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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Low-latency quantum control using AI algorithms on cryogenic microelectronics platforms

Superconducting quantum computers are a particular technology that involve the realization of qubits by means of LC circuits with a Josephson junction. As shown in Fig. 1, this latter addition has the effect of introducing a nonlinearity (anharmonicity) that makes the frequency spacing between each energy level non-uniform. This is a desired effect for separating the two lowest levels, used for computation, from the higher ones, that are theoretically infinite and which are not desired to be used.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Analysis of the automatic reconstruction of protons from simulated neutrino interactions in the ICARUS detector: study of the performance of track vs shower discrimination algorithms

ICARUS, Imaging Cosmic and Rare Underground Signals, is the far detector of the Short Baseline Neutrino (SBN) Program at Fermi National Accelerator Laboratory (FNAL). This program was born with the purpose of definitely explaining some anomalies in the field of neutrino oscillation physics, that can suggest the existence of a 4-type of neutrino: the sterile neutrino. It doesn’t interact directly with ordinary matter through the weak interaction, but we can observed the effect of its oscillation. In this chapter I will briefly observe: • the physics goals of the SBN Program; • the role of ICARUS as SBN far detector; • the detection technology.

43 PARTICLE ACCELERATORS↗
DOE OSTI2025

Small Scale Melter Testing of HLW Algorithm Glasses: Matrix 1 Tests

The principal objectives of the DM100 tests were to determine the effects of glass property extremes (glass viscosity, electrical conductivity, and T1%), minimum and maximum concentrations of several major and minor glass components, +/-15% batching errors in the addition of Glass Forming Chemicals (GFCs) to the feed, and variation in the sources of boron and sodium used in the GFCs on processing rates and melter conditions (off-gas characteristics, glass processing, foaming, cold cap, etc.) at constant bubbling rate.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Energy-efficient, Large-scale Molecular Dynamics Simulations via Hardware- and Algorithm-level Optimization

This work aims to develop a framework for energy-efficient computing that will enable molecular dynamics (MD) simulations of large-scale phenomena with atomic precision and simultaneously remove computational bottlenecks limiting the speed of MD simulations. We seek to implement such an approach through the development of surrogate models for the interatomic force calculation combined with the use of mixed numerical precision formats. For a model system of neutral atoms (only pairwise interactions), significant force calculation efficiency improvements were achieved, without detrimental effects on atomic structures or average energies, using single precision, by developing a surrogate model (deep neural network), and by quantizing this surrogate model. For a model system of charged atoms, the reciprocal-space calculation of electrostatic interactions was identified as the main bottleneck, and the development of a surrogate model should be pursued to achieve an estimated one-order-of-magnitude additional speedup.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Portable Parallel Algorithms and Frameworks for Exascale Graph Analytics

Graphs (or networks) are a tool used to model the interactions among various entities. Efficiently processing large graphs has recently attracted significant attention due to the applications of graphs in various domains, such as biology, chemistry, and cyber-security. Analyzing the structure and properties of these graphs is an important component of many scientific computing pipelines. With the explosion in the volume of data, graphs have become very large and can contain hundreds of billions of vertices and trillions of edges. Therefore, it is crucial to develop high-performance methods to enable graph analysis to be done quickly and energy-efficiently. Furthermore, these solutions should be highly parallel in order to take advantage of modern parallel machines. However, designing efficient solutions is not enough. With the wide variety of computing environments available, each with different programmability and performance characteristics, it is necessary to develop solutions that are portable in terms of both performance (i.e., provide theoretical guarantees) and programmability (i.e., provide high level abstractions).

97 MATHEMATICS AND COMPUTING↗