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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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Fully quantum algorithm for mesoscale fluid simulations with application to partial differential equations

Fluid flow simulations marshal our most powerful computational resources. In many cases, even this is not enough. Quantum computers provide an opportunity to speed up traditional algorithms for flow simulations. We show that lattice-based mesoscale numerical methods can be executed as efficient quantum algorithms due to their statistical features. This approach revises a quantum algorithm for lattice gas automata to reduce classical computations and state preparation at every time step. For this, the algorithm approximates the qubit relative phases and subtracts them at the end of each time step. Phases are evaluated using the iterative phase estimation algorithm and subtracted using single-qubit rotation phase gates. Further, this method optimizes the quantum resource required and makes it more appropriate for near-term quantum hardware. We also demonstrate how the checkerboard deficiency that the D1Q2 scheme presents can be resolved using the D1Q3 scheme. The algorithm is validated by simulating two canonical partial differential equations: the diffusion and Burgers' equations on different quantum simulators. We find good agreement between quantum simulations and classical solutions for the presented algorithm.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Translation-Invariant Quantum Algorithms for Ordered Search are Optimal

Ordered search is the task of finding an item in an ordered list using comparison queries. The best exact classical algorithm for this fundamental problem uses [log 2 n] queries for a list of length n. Quantum computers can achieve a constant-factor speedup, but the best possible coefficient of log 2 n for exact quantum algorithms is only known to lie between (ln2)/π ≈ 0.221 and 4/log 2 605 ≈ 0.4333. We consider a special class of translation-invariant algorithms with no workspace, introduced by Farhi, Goldstone, Gutmann, and Sipser, that has been used to find the best known upper bounds. First, we show that any bounded-error, k-query quantum algorithm for ordered search can be implemented by a k-query algorithm in this special class. Second, we use linear programming to show that the best exact 5-query quantum algorithm can search a list of length 7265, giving an ordered search algorithm that asymptotically uses 5 log 7265 n ≈ 0.390 log 2 n quantum queries.

Translation-invariant quantum algorithms↗
NASA NTRS2014

Improved Algorithms for Accurate Retrieval of UV - Visible Diffuse Attenuation Coefficients in Optically Complex, Inshore Waters

Photochemical processes driven by high-energy ultraviolet radiation (UVR) in inshore, estuarine, and coastal waters play an important role in global bio geochemical cycles and biological systems. A key to modeling photochemical processes in these optically complex waters is an accurate description of the vertical distribution of UVR in the water column which can be obtained using the diffuse attenuation coefficients of down welling irradiance (Kd()). The Sea UV Sea UVc algorithms (Fichot et al., 2008) can accurately retrieve Kd ( 320, 340, 380,412, 443 and 490 nm) in oceanic and coastal waters using multispectral remote sensing reflectances (Rrs(), Sea WiFS bands). However, SeaUVSeaUVc algorithms are currently not optimized for use in optically complex, inshore waters, where they tend to severely underestimate Kd(). Here, a new training data set of optical properties collected in optically complex, inshore waters was used to re-parameterize the published SeaUVSeaUVc algorithms, resulting in improved Kd() retrievals for turbid, estuarine waters. Although the updated SeaUVSeaUVc algorithms perform best in optically complex waters, the published SeaUVSeaUVc models still perform well in most coastal and oceanic waters. Therefore, we propose a composite set of SeaUVSeaUVc algorithms, optimized for Kd() retrieval in almost all marine systems, ranging from oceanic to inshore waters. The composite algorithm set can retrieve Kd from ocean color with good accuracy across this wide range of water types (e.g., within 13 mean relative error for Kd(340)). A validation step using three independent, in situ data sets indicates that the composite SeaUVSeaUVc can generate accurate Kd values from 320 490 nm using satellite imagery on a global scale. Taking advantage of the inherent benefits of our statistical methods, we pooled the validation data with the training set, obtaining an optimized composite model for estimating Kd() in UV wavelengths for almost all marine waters. This optimized composite set of SeaUVSeaUVc algorithms will provide the optical community with improved ability to quantify the role of solar UV radiation in photochemical and photobiological processes in the ocean.

UV↗
NASA NTRS2014

Algorithm Development and Validation of CDOM Properties for Estuarine and Continental Shelf Waters Along the Northeastern U.S. Coast

An extensive set of field measurements have been collected throughout the continental margin of the northeastern U.S. from 2004 to 2011 to develop and validate ocean color satellite algorithms for the retrieval of the absorption coefficient of chromophoric dissolved organic matter (aCDOM) and CDOM spectral slopes for the 275:295 nm and 300:600 nm spectral range (S275:295 and S300:600). Remote sensing reflectance (Rrs) measurements computed from in-water radiometry profiles along with aCDOM() data are applied to develop several types of algorithms for the SeaWiFS and MODIS-Aqua ocean color satellite sensors, which involve least squares linear regression of aCDOM() with (1) Rrs band ratios, (2) quasi-analytical algorithm-based (QAA based) products of total absorption coefficients, (3) multiple Rrs bands within a multiple linear regression (MLR) analysis, and (4) diffuse attenuation coefficient (Kd). The relative error (mean absolute percent difference; MAPD) for the MLR retrievals of aCDOM(275), aCDOM(355), aCDOM(380), aCDOM(412) and aCDOM(443) for our study region range from 20.4-23.9 for MODIS-Aqua and 27.3-30 for SeaWiFS. Because of the narrower range of CDOM spectral slope values, the MAPD for the MLR S275:295 and QAA-based S300:600 algorithms are much lower ranging from 9.9 and 8.3 for SeaWiFS, respectively, and 8.7 and 6.3 for MODIS, respectively. Seasonal and spatial MODIS-Aqua and SeaWiFS distributions of aCDOM, S275:295 and S300:600 processed with these algorithms are consistent with field measurements and the processes that impact CDOM levels along the continental shelf of the northeastern U.S. Several satellite data processing factors correlate with higher uncertainty in satellite retrievals of aCDOM, S275:295 and S300:600 within the coastal ocean, including solar zenith angle, sensor viewing angle, and atmospheric products applied for atmospheric corrections. Algorithms that include ultraviolet Rrs bands provide a better fit to field measurements than algorithms without the ultraviolet Rrs bands. This suggests that satellite sensors with ultraviolet capability could provide better retrievals of CDOM. Because of the strong correlations between CDOM parameters and DOM constituents in the coastal ocean, satellite observations of CDOM parameters can be applied to study the distributions, sources and sinks of DOM, which are relevant for understanding the carbon cycle, modeling the Earth system, and to discern how the Earth is changing.

CDOM Properties↗
NASA NTRS2015

Retrieval of Aerosol Microphysical Properties from AERONET Photo-Polarimetric Measurements. 2: A New Research Algorithm and Case Demonstration

A new research algorithm is presented here as the second part of a two-part study to retrieve aerosol microphysical properties from the multispectral and multiangular photopolarimetric measurements taken by Aerosol Robotic Network's (AERONET's) new-generation Sun photometer. The algorithm uses an advanced UNified and Linearized Vector Radiative Transfer Model and incorporates a statistical optimization approach.While the new algorithmhas heritage from AERONET operational inversion algorithm in constraining a priori and retrieval smoothness, it has two new features. First, the new algorithmretrieves the effective radius, effective variance, and total volume of aerosols associated with a continuous bimodal particle size distribution (PSD) function, while the AERONET operational algorithm retrieves aerosol volume over 22 size bins. Second, our algorithm retrieves complex refractive indices for both fine and coarsemodes,while the AERONET operational algorithm assumes a size-independent aerosol refractive index. Mode-resolved refractive indices can improve the estimate of the single-scattering albedo (SSA) for each aerosol mode and thus facilitate the validation of satellite products and chemistry transport models. We applied the algorithm to a suite of real cases over Beijing_RADI site and found that our retrievals are overall consistent with AERONET operational inversions but can offer mode-resolved refractive index and SSA with acceptable accuracy for the aerosol composed by spherical particles. Along with the retrieval using both radiance and polarization, we also performed radiance-only retrieval to demonstrate the improvements by adding polarization in the inversion. Contrast analysis indicates that with polarization, retrieval error can be reduced by over 50% in PSD parameters, 10-30% in the refractive index, and 10-40% in SSA, which is consistent with theoretical analysis presented in the companion paper of this two-part study.

aerosol retrieval algorithm↗
NASA NTRS2020

Dust Aerosol Retrieval Over the Oceans With the MODIS/VIIRS Dark‐Target Algorithm: 1. Dust Detection

To prepare for implementation of a new aerosol retrieval specifically designed for dust aerosol over ocean in the operational Dark-Target (DT) algorithms for the Moderate-resolution Imaging Spectrometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) satellite sensors, we focus on the challenge of detecting dust. We first survey the literature on existing dust detection algorithms and then develop an innovative algorithm that combines near-UV (deep blue), visible, and thermal infrared (TIR) wavelength spectral tests. The new detection algorithm is applied to Terra and Aqua MODIS granules and compared with other dust detection possibilities from existing MODIS products. Quantitative evaluation of the new dust detection algorithm is conducted using both a collocated AERONET-MODIS data set and collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO)-MODIS data set. From comparison with both AERONET and CALIOP measurements, we estimate the new dust detection algorithm detects about 30% of weakly dusty pixels and more than 80% of heavily dusty pixels, with false detections in the range of 1–2%. The very low false detection rate is particularly noteworthy in comparison with existing literature. Compared with the dust flag currently available as part of the MODIS cloud mask product (MOD35/MYD35), and dust classification based on commonly used thresholds with aerosol optical depth (AOD) and Angstrom exponent (AE), the new dust detection algorithm finds more dusty pixels and fewer false detections.

spectral dust detection↗
NASA NTRS2021

A Dark Target research aerosol algorithm for MODIS observations over eastern China: increasing coverage while maintaining accuracy at high aerosol loading

Satellite aerosol products such as the Dark Target (DT) produced from the MODerate resolution Imaging Spectroradiometer (MODIS) are useful for monitoring the progress of air pollution. Unfortunately, the DT often fails to retrieve during the heaviest aerosol events as well as the more moderate events in winter. Some of the literature at-tributes this lack of retrieval to the cloud mask. However, we found this lack of retrieval is mainly traced to thresholds used for masking of inland water and snow. Modifications to these two masks greatly increase 50 % of the retrievals of aerosol optical depth at 0.55 μm (AOD) greater than 1.0. The “extra”-high-AOD retrievals tend to be biased when com-pared with a ground-based sun photometer (AErosol RObotic NETwork, AERONET). Reducing bias in new retrievals re-quires two additional steps. One is an update to the assumed aerosol optical properties (aerosol model); the haze in this region is both less absorbing and lower in altitude than what is assumed in the global algorithm. The second is account-ing for the scale height of the aerosol, specifically that the heavy-aerosol events in the region are much closer to the surface than what is assumed by the global DT algorithm. The resulting combination of modified masking thresholds, new aerosol model, and lower aerosol layer scale height was applied to 3 months of MODIS observations (January–March2013) over eastern China. After these two additional steps are implemented, the significant increase in new retrievals introduces no overall bias at a high-AOD regime but does degrade other overall validation statistics. We also find that the research algorithm is able to identify additional pollution events that AERONET instruments may not due to different spatial sampling. Mean AOD retrieved from the re-search algorithm increases from 0.11 to 0.18 compared to values calculated from the operational DT algorithm during January to March of 2013 over the study area. But near Beijing, where the severe pollution occurs, the new algorithm increases AOD by as much as 3.0 for each 0.5°grid box over the previous operational-algorithm values.

Dark Target↗
DOE OSTI2024

Feedback-based quantum algorithms for ground state preparation

The ground state properties of quantum many-body systems are a subject of interest across chemistry, materials science, and physics. Thus, algorithms for finding ground states can have broad impacts. Variational quantum algorithms are one class of ground state algorithms that has received significant attention in recent years. These algorithms utilize a hybrid quantum-classical computing framework to prepare ground states on quantum computers. However, this requires solving a classical optimization problem that can become prohibitively expensive in high dimensions. Here, we develop formulations of feedback-based quantum algorithms for ground state preparation that can be used to address this challenge for two broad classes of Hamiltonians: Fermi-Hubbard Hamiltonians, and molecular Hamiltonians represented in second quantization. Feedback-based quantum algorithms are optimization-free; in place of classical optimization, quantum circuit parameters are set according to a deterministic feedback law derived from quantum Lyapunov control principles. This feedback law guarantees a monotonic improvement in solution quality with respect to the depth of the quantum circuit. A variety of numerical illustrations are provided that analyze the convergence and robustness of feedback-based quantum algorithms for these problem classes. Published by the American Physical Society 2024

Larsen, James B. (ORCID:000000020777440X)↗
DOE OSTI2024

An Advanced Synchronized Time Digital Grid Twin Testbed for Relay Misoperation Analysis of Electrical Fault Type Detection Algorithms

Distributed energy resources and the number of relays are expected to rise in modern electrical grids; consequently, relay misoperations are also expected to grow. Relays can detect electrical fault types using an internal algorithm and can display the result using light indicators on the front of the relay. However, some relays’ internal algorithms for predicting types of electrical faults could be improved. This study assesses a relay’s external and internal algorithms with an Advanced Synchronized Time Digital Grid Twin (ASTDGT) testbed with paired relays. A misoperation relay analysis focused on measuring the accuracy of using the boundary admittance (the external algorithm) versus the set-default (the internal algorithm) relay method to determine the electrical fault types was performed. In this study, the internal and external relay algorithms were assessed with a synchronized time digital grid twin testbed using a real-time simulator. This testbed evaluated two sets of logic at the same time with the digital grid twin and paired relays in the loop. Different types of electrical faults were simulated, and the relays’ recorded events and electrical fault light indicator states were collected from the human–machine interfaces. This ASTDGT testbed with paired relays successfully evaluated the relay algorithm misoperations. The boundary admittance method had an accuracy of 100% for line-to-line, line-to-ground, and line-to-line ground faults.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1973

Search properties of some sequential decoding algorithms.

Sequential decoding procedures are studied in the context of selecting a path through a tree. Several algorithms are considered, and their properties are compared. It is shown that the stack algorithm introduced by Zigangirov (1966) and by Jelinek (1969) is essentially equivalent to the Fano algorithm with regard to the set of nodes examined and the path selected, although the description, implementation, and action of the two algorithms are quite different. A modified Fano algorithm is introduced, in which the quantizing parameter is eliminated. It can be inferred from limited simulation results that, at least in some applications, the new algorithm is computationally inferior to the old. However, it is of some theoretical interest since the conventional Fano algorithm may be considered to be a quantized version of it.

Geist, J. M.↗
NASA NTRS1980

Improved local linearization algorithm for solving the quaternion equations

The objective of this paper is to develop a new and more accurate local linearization algorithm for numerically solving sets of linear time-varying differential equations. Of special interest is the application of this algorithm to the quaternion rate equations. The results are compared, both analytically and experimentally, with previous results using local linearization methods. The new algorithm requires approximately one-third more calculations per step than the previously developed local linearization algorithm; however, this disadvantage could be reduced by using parallel implementation. For some cases the new algorithm yields significant improvement in accuracy, even with an enlarged sampling interval. The reverse is true in other cases. The errors depend on the values of angular velocity, angular acceleration, and integration step size. One important result is that for the worst case the new algorithm can guarantee eigenvalues nearer the region of stability than can the previously developed algorithm.

Yen, K.↗
NASA NTRS1986

Fast frequency acquisition via adaptive least squares algorithm

A new least squares algorithm is proposed and investigated for fast frequency and phase acquisition of sinusoids in the presence of noise. This algorithm is a special case of more general, adaptive parameter-estimation techniques. The advantages of the algorithms are their conceptual simplicity, flexibility and applicability to general situations. For example, the frequency to be acquired can be time varying, and the noise can be nonGaussian, nonstationary and colored. As the proposed algorithm can be made recursive in the number of observations, it is not necessary to have a priori knowledge of the received signal-to-noise ratio or to specify the measurement time. This would be required for batch processing techniques, such as the fast Fourier transform (FFT). The proposed algorithm improves the frequency estimate on a recursive basis as more and more observations are obtained. When the algorithm is applied in real time, it has the extra advantage that the observations need not be stored. The algorithm also yields a real time confidence measure as to the accuracy of the estimator.

Kumar, R.↗
NASA NTRS1986

Algorithms versus architectures for computational chemistry

The algorithms employed are computationally intensive and, as a result, increased performance (both algorithmic and architectural) is required to improve accuracy and to treat larger molecular systems. Several benchmark quantum chemistry codes are examined on a variety of architectures. While these codes are only a small portion of a typical quantum chemistry library, they illustrate many of the computationally intensive kernels and data manipulation requirements of some applications. Furthermore, understanding the performance of the existing algorithm on present and proposed supercomputers serves as a guide for future programs and algorithm development. The algorithms investigated are: (1) a sparse symmetric matrix vector product; (2) a four index integral transformation; and (3) the calculation of diatomic two electron Slater integrals. The vectorization strategies are examined for these algorithms for both the Cyber 205 and Cray XMP. In addition, multiprocessor implementations of the algorithms are looked at on the Cray XMP and on the MIT static data flow machine proposed by DENNIS.

Partridge, H.↗
NASA NTRS1985

An efficient algorithm for estimating noise covariances in distributed systems

An efficient computational algorithm for estimating the noise covariance matrices of large linear discrete stochatic-dynamic systems is presented. Such systems arise typically by discretizing distributed-parameter systems, and their size renders computational efficiency a major consideration. The proposed adaptive filtering algorithm is based on the ideas of Belanger, and is algebraically equivalent to his algorithm. The earlier algorithm, however, has computational complexity proportional to p to the 6th, where p is the number of observations of the system state, while the new algorithm has complexity proportional to only p-cubed. Further, the formulation of noise covariance estimation as a secondary filter, analogous to state estimation as a primary filter, suggests several generalizations of the earlier algorithm. The performance of the proposed algorithm is demonstrated for a distributed system arising in numerical weather prediction.

Dee, D. P.↗
NASA NTRS1986

Fast frequency acquisition via adaptive least squares algorithm

A new least squares algorithm is proposed and investigated for fast frequency and phase acquisition of sinusoids in the presence of noise. This algorithm is a special case of more general, adaptive parameter-estimation techniques. The advantages of the algorithms are their conceptual simplicity, flexibility and applicability to general situations. For example, the frequency to be acquired can be time varying, and the noise can be non-Gaussian, nonstationary and colored. As the proposed algorithm can be made recursive in the number of observations, it is not necessary to have a priori knowledge of the received signal-to-noise ratio or to specify the measurement time. This would be required for batch processing techniques, such as the fast Fourier transform (FFT). The proposed algorithm improves the frequency estimate on a recursive basis as more and more observations are obtained. When the algorithm is applied in real time, it has the extra advantage that the observations need not be stored. The algorithm also yields a real time confidence measure as to the accuracy of the estimator.

Kumar, Rajendra↗
NASA NTRS1987

An adaptive algorithm for motion compensated color image coding

This paper presents an adaptive algorithm for motion compensated color image coding. The algorithm can be used for video teleconferencing or broadcast signals. Activity segmentation is used to reduce the bit rate and a variable stage search is conducted to save computations. The adaptive algorithm is compared with the nonadaptive algorithm and it is shown that with approximately 60 percent savings in computing the motion vector and 33 percent additional compression, the performance of the adaptive algorithm is similar to the nonadaptive algorithm. The adaptive algorithm results also show improvement of up to 1 bit/pel over interframe DPCM coding with nonuniform quantization. The test pictures used for this study were recorded directly from broadcast video in color.

Kwatra, Subhash C.↗
NASA NTRS1988

Least-Squares Frequency-Acquisition Algorithm

Algorithm finds frequency and phase of sinudoidal signal in presence of noise. Algorithm is special case of more-general, adaptive-paramenter-estimation techniques. Computational requirements of algorithm comparable to corresponding fast-Fourier-transform (FFT) algorithm. Algorithm works directly in time domain, whereas FFT algorithm transforms data into frequency domain for estimation and detection and requires secondary algorithm to interpolate between frequencies.

Kumar, Rajendra↗
NASA NTRS1987

An algorithmic approach to crustal deformation analysis

In recent years the analysis of crustal deformation measurements has become important as a result of current improvements in geodetic methods and an increasing amount of theoretical and observational data provided by several earth sciences. A first-generation data analysis algorithm which combines a priori information with current geodetic measurements was proposed. Relevant methods which can be used in the algorithm were discussed. Prior information is the unifying feature of this algorithm. Some of the problems which may arise through the use of a priori information in the analysis were indicated and preventive measures were demonstrated. The first step in the algorithm is the optimal design of deformation networks. The second step in the algorithm identifies the descriptive model of the deformation field. The final step in the algorithm is the improved estimation of deformation parameters. Although deformation parameters are estimated in the process of model discrimination, they can further be improved by the use of a priori information about them. According to the proposed algorithm this information must first be tested against the estimates calculated using the sample data only. Null-hypothesis testing procedures were developed for this purpose. Six different estimators which employ a priori information were examined. Emphasis was put on the case when the prior information is wrong and analytical expressions for possible improvements under incompatible prior information were derived.

Iz, Huseyin Baki↗