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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 721 records · Page 40
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quantum error mitigation by layerwise Richardson extrapolation

A widely used method for mitigating errors in noisy quantum computers is Richardson extrapolation, a technique in which the overall effect of noise on the estimation of quantum expectation values is captured by a single parameter that, after being scaled to larger values, is eventually extrapolated to the zero-noise limit. We generalize this approach by introducing layerwise Richardson extrapolation (LRE), an error mitigation protocol in which the noise of different individual layers (or larger chunks of the circuit) is amplified and the associated expectation values are linearly combined to estimate the zero-noise limit. The coefficients of the linear combination are analytically obtained from the theory of multivariate Lagrange interpolation. LRE leverages the flexible configurational space of layerwise unitary folding, allowing for a more nuanced mitigation of errors by treating the noise level of each layer of the quantum circuit as an independent variable. Furthermore, we provide numerical simulations demonstrating scenarios where LRE achieves superior performance compared to traditional (single-variable) Richardson extrapolation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Diabatic error and propagation of Majorana zero modes in interacting quantum dots systems

Motivated by recent experimental progress in realizing Majorana zero modes (MZMs) using quantum dot systems, we investigate the diabatic errors associated with the movement of those MZMs. The movement is achieved by tuning time-dependent gate potentials applied to individual quantum dots, effectively creating a moving potential wall. To probe the optimized movement of MZMs, we calculate the experimentally accessible time-dependent fidelity and local density-of-states using many-body time-dependent numerical methods. Furthermore, our analysis reveals that an optimal potential wall height is crucial to preserve the well-localized nature of the MZM during its movement. Moreover, we analyze diabatic errors in realistic quantum-dot systems, incorporating the effects of repulsive Coulomb interactions and disorder in both hopping and pairing terms. Additionally, we provide a comparative study of diabatic errors arising from the simultaneous versus sequential tuning of multiple gates during the MZMs movement. Finally, we estimate the timescale required for MZM transfer in a six-quantum-dot system, demonstrating that MZM movement is feasible and can be completed well within the qubit's operational lifetime in practical quantum-dot setups.

Density of states↗
DOE OSTI2024

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↗
DOE OSTI2024

Implementation and (Inverse Modified) Error Analysis for Implicitly Templated ODE-Nets

We focus on learning unknown dynamics from data using ODE-nets templated on implicit numerical initial value problem solvers. First, we perform inverse modified error analysis of the ODE-nets using unrolled implicit schemes for ease of interpretation. It is shown that training an ODE-net using an unrolled implicit scheme returns a close approximation of an inverse modified differential equation (IMDE). In addition, we establish a theoretical basis for hyperparameter selection when training such ODE-nets, whereas current strategies usually treat numerical integration of ODE-nets as a black box. We thus formulate an adaptive algorithm which monitors the level of error and adapts the number of (unrolled) implicit solution iterations during the training process, so that the error of the unrolled approximation is less than the current learning loss. This helps accelerate training while maintaining accuracy. Several numerical experiments are performed to demonstrate the advantages of the proposed algorithm compared to nonadaptive unrollings and validate the theoretical analysis. Here, we also note that this approach naturally allows for incorporating partially known physical terms in the equations, giving rise to what is termed “gray box” identification.

ODE-nets↗
DOE OSTI2026

QProR: An Efficient Framework for Quantity-of-Interest Based Progressive Retrieval with Guaranteed Error Control

Scientific applications generate an unprecedented volume of data, overwhelming the network and file systems’ bandwidth and posing challenges for efficient and scalable data retrieval and analysis. Progressive data compression offers a promising solution by enabling on-demand retrieval at reduced size. However, existing progressive methods either fail to bound the errors in essential quantities of interest (QoIs) derived from raw data or suffer from suboptimal retrieval efficiency. In this work, we propose QProR, an efficient QoI-based progressive framework that optimizes progressive retrieval for target QoIs. Our key contributions include: (1) a systematic framework that integrates error-controlled lossy compressors with bitplane encoding while decoupling the two processes for high flexibility and adaptability; (2) a novel weighted bitplane encoding method which incorperates QoI knowledge into data refactoring to enhance retrieval efficiency; (3) an optimized retrieval strategy that accounts for the varying impacts of different variables on multivariate QoIs; (4) comprehensive evaluations using six real-world datasets from multiple scientific applications and thorough comparisons against state of the arts. Experimental results demonstrate that QProR achieves up to 80.38% reduction in the retrieval size under the same requested QoI error tolerance, when compared with the best-performing existing methods. When transferring 384 GB of scientific data to remote sites, QProR delivers up to 1.68 × speedup in the end-to-end data transfer performance.

Li, Wenbo [University of Kentucky]↗
DOE OSTI2024

Combining compositional data sets introduces error in covariance network reconstruction

Microbial communities are diverse biological systems that include taxa from across multiple kingdoms of life. Notably, interactions between bacteria and fungi play a significant role in determining community structure. However, these statistical associations across kingdoms are more difficult to infer than intra-kingdom associations due to the nature of the data involved using standard network inference techniques. We quantify the challenges of cross-kingdom network inference from both theoretical and practical points of view using synthetic and real-world microbiome data. We detail the theoretical issue presented by combining compositional data sets drawn from the same environment, e.g. 16S and ITS sequencing of a single set of samples, and we survey common network inference techniques for their ability to handle this error. We then test these techniques for the accuracy and usefulness of their intra- and interkingdom associations by inferring networks from a set of simulated samples for which a ground-truth set of associations is known. We show that while the two methods mitigate the error of cross-kingdom inference, there is little difference between techniques for key practical applications including identification of strong correlations and identification of possible keystone taxa (i.e. hub nodes in the network). Furthermore, we identify a signature of the error caused by transkingdom network inference and demonstrate that it appears in networks constructed using real-world environmental microbiome data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Improving the efficiency of learning-based error mitigation

Error mitigation will play an important role in practical applications of near-term noisy quantum computers. Current error mitigation methods typically concentrate on correction quality at the expense of frugality (as measured by the number of additional calls to quantum hardware). To fill the need for highly accurate, yet inexpensive techniques, we introduce an error mitigation scheme that builds on Clifford data regression (CDR). The scheme improves the frugality by carefully choosing the training data and exploiting the symmetries of the problem. We test our approach by correcting long range correlators of the ground state of XY Hamiltonian on IBM Toronto quantum computer. We find that our method is an order of magnitude cheaper while maintaining the same accuracy as the original CDR approach. The efficiency gain enables us to obtain a factor of 10 improvement on the unmitigated results with the total budget as small as 2 ⋅ 10 5 shots. Furthermore, we demonstrate orders of magnitude improvements in frugality for mitigation of energy of the LiH ground state simulated with IBM's Ourense-derived noise model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

CV4Quantum: Reducing the Sampling Overhead in Probabilistic Error Cancellation Using Control Variates

Quasiprobabilistic decompositions (QPDs) play a key role in maximizing the utility of near-term quantum hardware. For example, Probabilistic Error Cancellation (PEC) (an error mitigation technique) and circuit cutting (which enables large quantum computations to be performed on quantum hardware with a limited number of qubits) both involve QPDs. Computations based on QPDs typically incur large sampling overheads that grow exponentially with the number of error-terms mitigated or number of circuit-cuts employed, limiting their practical feasibility. In this work, we adapt the control variates variance reduction technique from the statistics literature in order to reduce the sampling overhead in QPD-based computations. We demonstrate our method using simulation experiments that mimic a realistic PEC scenario. In our experiments, we observed a more than 50% reduction in the number of samples needed to achieve a given precision, in more than 50% of the PEC-based estimations performed in the study when using our approach. We discuss how future research on constructing good control variates can lead to even stronger sampling overhead reduction.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1971

A method of treating the non-grey error in total emittance measurements

In techniques for the rapid determination of total emittance, the sample is generally exposed to surroundings that are at a different temperature than the sample's surface. When the infrared spectral reflectance of the surface is spectrally selective, these techniques introduce an error into the total emittance values. Surfaces of aluminum overcoated with oxides of various thicknesses fall into this class. Because they are often used as temperature control coatings on satellites, their emittances must be accurately known. The magnitude of the error was calculated for Alzak and silicon oxide-coated aluminum and was shown to be dependent on the thickness of the oxide coating. The results demonstrate that, because the magnitude of the error is thickness-dependent, it is generally impossible or impractical to eliminate it by calibrating the measuring device.

Heaney, J. B.↗
NASA NTRS1972

End-to-end RMS error testing on a constant bandwidth FM/FM system

End-to-end root-mean-square (rms) tests performed on a constant bandwidth FM/FM system with various settings of system parameters are reported. The testing technique employed is that of sampling, digitizing, delaying, and comparing the analog input against the sampled and digitized corresponding output. Total system error is determined by fully loading all channels with band-limited noise and conducting end-to-end rms error tests on one channel. Tests are also conducted with and without a transmission link and plots of rms errors versus receiver signal-to-noise (S/N) values are obtained. The combined effects of intermodulation, adjacent channel crosstalk, and residual system noise are determined as well as the single channel distortion of the system.

Wallace, G. R.↗
NASA NTRS1970

Multipath errors in range rate measurement by a TDRS/VHF - GRARR

Range rate errors due to multipath reflection are calculated for a tracking and data relay satellite system using the VHF Goddard range and range rate (GRARR) system. At VHF the reflection is primarily specular, and the strength of the multipath relative to the direct path can be modeled in terms of the geometry and the surface characteristics, specifically the root-mean-square (rms) ocean wave height. The uplink and downlink multipath introduces phase jitter on the GRARR carrier and subcarrier. The derivation of these effects is reviewed leading to an expression for the rms range rate error. The derivation assumed the worst-case orbital configurations in which there was very little relative specular Doppler. This means that the specular multipath interference was not attenuated by the carrier and subcarrier PLL transfer functions. Curves of range rate error are presented as a function of grazing angle with wave height 0.3 to 0.7 meters and spacecraft altitude 100 to 700 miles as parameters.

Sohn, S. J.↗
NASA NTRS1972

Mars gravitational field estimation error

The error covariance matrices associated with a weighted least-squares differential correction process have been analyzed for accuracy in determining the gravitational coefficients through degree and order five in the Mars gravitational potential junction. The results are presented in terms of standard deviations for the assumed estimated parameters. The covariance matrices were calculated by assuming Doppler tracking data from a Mars orbiter, a priori statistics for the estimated parameters, and model error uncertainties for tracking-station locations, the Mars ephemeris, the astronomical unit, the Mars gravitational constant (G sub M), and the gravitational coefficients of degrees six and seven. Model errors were treated by using the concept of consider parameters.

Compton, H. R.↗
NASA NTRS1971

L-/S-band calibration error analysis.

Results of a statistical error analysis performed to determine the degree of uncertainty encountered when calibrating steerable receiving antennas with the solar calibration method. The analysis considers the propagation of precision error indices. It is shown that a worst-case one-sigma (1 sigma) uncertainty of plus or minus 0.8 dB in system noise temperature occurs for a solar calibration at L-band. Somewhat better precision can be achieved by monitoring the antenna gain-to-noise temperature ratio at a station; a worst-case uncertainty of plus or minus 0.5 dB (1 sigma) can be realized. An error analysis is made of a method to determine absolute antenna gain based upon solar flux density. The uncertainty in this type of measurement is plus or minus 0.7 dB (1 sigma) at L- and S-band frequencies.

Taylor, R. E.↗
NASA NTRS1971

136 MHz interferometer error due to galactic nucleus.

Extraneous interfering signals are discussed which limit the basic accuracy of the 136 MHz Minitrack radio-interferometer system providing electrical phase data from which direction cosines for determining spacecraft orbits are generated. In particular, the fundamental error due to interference caused by the passage of the galactic nucleus is investigated. An expression is developed for the lower bound of the phase error when the noise source is not uniformly distributed across the Minitrack's zenith-pointed fan beam. In addition, the threshold of the Minitrack input power levels is determined below which the electrical phase is no longer determined unambiguously. The effect of the passage of the galactic nucleus coincident with the presence of a spacecraft is analyzed, and the corresponding phase error established.

Kyriakopoulos, N.↗
NASA NTRS1972

Reconstruction errors in digital-to-analog conversion.

Error could theoretically be found as a function of time, midway between any two arbitrarily placed sample points. However, the analysis and the result would be difficult to use. As an alternative, worst-case instantaneous errors can be evaluated near the base-line crossing and at the peak of the analog signal. Location of sample points affects the error values obtained, but use of the points provides a means of comparing different reconstruction techniques. Zero-order conversion is discussed together with first-order conversion, second-order conversion, and third-order conversion.

Dotson, W. P., Jr.↗
NASA NTRS1971

Optimum impulsive midcourse guidance with control dependent errors.

The problem of determining the optimum guidance policy for an interplanetary spacecraft is treated as a stochastic optimal control problem. An algorithm for computing the optimum velocity correction and the optimum execution time (with allowance for correction-dependent errors) is derived in the case of a single midcourse correction. The performance index was chosen to be an upper bound for the probability that the mission fails, and it is defined as a function of the maximum allowable velocity correction and the maximum allowable deviation of the terminal state. Numerical results obtained for a Jupiter fly-by mission indicate that the execution errors have a significant influence on the performance index, but an acceptably small upper bound on the probability of mission failure can be obtained for sufficiently small execution errors.

Tapley, B. D.↗
NASA NTRS1972

Polarization mismatch errors in radio phase interferometers.

An analysis is presented which deals with the effects of polarization mismatch errors on the accuracy of a phase interferometer used for position location of unknown emitters relative to known calibration emitters. Closed-form expressions for the induced phase difference between interferometer antennas are derived for several combinations of receiving and transmitting antenna polarizations. Errors contributed by mechanical misalignment between antennas, as well as effects of power loss attributable to polarization mismatch, are also considered. The analysis leads to the conclusion that circularly polarized interferometer and transmitter antennas are best suited for the position location application, if it is assumed that polarization tracking of the interferometer antennas is not available. It is shown that a reasonable amount of ellipticity can be tolerated before the phase error becomes significant.

Muehldorf, E. I.↗