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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Rai, Man Mohan↗
DOE OSTI2025

Simulating large one-dimensional neutral-atom quantum systems

While abstract models of quantum computation assume a closed system of two-level states, practical quantum devices inevitably couple to the environment in some way, creating sources of noise. Understanding the tolerance to noise of specific quantum algorithms run on specific devices is important for determining the feasibility of quantum computing in the current noisy intermediate-scale quantum era. Of particular interest is understanding the noise sensitivity of these devices as more qubits are added to the system. Classical simulations are a useful tool to understand the effects of this noise, but direct classical simulations of open quantum systems are burdened by an exponentially growing cost in the number of qubits and a large local Hilbert space dimension. For onedimensional, shallow circuits, using tensor networks can replace this exponential cost with a linear one and simulate far wider systems than what would normally be available. In this paper, we describe a tensor network simulation of a neutral atom quantum system under the presence of noise, while introducing a purity-preserving truncation technique that compromises between the simplicity of the matrix product state and the positivity of the matrix product density operator. We apply this simulation to a near-optimized iteration of the quantum approximate optimization algorithm on a transverse field Ising model in order to investigate the influence of large system sizes on the performance of the algorithm. We find that while circuits with a large number of qubits fail more often under noise that depletes the qubit population, their outputs on a successful measurement are just as robust under Rydberg atom dissipation or qubit dephasing as smaller systems. However, such circuits might not perform as well under coherent multiqubit errors such as Rydberg atom crosstalk. We also find that the optimized parameters are especially robust to noise, suggesting that a noisier quantum system can be used to find the optimal parameters before switching to a cleaner system for measurements of observables.

Allen, James↗
DOE OSTI2022

Quantitative analysis of Cu XANES spectra using linear combination fitting of binary mixtures simulated by FEFF9

We report x-ray absorption near edge structure (XANES) is a powerful tool to probe the fingerprint of local structures, and when coupled with X-ray microscopy, the small spot size enables one to probe very specific regions of interest in a device or material, e.g. interfaces/bulk, different grains, good/bad electrical areas. In this work, we investigate the use of linear combination fitting (LCF) of XANES spectra for the particular case of Cu doping in CdTe. We show that the experimental data seem to be accurately represented by standards of Cu 2 Te and its substoichiometric counterpart, Cu 1.43 Te. We use Cu in CdTe as a case study to evaluate the accuracy of linear combination fitting using simulated standards, given that experimental standards for certain phases (e.g. Cu 1.43 Te) or defect structures (e.g. vacancies) cannot be readily obtained. We discuss how spectral features of the FEFF9-simulated standards, fitting ranges, and noise levels all dictate the accuracy of this type of analysis. We show that the greater the spectral difference between the two standards, the better the LCF is able to differentiate between the two structures and to tolerate experimental noise. Finally, we estimate the error of the fitted weights for different spectral features and noise levels and propose a framework to study local structures semi-quantitatively by using binary mixtures of FEFF9-simulated standards.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1982

A technology program for the development of the large deployable reflector for space based astronomy

Technologies for the development of the Large Deployable Reflector (LDR), a NASA project for the 1990's, for infrared and submillimeter astronomy are presented. The proposed LDR is a 10-30 diameter spaceborne observatory operating in the spectral region from 30 microns to one millimeter, where ground observations are nearly impossible. Scientific rationales for such a system include the study of ancient signals from galaxies at the edge of the universe, the study of star formation, and the observation of fluctuations in the cosmic background radiation. System requirements include the ability to observe faint objects at large distances and to map molecular clouds and H II regions. From these requirements, mass, photon noise, and tolerance budgets are developed. A strawman concept is established, and some alternate concepts are considered, but research is still necessary in the areas of segment, optical control, and instrument technologies.

Kiya, M. K.↗
NASA NTRS1988

Speech coding at 4800 bps for mobile satellite communications

A speech compression project has recently been completed to develop a speech coding algorithm suitable for operation in a mobile satellite environment aimed at providing telephone quality natural speech at 4.8 kbps. The work has resulted in two alternative techniques which achieve reasonably good communications quality at 4.8 kbps while tolerating vehicle noise and rather severe channel impairments. The algorithms are embodied in a compact self-contained prototype consisting of two AT and T 32-bit floating-point DSP32 digital signal processors (DSP). A Motorola 68HC11 microcomputer chip serves as the board controller and interface handler. On a wirewrapped card, the prototype's circuit footprint amounts to only 200 sq cm, and consumes about 9 watts of power.

Gersho, Allen↗
NASA NTRS1987

A prototype 4800 bps voice terminal for the mobile satellite experiment

The authors report the final stage of a research project for the NASA mobile satellite experiment (MSAT-X). The work has resulted in two alternative coding techniques which have achieved good communications quality at 4.8 kb/s while tolerating vehicle noise, fading, and a fairly high-error-rate, bursty channel. The authors have constructed a circuit board based on three AT&T 32-bit floating-point DSP32 digital signal processors (DSP) and providing both excess processing power and considerable flexibility for handling different variations of the algorithms. A Motorola 68HC11 microcomputer chip serves as the board controller and interface handler. Mounted on a wirewrapped card, the prototype's circuit footprint amounts to only 225 cm2 and consumes about 13 W of power. A description is given of the architecture, signal processing and communication functions, circuitry, and firmware of the prototype. Issues such as synchronization, framing, error control, and modem interface are also addressed.

Chan, Wai-Yip↗
NASA NTRS2017

Determining the Optimal Spectral Sampling Frequency and Uncertainty Thresholds for Hyperspectral Remote Sensing of Ocean Color

Using a modified geostatistical technique, empirical variograms were constructed from the first derivative of several diverse remote sensing reflectance and phytoplankton absorbance spectra to describe how data points are correlated with distance across the spectra. The maximum rate of information gain is measured as a function of the kurtosis associated with the Gaussian structure of the output, and is determined for discrete segments of spectra obtained from a variety of water types (turbid river filaments, coastal waters, shelf waters, a dense Microcystis bloom, and oligotrophic waters), as well as individual and mixed phytoplankton functional types (PFTs; diatoms, chlorophytes, cyanobacteria, coccolithophores). Results show that a continuous spectrum of 5 to 7 nm spectral resolution is optimal to resolve the variability across mixed reflectance and absorbance spectra. In addition, the impact of uncertainty on subsequent derivative analysis is assessed, showing that a limit of 3 Gaussian noise (SNR 66) is tolerated without smoothing the spectrum, and 13 (SNR 15) noise is tolerated with smoothing.

Noise in imaging systems↗
NASA NTRS1992

Appendix: Limits on the use of heterodyning and amplification in optical interferometry

The development of optical fibers, lasers, and mixers at optical frequencies has offered the hope that active methods can contribute to optical interferometry. Heterodyning, in particular, looks attractive, even though bandwidths are narrower than one would like at present; one might expect this limitation to lessen as technology develops. That expectation, unfortunately, is not likely to benefit interferometry at optical wavelengths because of the intervention of quantum mechanics and the second law of thermodynamics, as Burke (1985a) pointed out. So much 'second quantization' noise is generated that only at infrared frequencies, somewhere in the 10-100 micron range, can one look forward to heterodyning in any realistic sense. The reason is easily understood. Every amplifier, in the quantum limit, works by stimulated emission, even though this basic truth is not obvious at radio frequencies. This means that there must be spontaneous emission occurring within every amplifier, and Strandberg (1957) showed that this implied a limiting noise temperature, T sub N = h nu/k, for any amplifier. Burke (1969) used this result to demonstrate that, if it were not for this quantum noise, the VLBI method would allow one to tell which slit a photon went through before forming an interference pattern, thus violating basic tenants of quantum mechanics. In essence, the second quantization condition Delta N Delta phi greater than or = 1 saves one from paradox. One can state the conclusion simply: any amplifier produces approximately one photon per Hertz of bandwidth. In optical interferometry, one will certainly want bandwidth in the 10(exp 12) to 10(exp 14) Hz range, and that implies an intolerable cacophony of noise photons. Only at infrared frequencies can one tolerate the quantum noise, where the natural noise background may be high and the mixers are not as efficient as one would hope for. The crossover at present is about 10 or 20 microns, but the boundary will shift to longer wavelengths as noise performance improves. One might guess that ultimately a wavelength of about 100 microns will mark the limit of useful amplification and heterodyning in astronomical aperture synthesis interferometry.

Burke, Bernard F.↗
DOE OSTI2024

Stochastic Error Cancellation in Analog Quantum Simulation

Analog quantum simulation is a promising path towards solving classically intractable problems in many-body physics on near-term quantum devices. However, the presence of noise limits the size of the system and the length of time that can be simulated. In our work, we consider an error model in which the actual Hamiltonian of the simulator differs from the target Hamiltonian we want to simulate by small local perturbations, which are assumed to be random and unbiased. We analyze the error accumulated in observables in this setting and show that, due to stochastic error cancellation, with high probability the error scales as the square root of the number of qubits instead of linearly. We explore the concentration phenomenon of this error as well as its implications for local observables in the thermodynamic limit. Moreover, we show that stochastic error cancellation also manifests in the fidelity between the target state at the end of time-evolution and the actual state we obtain in the presence of noise. This indicates that, to reach a certain fidelity, more noise can be tolerated than implied by the worst-case bound if the noise comes from many statistically independent sources.

Analog quantum simulation↗
NASA NTRS2006

The X-43 Fin Actuation System Problem - Reliability in Shades of Gray

Following the loss of the first X-43 during launch, the mishap investigation board indicated the Fin Actuator System (FAS) needed to have a larger torque margin. To supply this added torque, a second actuator was added. The consequences of what seemed to be a simple modification would trouble the X-43 program. Because of the second actuator, a new computer board was required. This proved to be subject to electronic noise. This resulted in the actuator latch up in ground tests of the FAS for the second launch. Such a latch up would cause the Pegasus booster to fail, as the FAS was a single string system. The problem was corrected and the second flight was successful. The same modifications were added to the FAS for flight three. When the FAS underwent ground tests, it also latched up. The failure indicated that each computer board had a different tolerance to electronic noise. The problem with the FAS was corrected. Subsequently, another failure occurred, raising questions about the design, and the probability of failure for the X-43 Mach 10 flight. This was not simply a technical issue, but illuminated the difficulties facing both managers and engineers in assessing risk, design requirements, and probabilities in cutting edge aerospace projects.

Peebles, Curtis↗
NASA NTRS1992

Real-valued composite filters for correlation-based optical pattern recognition

Advances in the technology of optical devices such as spatial light modulators (SLMs) have influenced the research and growth of optical pattern recognition. In the research leading to this report, the design of real-valued composite filters that can be implemented using currently available SLMs for optical pattern recognition and classification was investigated. The design of real-valued minimum average correlation energy (RMACE) filter was investigated. Proper selection of the phase of the output response was shown to reduce the correlation energy. The performance of the filter was evaluated using computer simulations and compared with the complex filters. It was found that the performance degraded only slightly. Continuing the above investigation, the design of a real filter that minimizes the output correlation energy and the output variance due to noise was developed. Simulation studies showed that this filter had better tolerance to distortion and noise compared to that of the RMACE filter. Finally, the space domain design of RMACE filter was developed and implemented on the computer. It was found that the sharpness of the correlation peak was slightly reduced but the filter design was more computationally efficient than the complex filter.

Rajan, P. K.↗
DOE OSTI2025

A quantum eigenvalue solver based on tensor networks

Electronic ground states are of central importance in chemical simulations, but have remained beyond the reach of efficient classical algorithms except in cases of weak electron correlation or one-dimensional spatial geometry. We introduce a hybrid quantum-classical eigenvalue solver that constructs a wavefunction ansatz from a linear combination of matrix product states in rotated orbital bases, enabling the characterization of strongly correlated ground states with arbitrary spatial geometry. The energy is converged via a gradient-free generalized sweep algorithm based on quantum subspace diagonalization, with a potentially exponential speedup in the off-diagonal matrix element contractions upon translation into compact quantum circuits of linear depth in the number of qubits. Chemical accuracy is attained in numerical experiments for both a stretched water molecule and an octahedral arrangement of hydrogen atoms, achieving substantially better correlation energies compared to a unitary coupled-cluster benchmark, with orders of magnitude reductions in quantum resource estimates and a surprisingly high tolerance to shot noise. This proof-of-concept study suggests a promising new avenue for scaling up simulations of strongly correlated chemical systems on near-term quantum hardware.

chemistry↗
DOE OSTI2026

Dynamic Focusing to Suppress Emittance Transfer in Crab-Crossing Flat Beam Collisions

Flat hadron beam collisions, though expected to enhance peak luminosity by about an order of magnitude, have not yet been demonstrated. We identify a new mechanism in which the hourglass-induced synchrobetatron resonance, when coupled to unavoidable machine fluctuations, drives emittance transfer and degrades the flat-beam condition. This effect becomes a critical limitation for maintaining flat hadron beams on operational timescales. Using Electron-Ion Collider (EIC) parameters, we show that it imposes stringent tolerances on machine noise. We further demonstrate that a dynamic focusing scheme, implemented by combining sextupoles with crab cavities, suppresses the resonance and relaxes these constraints, providing a practical path toward robust flat-beam collisions in future lepton-hadron colliders.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗