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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
DOE OSTI2024

Distributionally Robust Variational Quantum Algorithms With Shifted Noise

Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant challenge. A practical issue is the high sensitivity of quantum noise to environmental changes, and its propensity to shift in real time. This presents a critical problem as an optimized VQA ansatz may not perform effectively under a different noise environment. For the first time, we explore how to optimize VQA parameters to be robust against unknown shifted noise. We model the noise level as a random variable with an unknown probability density function (PDF), and we assume that the PDF may shift within an uncertainty set. This assumption guides us to formulate a distributionally robust optimization problem, with the goal of finding parameters that maintain effectiveness under shifted noise. We utilize a distributionally robust Bayesian optimization solver for our proposed formulation. This provides numerical evidence in both the Quantum Approximate Optimization Algorithm (QAOA) and the Variational Quantum Eigensolver (VQE) with hardware-efficient ansatz, indicating that we can identify parameters that perform more robustly under shifted noise. We regard this work as the first step towards improving the reliability of VQAs influenced by real-time noise.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1989

Error control techniques for satellite and space communications

The performance of bandwidth efficient trellis codes on channels with phase jitter, or those disturbed by jamming and impulse noise is analyzed. An heuristic algorithm for construction of bandwidth efficient trellis codes with any constraint length up to about 30, any signal constellation, and any code rate was developed. Construction of good distance profile trellis codes for sequential decoding and comparison of random coding bounds of trellis coded modulation schemes are also discussed.

Costello, Daniel J., Jr.↗
NASA NTRS1990

Random-Field Estimation For Dynamics Of Robots

Report discusses use of random-field mathematical models as alternatives to deterministic models of classical mechanics to describe dynamics of robot arms. These alternative models used to establish relationship between methods of estimation theory and robot dynamics. Approach yields new class of algorithms performing computations typical of estimation theory to solve such fundamental problems in robotics as forward and inverse dynamics and inverse kinematics.

Rodriguez, Guillermo↗
NASA NTRS1990

Infrared fiber coupled acousto-optic tunable filter spectrometer

A spectrometer design is introduced which combines an acoustooptic tunable filter (AOTF) and IR-transmitting flouride-glass fibers. The AOTF crystal is fabricated from TeO2 and permits random access to any wavelength in less than 50 microseconds, and the resulting spectrometer is tested for the remote analysis of gases and hydrocarbons. The AOTF spectrometer, when operated with a high-speed frequency synthesizer and optimized algorithms, permits accurate high-speed spectroscopy in the mid-IR spectral region.

Levin, K. H.↗
NASA NTRS2006

Effects of the Antenna Aperture on Remote Sensing of Sea Surface Salinity at L-Band

Remote sensing of sea surface salinity with sufficient accuracy to meet the needs of global oceanography is a challenging task. The global variability of the salinity signal in the open ocean is only a few Kelvin even at L-band and an accuracy on the order of 0.1K is desired to study the influence of salinity on ocean circulation and energy exchange with the atmosphere. On the other hand, resolution is not an issue for understanding the dynamics of the open ocean where scales of hundreds of km are not uncommon. This permits remote sensing with large antenna footprints and spatial averaging to reduce noise. However, antennas with large footprints introduce other problems. For example, the angle of incidence and hence the brightness temperature varies over the footprint. Similarly, the polarization of brightness temperature relative to the antenna ports changes. Studies have been conducted using antenna patterns representative of the antenna that will be flown on the Aquarius mission to examine these effects. Aquarius is a pushbroom style radiometer with three beams looking across track away from the sun. The beams are at incidences angles (at the spacecraft) of about 26.5, 34 and 40 degrees each with a half-power beam width of about 5.8 degrees. It is shown that the measured brightness temperature is biased relative to the value at boresight because of changes across the field of view. The bias can be as much as 4K and positive or negative depending on polarization. Polarization mixing because of the variations of the local plane of incidence across the footprint also occur and can result in biased polarimetric measurements. A bias in the third Stokes parameter of as much as 0.4K is possible. Such effects may affect algorithms that use the third Stokes parameter to correct for Faraday rotation. Another issue associated with the antenna is sun glint. This is an issue determined by surface roughness and antenna sidelobes. Examples will be given for the random component (glint) for the case of the Aquarius antenna beams. Fortunately, the Aquarius beams mostly look to the dark side of the day-night termination, but during some portions of the year they will see sun-lighted ocean. In this case, glint could be an issue for the inner-most beam.

Dinnat, Emmanuel P.↗
NASA NTRS2015

Online Tools for Uncovering Data Quality (DQ) Issues in Satellite-Based Global Precipitation Products

Data quality (DQ) has many attributes or facets (i.e., errors, biases, systematic differences, uncertainties, benchmark, false trends, false alarm ratio, etc.)Sources can be complicated (measurements, environmental conditions, surface types, algorithms, etc.) and difficult to be identified especially for multi-sensor and multi-satellite products with bias correction (TMPA, IMERG, etc.) How to obtain DQ info fast and easily, especially quantified info in ROI Existing parameters (random error), literature, DIY, etc.How to apply the knowledge in research and applications.Here, we focus on online systems for integration of products and parameters, visualization and analysis as well as investigation and extraction of DQ information.

precipitation↗
DOE OSTI2025

Robust Multi-fidelity Bayesian Optimization with Deep Kernel and Partition

Multi-fidelity Bayesian optimization (MFBO) is a powerful approach that utilizes lowfidelity, cost-effective sources to expedite the exploration and exploitation of a high-fidelity objective function. Existing MFBO methods with theoretical foundations either lack justification for performance improvements over single-fidelity optimization or rely on strong assumptions about the relationships between fidelity sources to construct surrogate models and direct queries to low-fidelity sources. To mitigate the dependency on cross-fidelity assumptions while maintaining the advantages of low-fidelity queries, we introduce a random sampling and partition-based MFBO framework with deep kernel learning. This framework is robust to cross-fidelity model misspecification and explicitly illustrates the benefits of low-fidelity queries. Our results demonstrate that the proposed algorithm effectively manages complex cross-fidelity relationships and efficiently optimizes the target fidelity function.

Zhang, Fengxue [University of Chicago, Illinois, U↗
DOE OSTI2025

End–to–End Metasurface Design for Temperature Imaging via Broadband Planck‐Radiation Regression

A theoretical framework is presented for temperature imaging from long-wavelength infrared (LWIR) thermal radiation (e.g., 8–12 µm) through the end-to-end design of a metasurface-optics frontend and a computational-reconstruction backend. A new nonlinear reconstruction algorithm, “Planck regression”, is introduced to reconstruct the temperature map from a gray scale sensor image, even in the presence of severe chromatic aberration, by exploiting black body and optical physics particular to thermal imaging. This algorithm is combined with an end-to-end approach that optimizes manufacturable, single-layer metasurfaces to yield the most accurate reconstruction. The designs demonstrate high-quality, noise-robust reconstructions of arbitrary temperature maps (including completely random images) in simulations of an ultra-compact thermal-imaging device. Here, it is also shown that Planck regression is much more generalizable to arbitrary images than a straightforward neural-network reconstruction, which requires a large training set of domain-specific images.

36 MATERIALS SCIENCE↗
NASA NTRS1974

Efficient generation of statistically good pseudonoise by linearly interconnected shift registers

A number of efficient new algorithms for generating digital pseudonoise are presented. The algorithms are efficient because a large number of new pseudorandom bits are generated at each iteration of a computer implementation or at each clock pulse of a hardware implementation. The maximal-length shift register sequences obtained have good randomness properties. Some of the properties of p-n sequences are reviewed and the results of an extensive statistical evaluation of the pseudonoise are presented.

Hurd, W. J.↗
NASA NTRS1994

System identification of the Large-Angle Magnetic Suspension Test Fixture (LAMSTF)

The Large-Angle Magnetic Suspension Test Fixture (LAMSTF), a laboratory-scale research project to demonstrate the magnetic suspension of objects over wide ranges of attitudes, has been developed. This system represents a scaled model of a planned Large-Gap Magnetic Suspension System (LGMSS). The LAMSTF consists of a small cylindrical permanent magnet suspended element which is levitated above a planar array of five electromagnets mounted in a circular configuration. The cylinder is a rigid body and can be controlled to move in five independent degrees of freedom. Six position variables are sensed indirectly by using infrared light-emitting diodes and light-receiving phototransistors. The motion of the suspended cylinder is in general nonlinear and hence only the linear, time-invariant perturbed motion about an equilibrium state is considered. One of the main challenges in this project is the control of the suspended element over a wide range of orientations. An accurate dynamic model plays an essential role in controller design. The analytical model is first derived and open-loop characteristics discussed. The system is shown to be highly unstable and requires feedback control for system identification. Projection filters are first proposed to identify the state space model from closed-loop input/output test data in the time domain. This method is then extended to identify linear systems from the frequency test data. A canonical transformation matrix is also derived to transform the identified state space model into the physical coordinate. The LAMSTF system is stabilized by using a linear quadratic regulator (LQR) feedback controller for closed-loop identification. The rate information is obtained by calculating the back difference of the sensed position signals. Only the closed-loop random input/output data are recorded. Preliminary results from numerical simulations demonstrate that the identified system model is fairly accurate from either time domain or frequency-domain data. Experiments will be performed to validate the proposed closed-loop identification algorithms.

Huang, Jen-Kuang↗
NASA NTRS2017

Automation of POST Cases via External Optimizer and "Artificial p2" Calculation

During conceptual design speed and accuracy are often at odds. Specifically in the realm of launch vehicles, optimizing the ascent trajectory requires a larger pool of analytical power and expertise. Experienced analysts working on familiar vehicles can produce optimal trajectories in a short time frame, however whenever either "experienced" or "familiar " is not applicable the optimization process can become quite lengthy. In order to construct a vehicle agnostic method an established global optimization algorithm is needed. In this work the authors develop an "artificial" error term to map arbitrary control vectors to non-zero error by which a global method can operate. Two global methods are compared alongside Design of Experiments and random sampling and are shown to produce comparable results to analysis done by a human expert.

Dees, Patrick D.↗
DOE OSTI2024

Chaotic roots of the modular multiplication dynamical system in Shor's algorithm

Shor's factoring algorithm, believed to provide an exponential speedup over classical computation, relies on finding the period of an exactly periodic quantum modular multiplication operator. This exact periodicity is the hallmark of an integrable system, which is paradoxical from the viewpoint of quantum chaos, given that the classical limit of the modular multiplication operator is a highly chaotic system that occupies the “maximally random” Bernoulli level of the classical ergodic hierarchy. In this work, we approach this apparent paradox from a quantum dynamical systems viewpoint, and consider whether signatures of ergodicity and chaos may indeed be encoded in such an “integrable” quantization of a chaotic system. We show that Shor's modular multiplication operator, in specific cases, can be written as a superposition of quantized 𝐴-baker's maps exhibiting more typical signatures of quantum chaos and ergodicity. This work suggests that the integrability of Shor's modular multiplication operator may stem from the interference of other “chaotic” quantizations of the same family of maps, and paves the way for deeper studies on the interplay of integrability, ergodicity, and chaos in and via quantum algorithms.

Dynamical systems↗
DOE OSTI2024

Constant-Depth Preparation of Matrix Product States with Adaptive Quantum Circuits

Adaptive quantum circuits, which combine local unitary gates, midcircuit measurements, and feedforward operations, have recently emerged as a promising avenue for efficient state preparation, particularly on near-term quantum devices limited to shallow-depth circuits. Matrix product states (MPS) comprise a significant class of many-body entangled states, efficiently describing the ground states of one-dimensional gapped local Hamiltonians and finding applications in a number of recent quantum algorithms. Recently, it has been shown that the Affleck-Kennedy-Lieb-Tasaki state—a paradigmatic example of an MPS—can be exactly prepared with an adaptive quantum circuit of constant depth, an impossible feat with local unitary gates alone due to its nonzero correlation length [Smith , PRX Quantum 4, 020315 (2023)]. In this work, we broaden the scope of this approach and demonstrate that a diverse class of MPS can be exactly prepared using constant-depth adaptive quantum circuits, outperforming theoretically optimal preparation with unitary circuits. We show that this class includes short- and long-ranged entangled MPS, symmetry-protected topological (SPT) and symmetry-broken states, MPS with finite Abelian, non-Abelian, and continuous symmetries, resource states for MBQC, and families of states with tunable correlation length. Moreover, we illustrate the utility of our framework for designing constant-depth sampling protocols, such as for random MPS or for generating MPS in a particular SPT phase. We present sufficient conditions for particular MPS to be preparable in constant time, with global on-site symmetry playing a pivotal role. Altogether, this work demonstrates the immense promise of adaptive quantum circuits for efficiently preparing many-body entangled states and provides explicit algorithms that outperform known protocols to prepare an essential class of states. Published by the American Physical Society 2024

Smith, Kevin C. (ORCID:0000000223971518)↗
DOE OSTI2024

Porting Classical Approaches for Quantum Simulations to Quantum Computers

Simulating quantum many-body systems is one of the most promising problems in which we might anticipate that quantum computers should show quantum advantage. Unfortunately, there is still a gap between this promise and actual practice. New quantum algorithms need to be developed and the current quantum algorithms have various difficulties - e.g efficient state preparation - which must be overcome and improved upon. In many cases, classical approaches need to be ported over to quantum devices. In this project we have developed a suite of new quantum algorithms which makes progress in this regard. We developed a new optimization scheme for variational quantum eigensolvers, UBOS, which mitigates problems with local minimas and barren plateaus while improving convergence to the ground state by an order of magnitude. We developed a new way to utilize qubitization to find ground states of nearly frustration-free Hamiltonians faster than all previous methods. We developed a series of state preparation techniques which helps initialize parameterized quantum circuits into reasonable starting points on which quantum algorithms are then applied. In addition to the development of novel algorithms, it is critical to have classical simulation techniques for approximately simulating quantum circuits which can be used to benchmark and understand quantum algorithms. Toward that end, we developed a novel POVM formalism to simulate quantum circuits as well as exemplify the massive parallelization of tensor network methodologies. Finally, we developed physical understanding of entanglement phase transitions such as many-body localization and random tensor networks.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1980

Calculation of power spectrums from digital time series with missing data points

Two algorithms are developed for calculating power spectrums from the autocorrelation function when there are missing data points in the time series. Both methods use an average sampling interval to compute lagged products. One method, the correlation function power spectrum, takes the discrete Fourier transform of the lagged products directly to obtain the spectrum, while the other, the modified Blackman-Tukey power spectrum, takes the Fourier transform of the mean lagged products. Both techniques require fewer calculations than other procedures since only 50% to 80% of the maximum lags need be calculated. The algorithms are compared with the Fourier transform power spectrum and two least squares procedures (all for an arbitrary data spacing). Examples are given showing recovery of frequency components from simulated periodic data where portions of the time series are missing and random noise has been added to both the time points and to values of the function. In addition the methods are compared using real data. All procedures performed equally well in detecting periodicities in the data.

Murray, C. W., Jr.↗
NASA NTRS1990

Evaluation of voice codecs for the Australian mobile satellite system

The evaluation procedure to choose a low bit rate voice coding algorithm is described for the Australian land mobile satellite system. The procedure is designed to assess both the inherent quality of the codec under 'normal' conditions and its robustness under 'severe' conditions. For the assessment, normal conditions were chosen to be random bit error rate with added background acoustic noise and the severe condition is designed to represent burst error conditions when mobile satellite channel suffers from signal fading due to roadside vegetation. The assessment is divided into two phases. First, a reduced set of conditions is used to determine a short list of candidate codecs for more extensive testing in the second phase. The first phase conditions include quality and robustness and codecs are ranked with a 60:40 weighting on the two. Second, the short listed codecs are assessed over a range of input voice levels, BERs, background noise conditions, and burst error distributions. Assessment is by subjective rating on a five level opinion scale and all results are then used to derive a weighted Mean Opinion Score using appropriate weights for each of the test conditions.

Bundrock, Tony↗
NASA NTRS1998

Earth Probe Total Ozone Mapping Spectrometer (TOMS) Data Product User's Guide

Two data products from the Earth Probe Total Ozone Mapping Spectrometer (EP/TOMS) have been archived at the Distributed Active Archive Center, in the form of Hierarchical Data Format files. The EP/ TOMS began taking measurements on July 15, 1996. The instrument measures backscattered Earth radiance and incoming solar irradiance; their ratio is used in ozone retrievals. Changes in the reflectivity of the solar diffuser used for the irradiance measurement are monitored using a carousel of three diffusers, each exposed to the degrading effects of solar irradiation at different rates. The algorithm to retrieve total column ozone compares measured Earth radiances at sets of three wavelengths with radiances calculated for different total ozone values. The initial error in the absolute scale for TOMS total ozone is 3 percent, the one standard deviation random error is 2 percent, and the drift is less than 0.5 percent over the first year of data. The Level-2 product contains the measured radiances, the derived total ozone amount, and reflectivity information for each scan position. The Level-3 product contains daily total ozone and reflectivity in a 1-degree latitude by 1.25 degrees longitude grid. Level-3 files containing estimates of LTVB at the Earth surface and tropospheric aerosol information are also available, Detailed descriptions of both HDF data-files and the CD-ROM product are provided.

McPeters, R.↗
NASA NTRS2006

Estimating Random Errors Due to Shot Noise in Backscatter Lidar Observations

In this paper, we discuss the estimation of random errors due to shot noise in backscatter lidar observations that use either photomultiplier tube (PMT) or avalanche photodiode (APD) detectors. The statistical characteristics of photodetection are reviewed, and photon count distributions of solar background signals and laser backscatter signals are examined using airborne lidar observations at 532 nm using a photon-counting mode APD. Both distributions appear to be Poisson, indicating that the arrival at the photodetector of photons for these signals is a Poisson stochastic process. For Poisson-distributed signals, a proportional, one-to-one relationship is known to exist between the mean of a distribution and its variance. Although the multiplied photocurrent no longer follows a strict Poisson distribution in analog-mode APD and PMT detectors, the proportionality still exists between the mean and the variance of the multiplied photocurrent. We make use of this relationship by introducing the noise scale factor (NSF), which quantifies the constant of proportionality that exists between the root-mean-square of the random noise in a measurement and the square root of the mean signal. Using the NSF to estimate random errors in lidar measurements due to shot noise provides a significant advantage over the conventional error estimation techniques, in that with the NSF uncertainties can be reliably calculated from/for a single data sample. Methods for evaluating the NSF are presented. Algorithms to compute the NSF are developed for the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar and tested using data from the Lidar In-space Technology Experiment (LITE). OCIS Codes:

Liu, Zhaoyan↗