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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 487 records · Page 27

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NASA NTRS2004

Simple broadband implementation of a phase contrast wavefront sensor for adaptive optics

The most critical element of an adaptive optics system is its wavefront sensor, which must measure the closed-loop difference between the corrected wavefront and an ideal template at high speed, in real time, over a dense sampling of the pupil. Most high-order systems have used Shack-Hartmann wavefront sensors, but a novel approach based on Zernike's phase contrast principle appears promising. In this paper we discuss a simple way to achromatize such a phase contrast wavefront sensor, using the pi/2 phase difference between reflected and transmitted rays in a thin, symmetric beam splitter. We further model the response at a range of wavelengths to show that the required transverse dimension of the focal-plane phase-shifting spot, nominally lambda/D, may not be very sensitive to wavelength, and so in practice additional optics to introduce wavelength-dependent transverse magnification achromatizing this spot diameter may not be required. A very simple broadband implementation of the phase contrast wavefront sensor results.

wavefront sensors↗

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 OSTI2025

Point cloud-based diffusion models for the Electron-Ion Collider

At high-energy collider experiments, generative models can be used for a wide range of tasks, including fast detector simulations, unfolding, searches of physics beyond the Standard Model, and inference tasks. In particular, it has been demonstrated that score-based diffusion models can generate high-fidelity and accurate samples of jets or collider events. This work expands on previous generative models in three distinct ways. First, our model is trained to generate entire collider events, including all particle species with complete kinematic information. We quantify how well the model learns event-wide constraints such as the conservation of momentum and discrete quantum numbers. We focus on the events at the future Electron-Ion Collider, but we expect that our results can be extended to proton-proton and heavy-ion collisions. Second, previous generative models often relied on image-based techniques. The sparsity of the data can negatively affect the fidelity and sampling time of the model. We address these issues using point clouds and a novel architecture combining edge creation with transformer modules called Point Edge Transformers. Third, we adapt the foundation model OmniLearn, to generate full collider events. This approach may indicate a transition toward adapting and fine-tuning foundation models for downstream tasks instead of training new models from scratch.

Araz, Jack Y. [Stony Brook Univ., NY (United State↗

DOE OSTI2024

SmoQyDQMC.jl: A flexible implementation of determinant quantum Monte Carlo for Hubbard and electron-phonon interactions

We introduce the SmoQyDQMC.jl package, a Julia implementation of the determinant quantum Monte Carlo algorithm. SmoQyDQMC.jl supports generalized tight-binding Hamiltonians with on-site Hubbard and generalized electron-phonon ( e e -ph) interactions, including non-linear e e -ph coupling and anharmonic lattice potentials. Our implementation uses hybrid Monte Carlo methods with exact forces for sampling the phonon fields, enabling efficient simulation of low-energy phonon branches, including acoustic phonons. The SmoQyDQMC.jl package also uses a flexible scripting interface, allowing users to adapt it to different workflows and interface with other software packages in the Julia ecosystem. The code for this package can be downloaded from our GitHub repository at https://github.com/SmoQySuite/SmoQyDQMC.jl or installed using the Julia package manager. The online documentation, including examples, can be obtained from our document page at https://smoqysuite.github.io/SmoQyDQMC.jl/stable/.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2024

Codebase release r0.3 for SmoQyDQMC.jl

Cohen-Stead, Benjamin (ORCID:0000000279156280)↗

DOE OSTI2026

Bayesian chain graph models to characterize microbe-environment dynamics

Microbiome data require statistical models that can simultaneously decode microbes' reaction to the environment and interactions among microbes. While a multiresponse linear regression model seems like a straight-forward solution, we argue that treating it as a graphical model is problematic given that the regression coefficient matrix does not encode the conditional dependence structure between response and predictor nodes. This observation is especially important in biological settings when we have prior knowledge on the edges from specific experimental interventions that can only be properly encoded under a conditional dependence model. Here, we propose a chain graph model with two sets of nodes (predictors and responses) whose solution yields a graph with edges that indeed represent conditional dependence, thus agreeing with the experimenter's intuition on the average behavior of nodes under treatment. The solution to our model is sparse via the Bayesian linear regression (LASSO). In addition, we propose an adaptive extension so that different shrinkages can be applied to different edges to incorporate edge-specific prior knowledge. Our model is computationally inexpensive through an efficient Gibbs sampling algorithm and can account for binary, counting, and compositional responses via an appropriate hierarchical structure. We test the performance of our model in a variety of simulated datasets, thereby showing superior performance to state-of-the-art approaches. We further apply our model to human gut and soil microbial compositional datasets, and we highlight that CG-LASSO can estimate biologically meaningful network structures in the data.

compositional data↗

NASA NTRS1994

Experiment K-7-31: Studies of Vestibular Primary Afferents and Eye Movements in Normal, Hypergravity and Hypogravity - Axon Cosmos Flight 2044

Fourteen days of active head movements in microgravity appear to modify the gain and neural adaptation properties of the horizontal semicircular canals in the rhesus monkey. This is the first demonstration of adaptive plasticity in the sensory receptor. Reversing prisms, for example, do not modify the gain of the primary afferent response. Pulse yaw rotation, sinusoidal rotation, and sum of sinusoidal rotation testing during the first day following recovery revealed that the gain of a sample of afferents was significantly greater than the gain derived from afferent responses obtained during pre-flight and control monkey testing. There was no strong evidence of tilt sensitivity in the sample of afferents that we tested either during the pre-flight or control tests or during the first day post-flight. Two irregular afferents tested on postflight day 2 showed changes with tilt but the responses were not systematic. The spontaneous discharge did not change following flight. Mean firing rate and coefficient of variation remained constant during the post flight tests and was near the value measured during pre flight tests. The change in gain of horizontal canal afferents might be adaptive. The animals were required to look at a target for food. This required active head and eye movements. Active head movements have been shown to be hypometric and eye movements have been shown to be hypermetric during the first few days of past Cosmos flights (see introduction). It might be that the increased gain in the horizontal semicircular canals permit accurate target acquisition during hypometric head movements by driving the eyes to greater angles for smaller angles of head movement. The mechanism by which the semicircular canals recalibrate (increase their gain) is unknown. The efferent vestibular system is a logical candidate. Horizontal nystagmus during rotation about an earth vertical axis with the horizontal semicircular canals in the plane of rotation produced the same response during postflight day 1 and post-flight day 9. But when the head was pitched down 45? the nystagmus slow phase velocity was greater and the duration was about twice during post-flight day 1. Apparently, this response involving the interaction of the horizontal and vertical semicircular canals and the otoliths did not recalibrate during post-flight day 1. The 'DC' bias of the slow phase velocity of the horizontal nystagmus during constant velocity horizontal axis rotation was roughly 4 times for one flight monkey and roughly 2 times for the other on post-flight day 1 compared to post-flight day 9. These results suggest that the otolith mediated response during constant velocity rotation also did not recalibrate on post-flight day 1.

Correia, M. J.↗

DOE OSTI2025

Adaptation and Plasticity of Nannochloropsis sp. in Response to Seasonal and Geographic Climate Variation

Phytoplankton respond to their environment through genetic adaptation and plasticity to maintain fitness. This poses challenges when growing microalgae for industrial applications because, inherently, outdoor mass cultivation may lead to adaptations that alter desirable phenotypic traits and environmental niches. Here, we used common garden experiments to quantify the plasticity and adaptive responses to seasonal and geographic climate variation of Nannochloropsis, a microalga commonly used in biotechnology. An initially monoclonal strain was grown outdoors across four locations in Hawaii, Texas, California, and New Mexico. Following 17 and 22 months of cultivation outdoors, we collected samples during winter and summer, respectively, and we compared strains' growth from the four sites across temperature and light gradients in the laboratory. Despite hundreds of generations of exposure to divergent climates, with ~20°C and three-fold differences in daily light intensity, strains showed only minor differences in performance. Thermal performance varied more among seasons than sites, whereas light performance varied with both season and site. Our study indicates that Nannochloropsis exhibits broad plasticity in response to light and temperature, which may inhibit genetic adaptation in space or time. Highly variable field conditions, with daily and seasonal climate fluctuations, may favor plasticity and prevent the rapid adaptation often seen in laboratory studies of microorganisms in constant environments.

common garden experiment↗

NASA NTRS1992

CGF toxic sample handling using a flexible glovebox

This paper discusses design and operational issues encountered in designing a flexible glovebox to be used on a microgravity crystal growth experiment. The glovebox discussed protects the crew from exposure to hazardous particulates, and is adaptable to other payloads.

Lecroy, J.↗

DOE OSTI2025

Conditioned quantum-assisted deep generative surrogate for particle-calorimeter interactions

Particle collisions at accelerators like the Large Hadron Collider (LHC), recorded by experiments such as ATLAS and CMS, enable precise standard model measurements and searches for new phenomena. Simulating these collisions significantly influences experiment design and analysis but incurs immense computational costs, projected at millions of CPU-years annually during the high luminosity LHC (HL-LHC) phase. Currently, simulating a single event with Geant4 consumes around 1000 CPU seconds, with calorimeter simulations especially demanding. To address this, we propose a conditioned quantum-assisted generative model, integrating a conditioned variational autoencoder (VAE) and a conditioned restricted Boltzmann machine (RBM). Our RBM architecture is tailored for D-Wave’s Pegasus-structured advantage quantum annealer for sampling, leveraging the flux bias for conditioning. This approach combines classical RBMs as universal approximators for discrete distributions with quantum annealing’s speed and scalability. We also introduce an adaptive method for efficiently estimating effective inverse temperature, and validate our framework on Dataset 2 of CaloChallenge.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1975

Users manual for flight control design programs

Computer programs for the design of analog and digital flight control systems are documented. The program DIGADAPT uses linear-quadratic-gaussian synthesis algorithms in the design of command response controllers and state estimators, and it applies covariance propagation analysis to the selection of sampling intervals for digital systems. Program SCHED executes correlation and regression analyses for the development of gain and trim schedules to be used in open-loop explicit-adaptive control laws. A linear-time-varying simulation of aircraft motions is provided by the program TVHIS, which includes guidance and control logic, as well as models for control actuator dynamics. The programs are coded in FORTRAN and are compiled and executed on both IBM and CDC computers.

Nalbandian, J. Y.↗

NASA NTRS1992

Venturi air-jet vacuum ejectors for high-volume atmospheric sampling on aircraft platforms

Documentation of the installation and use of venturi air-jet vacuum ejectors for high-volume atmospheric sampling on aircraft platforms is presented. Information on the types of venturis that are useful for meeting the pumping requirements of atmospheric-sampling experiments is also presented. A description of the configuration and installation of the venturi system vacuum line is included with details on the modifications that were made to adapt a venturi to the NASA Electra aircraft at GSFC, Wallops Flight Facility. Flight test results are given for several venturis with emphasis on applications to the Differential Absorption Carbon Monoxide Measurement (DACOM) system at LaRC. This is a source document for atmospheric scientists interested in using the venturi systems installed on the NASA Electra or adapting the technology to other aircraft.

Hill, Gerald F.↗

NASA NTRS1994

NASA Lewis Research Center lean-, rich-burn materials test burner rig

The lean-, rich-burn materials test burner rig at NASA LeRC is used to evaluate the high temperature environmental durability of aerospace materials. The rig burns jet fuel and pressurized air, and sample materials can be subjected to both lean-burn and rich-burn environments. As part of NASA's Enabling Propulsion Materials (EPM) program, an existing rig was adapted to simulate the rich-burn quick-quench lean-burn (RQL) combustor concept which is being considered for the HSCT (high speed civil transport) aircraft. RQL materials requirements exceed that of current superalloys, thus ceramic matrix composites (CMC's) emerged as the leading candidate materials. The performance of these materials in the quasi reducing environment of the rich-burn section of the RQL is of fundamental importance to materials development. This rig was developed to conduct such studies, and its operation and capabilities are described.

Stearns, C. A.↗

NASA NTRS2003

Development and Flight Testing of an Adaptable Vehicle Health-Monitoring Architecture

Development and testing of an adaptable wireless health-monitoring architecture for a vehicle fleet is presented. It has three operational levels: one or more remote data acquisition units located throughout the vehicle; a command and control unit located within the vehicle; and a terminal collection unit to collect analysis results from all vehicles. Each level is capable of performing autonomous analysis with a trained adaptable expert system. The remote data acquisition unit has an eight channel programmable digital interface that allows the user discretion for choosing type of sensors; number of sensors, sensor sampling rate, and sampling duration for each sensor. The architecture provides framework for a tributary analysis. All measurements at the lowest operational level are reduced to provide analysis results necessary to gauge changes from established baselines. These are then collected at the next level to identify any global trends or common features from the prior level. This process is repeated until the results are reduced at the highest operational level. In the framework, only analysis results are forwarded to the next level to reduce telemetry congestion. The system's remote data acquisition hardware and non-analysis software have been flight tested on the NASA Langley B757's main landing gear.

Woodard, Stanley E.↗

NASA NTRS2014

System and Method for Isolation of Samples

Systems and methods for isolating samples are provided. The system comprises a first membrane and a second membrane disposed within an enclosure. First and second reservoirs can also be disposed within the enclosure and adapted to contain one or more reagents therein. A first valve can be disposed within the enclosure and in fluid communication with the first reservoir, the second reservoir, or both. The first valve can also be in fluid communication with the first or second membranes or both. The first valve can be adapted to selectively regulate the flow of the reagents from the first reservoir, through at least one of the first and second membranes, and into the second reservoir.

Zhang, Ye↗

NASA NTRS1992

In vitro measurement of nucleus pulposus swelling pressure: A new technique for studies of spinal adaptation to gravity

Swelling of the intervertebral disc nucleus pulposus is altered by posture and gravity. We have designed and tested a new osmometer for in vitro determination of nucleus pulposus swelling pressure. The functional principle of the osmometer involves compressing a sample of nucleus pulposus with nitrogen gas until saline pressure gradients across a 0.45 microns Millipore filter are eliminated. Swelling pressure of both pooled dog and pooled pig lumbar disc nucleus pulposus were measured on the new osmometer and compared to swelling pressures determined using the equilibrium dialysis technique. The osmometer measured swelling pressures comparable to those obtained by the dialysis technique. This osmometer provides a rapid, direct, and accurate measurement of swelling pressure of the nucleus pulposus.

Hargens, A. R.↗

DOE OSTI2025

Development and characterization of a wild emmer wheat backcross introgression population for hard winter wheat improvement

Abstract Wild emmer wheat (Triticum turgidumsubsp.dicoccoides) is the tetraploid progenitor of hexaploid bread wheat (Triticum aestivumL.) and is known to be a valuable source of genetic variation for wheat improvement. However, direct evaluation of wild emmer diversity for agronomic potential has limited value unless performed in the backgrounds of adapted cultivars. Here, we present a genetic characterization of a population of 1601 backcross recombinant inbred lines, with an average genome composition of 75% bread wheat and 25% wild emmer. Low‐coverage whole‐genome sequencing allowed introgressions and aneuploidies to be identified at a relatively low cost per sample. We identified a relatively large proportion of small introgressions (median length 38 Mb), and we found introgressions to be distributed across all chromosomes. Approximately 44% of genotyped progeny carried at least one aneuploidy, with monosomies being by far the most common. This population, which we have denoted as the Great Plains Wild Emmer/Hard Winter Wheat introgression population (GPWEW‐IP), is, to our knowledge, the first introgression population developed through the direct hybridization of wild emmer wheat and US‐adapted hard winter wheat. We believe that this population represents a valuable resource for wheat breeders and will accelerate the discovery and integration of useful variation from wild emmer wheat.

Genetics & Heredity↗

DOE OSTI2024

Algorithm 1049: The Delaunay Density Diagnostic

Accurate approximation of a real-valued function depends on two aspects of the available data: the density of inputs within the domain of interest and the variation of the outputs over that domain. There are few methods for assessing whether the density of inputs is sufficient to identify the relevant variations in outputs—i.e., the “geometric scale” of the function—despite the fact that sampling density is closely tied to the success or failure of an approximation method. In this article, we introduce a general purpose, computational approach to detecting the geometric scale of real-valued functions over a fixed domain using a deterministic interpolation technique from computational geometry. The algorithm is intended to work on scalar data in moderate dimensions (2–10). Our algorithm is based on the observation that a sequence of piecewise linear interpolants will converge to a continuous function at a quadratic rate (in L 2 norm) if and only if the data are sampled densely enough to distinguish the feature from noise (assuming sufficiently regular sampling). We present numerical experiments demonstrating how our method can identify feature scale, estimate uncertainty in feature scale, and assess the sampling density for fixed (i.e., static) datasets of input–output pairs. Finally, we include analytical results in support of our numerical findings and have released lightweight code that can be adapted for use in a variety of data science settings.

97 MATHEMATICS AND COMPUTING↗