. This places an upper limit on the error budget of the altimeter system, excluding ocean tides and inverse barometer effect. There are several short-period variations in the residuals. The most pronounced is a 55-day period, with a 1-cm amplitude, which we believe is (at least in part) due to orbit error. When the model-derived wet tropospheric correction is substituted for the TOPEX microwave radiometer correction, the RMS error increases significantly, possibly resulting in an annual cycle of a few centimeters. Evaluation of the ionospheric correction indicates that the dual-frequency correction provides an average improvement of 0.85 cm over the Doppler orbitography and radiopositioning integrated by satellite (DORIS) correction. Although there are insufficient data to directly assess the CNES altimeter, the relative bias between the altimeters is estimated to be either -14.3 or -15.6 cm (NASA altimeter measuring short), depending on whether the DORIS or dual-frequency ionospheric correction is applied to the NASA altimeter.
Morris, Charles S.↗
SNPP and NOAA-20 VIIRS On-Orbit Geolocation Trending and Improvements
Two Visible Infrared Imaging Radiometer Suite (VIIRS) sensors have been in operations for more than 8.5 and 2.5 years since they were launched in October 2011 on SNPP satellite and in November 2017 on NOAA-20 satellite, respectively. These are two satellites in the Join Polar Satellite System (JPSS) constellation, of which Suomi National Polar-orbiting Partnership (SNPP) is a risk reduction satellite and NOAA-20 is the first of four JPSS satellites(JPSS-1 became NOAA-20 after launch). Accurate geolocation is a critical element in data calibration for accurate retrieval of global biogeophysical parameters. In this paper, we describe the latest trends in the continuously improved geolocation accuracy in VIIRS Collection-1 (C1) and C2 re-processing. We implemented a VIIRS instrument geometric model update (VIGMU)for both sensors that correct for geolocation error oscilations in the scan direction. We borrowed code from Moderate Resolution Imaging Spectroradiometer (MODIS) geolocation software to correct for time-dependent pointing variations, that are particularly acute in NOAA-20 VIIRS, and some pointing anomalies in SNPP VIIRS. We developed a Kalman Filter using gyrodata to correct for attitude errors due to the degradation of the star trackers performance from the SNPP satellite. We also present an improved ground control point matching (CPM) tool, in which the ground control point (GCP) chips library is refreshed using recently launched Landsat-8 images.
SNPP↗
A method for simultaneous linear optics and coupling correction for storage rings with turn-by-turn beam position monitor data
We propose a method to simultaneously correct linear optics errors and linear coupling for storage rings using turn-by-turn (TbT) beam position monitor (BPM) data. The independent component analysis (ICA) method is used to isolate the betatron normal modes from the measured TbT BPM data. The betatron amplitudes and phase advances of the projections of the normal modes on the horizontal and vertical planes are then extracted, which, combined with dispersion measurement, are used to fit the lattice model. The fitting results are used for lattice correction. The method has been successfully demonstrated on the NSLS-II storage ring.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Active Full-Shell Grazing-Incidence Optics
MSFC has a long history of developing full-shell grazing-incidence x-ray optics for both narrow (pointed) and wide field (surveying) applications. The concept presented in this paper shows the potential to use active optics to switch between narrow and wide-field geometries, while maintaining large effective area and high angular resolution. In addition, active optics has the potential to reduce errors due to mounting and manufacturing lightweight optics. The design presented corrects low spatial frequency error and has significantly fewer actuators than other concepts presented thus far in the field of active x-ray optics. Using a finite element model, influence functions are calculated using active components on a full-shell grazing-incidence optic. Next, the ability of the active optic to effect a change of optical prescription and to correct for errors due to manufacturing and mounting is modeled.
Full-shell↗